Urgent Appeal: Freeze CERN Funding, Fund Innovations Suppressed for 32 Years That Can Save Millions of Lives and Billions of Euros

32 Years of Suppression and Plagiarism of a Recognized Breakthrough: It is Time for Scientists and Leaders with Integrity to Endorse Funding the Inventor and Unlock the Full Potential for Cost-Effective Advances in Physics and Life-Saving Cancer Detection

DALLAS, Aug. 28, 2025 (GLOBE NEWSWIRE) -- (In PDF: https://bit.ly/3UCW8XE) The Crosetto Foundation for the Reduction of Cancer Deaths, a registered nonprofit organization, urgently calls on the public to help expose and correct scientific and institutional inconsistencies that any person—with or without a scientific background—can understand through common sense and factual evidence.

A Media Snippet accompanying this announcement is available by clicking on this link.

These inconsistencies have harmed taxpayers, patients, and the advancement of science. They can be fixed with dialogue, transparency, and your support. Please consider contributing $10, $20, $50, or whatever you can via online donation (https://crosettofoundation.org/donate-now/) or if you have Zelle app on your phone or computer, send your donation directly to donate@crosettofoundation.org [1]. If you cannot donate, your voice still matters—read on to learn how to take action.

Two grave inconsistencies stand out:

• CERN has wasted over €4 billion of taxpayer money over the past three decades, with a projected >€12 billion in further waste over the next 10 years, unless transparency and accountability are implemented [2], [3].
• Meanwhile, over 39 million lives have been lost prematurely to cancer, with another 69 million deaths projected over the next seven years—despite the availability of cost-effective early detection technology [4].
  
  

If you're unable to donate, you can still make a meaningful impact by contacting your elected representatives in the U.S. or Europe and urging them to act. (To make this easier, we’ve provided a tool to find your representative [5] and a template letter [6]).

EXECUTIVE SUMMARY

This document presents verifiable facts exposing the suppression of two life-saving, cost-reducing inventions—3D-Flow for high-energy physics, and 3D-CBS for early cancer detection. Although recognized as a scientific breakthrough at Fermilab in 1993 and in several international, public scientific reviews (see Sections 3, 6.4, 6.5, 6.6.3, and 10), these inventions have never been funded, despite being unrefuted, but instead have been suppressed for more than three decades.

Meanwhile, billions in taxpayer funding continue to be allocated to less effective technologies that waste public resources on flawed systems (see Ref. [9]). In particular, CERN continues to waste billions of taxpayer euros despite well-documented inefficiencies and flaws (see Sections 9.1.1, 9.1.2).

Only transparency, accountability, and cooperation through open dialogue can save CERN from the misuse of trust, funds, and scientific authority (Sec. 11), resulting in the waste of billions, and the blocking of innovations in particle detection—thereby also blocking advances in cancer detection that could have already saved millions of lives. (Sec. 13.1).

The 3D-Flow invention filters valuable signals from radiation for two distinct applications. In particle physics, it detects new particles like the Higgs boson. In medical imaging, specifically with the 3D-CBS device, it detects signals from radiation associated with tumor markers. This allows for the cost-effective, early detection of diseases like cancer, ultimately saving lives. (Secs. 1.2, 2).

The central issue is the continued, decades-long funding of CERN’s FPGA-based approach, which has proven to be incapable of efficiently filtering 1.2 billion events per second from the LHC’s radiation. The 3D-Flow breakthrough invention has been officially recognized as solving this problem, and yet its inventor continues to be excluded from a public dialogue with CERN’s FPGA-based Level-1 Trigger designers (Secs. 6.4.4, 9, 14.1.2).

The escalation of CERN’s multiple flawed FPGA systems—which have already wasted over €4 billion in decades (Sec. 8)—has culminated in CERN’s reliance on a massive 20-trillion-transistor, ~650 kW FPGA Trigger system planned for the next ten years, 2026–2036, to filter valuable data from radiation arriving at 8-billion events per second from the HL-LHC. It was approved by the CERN Council on 20 June 2025 [9], alongside other ATLAS and CMS upgrades. This Level-1 Trigger system is limited to executing approximately 66 operations on each dataset arriving every 25 nanoseconds making it also destined to fail. The result will be a projected waste of over €12 billion in the next decade (Sec. 9.1.3).

By contrast, Crosetto’s 3D-Flow system operates at ~6 kW and performs over 8,000 operations per dataset offering a vastly more efficient and powerful alternative (Secs. 6.3, 7, 10, 14.1.7, 17.2).

Twenty-five years after the invention of the 3D-CBS, the necessary resources should be provided to the inventor to experimentally test his inventions, which can save billions in physics experiments, enable the discovery of new particles, with the potential to halve premature cancer deaths—saving millions of lives and billions of euros by significantly reducing the global financial burden of cancer care (Secs. 10, 11.1, 12, 17.2).

The path forward requires more than just funding; it demands a recommitment to core principles of scientific integrity: honesty, the humility to accept experimental failure, and an openness for dialogue and cooperation to understand and respect nature’s laws (Secs. 6.4, 13.3, 17.2).

Humility includes learning from errors (Sec. 6.8), comparing the FPGA approach with the 3D-Flow solution that has existed for 32 years, and cooperating to implement the higher performing and most cost-effective solution. It also requires accepting the undisputed failures highlighted by Crosetto during his two-hour, 102-slide presentation [13] granted by the Chairs of the 2024 IEEE-NSS-MIC-RTSD conference attended by 1,300 scientists, with video and slides made available on the IEEE website without being challenged. (Sec. 14.1.6)

However, the transparency implemented by IEEE in 2024 should not have been reversed on 14 April 2025, when IEEE denied Crosetto the right to share his 82-page article [25] from preprint, followed by the suppression of his two 2-page articles [2], [3] submitted to the 2025 IEEE-NSS-MIC-RTSD Conference detailing mistakes made and the remedies. (Secs. 9.1.2, 14.1.7).

IEEE continued to approve articles on FPGA-Based Level-1 Triggers, while CERN Council ignored their flaws. On 20 June 2025 [9], the Council approved the CMS and ATLAS upgrades—relying on an FPGA-Based Level-1 Trigger system almost completely built for 2026–2036—a decision that will waste over $12 billion in the next decade.

There needs to be an open, public dialogue between the 3D-Flow and 3D-CBS inventor and all relevant institutions—CERN and IEEE taking a leading role—to ensure a transparent, reliable, and ethical approach to uncovering the scientific truth for the benefit of humanity. Such a collaborative, truth-seeking process will not only benefit patients and taxpayers but will also restore public trust in the institutions and individuals dedicated to advancing science for the good of humanity. (Secs. 13.3, 14.1.7, 17.2, 17.3).

By unlocking these medical applications, we can save countless lives, significantly reduce the global financial burden of cancer care, and ensure fewer families lose loved ones too soon (Secs. 2, 3, 6.6.2, 12, 13.3, 14.1.3, 14.1.5).

Key Facts

• Scientific Breakthrough Suppressed: In 1993, a major public scientific review at Fermilab declared Crosetto’s 3D-Flow invention a breakthrough [10], yet anonymous reviewers and influential scientists have consistently suppressed it (Secs. 6.4, 6.5).
• Performance Advantage: The 3D-Flow, capable of over 8,000 operations per dataset while using ~6 kW, can efficiently detect new particles and cancer, unlike CERN’s ~650 kW FPGA systems limited to ~66 operations, which cannot detect particles efficiently (Sec. 7.3.6).
• Medical Impact: The 3D-Flow concept is implemented in the 3D-CBS which enables the safe screening of ~90,000 individuals per year, per device, at €200 per test and, based on early detection, can save over 260 lives per device, per year (Sec. 12.3).
• Suppression Pattern: Despite submitting peer-reviewed papers and receiving editor invitations, Crosetto’s manuscripts were excluded by anonymous reviewers or denied by influencers without valid scientific reasons (Secs. 14.1.7, 14.5, 15.2).
• Plagiarism Documented: In 2015, U.S. universities copied key ideas from Crosetto’s 2000 3D-CBS book to build the EXPLORER PET/CT system—at six times the cost and with reduced efficiency (Sec. 17.2).
• CERN Director of Research's Failed Project: CERN’s Director of Research awarded himself first prize at the 2010 ‘Physics for Health’ workshop, but the project failed (Secs. 11, 13.2).
• CERN-ATTRACT Misstep: The CERN-ATTRACT consortium, led by CERN’s same former Director of Research, funded WPET—an implausible 350+ kg cancer-screening coat (Secs. 11.1, 13.1).
• CERN Blunder which claimed a Neutrino to be faster than Light was due to poor experimental design, and a failure to apply fundamental principles of measurement accuracy. (Sec. 13).
  
  

Solution

Hold a public scientific comparison between CERN’s current system and Crosetto’s 3D-Flow system. This will introduce transparency and accountability, and enable an objective evaluation based on merit, power consumption, and operational capacity. Implementing this solution would not only save billions in misallocated taxpayer funds but also unlock the potential of 3D-Flow for broader applications, including 3D-CBS—accelerating the development of life-saving innovations for cancer patients.

Call to Action

1. Freeze current and future funding for CERN’s FPGA-based Level-1 Triggers for CMS and ATLAS upgrades, approved by the CERN Council on 20 June 2025 [9], until a public scientific comparison is held (Secs. 11, 13.1).
2. Fund Italian-American scientist Dario Crosetto, the inventor of the 3D-CBS, to build 2 prototypes with less than 0.00000067 of the $30 trillion already spent on global R&D since his inventions (Secs. 16, 17.2.b, 17.3.b).
3. Share this appeal with media, institutions, and elected representatives (Sec. 17.c).
4. Contact officials responsible for cancer research, transparency, and stewardship of taxpayer funds (Sec. 17.3.a).
5. Donate to support transparency, scientific integrity, and the implementation of open, public scientific procedures to let the scientific truth emerge for the benefit of humanity: https://crosettofoundation.org/donate-now/ (Sec. 17.b).
   
   

See Previous 400-word, 3 July 2025, GLOBE Newswire Press Release at: https://www.globenewswire.com/news-release/2025/07/03/3109825/0/en/Only-Transparency-and-Accountability-Can-Save-CERN-Stop-Billions-in-Waste-Unlock-Life-Saving-Innovations.html

Public Scientific Review Urgently Needed

Preventing Further Waste at CERN and Halving Cancer Deaths
with the 3D-Flow and 3D-CBS Inventions Suppressed for 32 Years

We respectfully urge action on the following:

a) Fund the Inventor of the 3D-Flow Breakthrough

After 32 years, the 3D-Flow invention, officially recognized in a public international scientific review at Fermilab in 1993 as a breakthrough solving a key bottleneck in real-time data processing for particle physics, remains unfunded. It offers a powerful, scalable tool for physicists to discover new particles, advance science, reduce costs, and—critically—save millions of lives by enabling cost-effective early cancer detection Billion-dollar physics experiments and Medical Imaging devices have one thing in common: they both deal with radiation. The 3D-Flow invention is capable of filtering valuable data from this radiation. In medical imaging, specifically in the 3D-CBS (3D Complete Body Screening), an advanced PET/CT (Positron Emission Tomography) device, it filters valuable data from radiation associated with tumor markers. This allows for the cost-effective, early detection of many diseases, including cancer, ultimately saving lives. Funding the inventor with just 0.00000067 of the over $30 trillion spent on research and development globally since 1993 would allow him to build two 3D-CBS [7] (3D Complete Body Screening) prototypes.

These devices could experimentally demonstrate how cancer deaths and healthcare costs can be cut in half within a selected population.

Funding the inventor is not only fair to taxpayers, cancer patients, and science—it is long overdue, both ethically and scientifically.

b) Enforce the code of conduct, the code of ethics [8], and transparency among scientists, eliminating the shielding of corruption through anonymous reviewers

Call for responsibility from those who manage taxpayer money by freezing public funding to the CERN CMS and ATLAS upgrades, approved by CERN Council on 20 June 2025 [9], which have already wasted more than $4 billion over the past decades.

These upgrades rely on FPGA-based Level-1 Trigger systems, whose architecture, based on clear technical evidence, is expected to waste an additional €12 billion in the next decade.

A transparent, public scientific meeting is requested between CERN’s trigger system designers and the inventor of the 3D-Flow architecture. This meeting needs to be side by side, in an open scientific dialogue, to allow the fact to emerge. Only through such cooperation can the truth—and its benefits for humanity—be fully realized.

Only Transparency and Accountability Can Save CERN

Note to Readers: Sections marked ‘[TECHNICAL]’ contain detailed content for scientists and experts. General readers may skip them. For clarity and ease of reference, key details are reiterated so readers can find information without recalling the entire text, and important section can be read as a stand-alone unit.

1. What Are the Problems That Must Be Solved?

1.1 The Stumbling Block in Physics at CERN

The problem that experimental physicists at CERN must solve is unprecedented in scale:

• Year 2000: The CERN Large Hadron Collider (LHC) was originally expected to generate 600 million events per second.
• 2016–2026: The CERN LHC has produced approximately 1.2 billion events per second, with up to 2 MB per event, equating to 2.4 Petabytes per second (2,400,000,000,000,000 bytes per second).
• 2026–2042: The upgraded High-Luminosity LHC (HL-LHC) at CERN is projected to generate 8 billion events per second. With up to 8 MB per event, this totals 64 Petabytes per second = 64,000,000,000,000,000 bytes per second —or a staggering 5.5 Zettabytes per day (5,529,600,000,000,000,000,000 bytes/day).
  
  

To put this in perspective: saving all that raw data would fill every hard drive on Earth within a single day.

Because of this, CERN must use a Level-1 Trigger system—a real-time data processing unit—to analyze the incoming data stream and immediately filter out more than 99% of the events, retaining only those likely to contain meaningful physical phenomena (i.e., combinations of photons, electrons, muons, etc.).

However, once data is discarded, it is lost forever. If the filtering system is inefficient, years of analysis may be wasted on ‘garbage’ data, while rare but valuable events remain undetected.

1.2 The Stumbling Block in Significantly Reducing Cancer Deaths and Healthcare Costs

In cancer diagnostics, early detection is key to survival and cost savings. The difference is dramatic:

• Tumors detected early offer a 50% to 98% chance of survival
• Tumors detected late offer only a 2.5% to 27% chance of survival
  
  

Among imaging devices, Positron Emission Tomography (PET) stands out. Unlike CT, MRI, or mammography—which detect anatomical anomalies only once millions of cancer cells are present—PET detects biological anomalies associated with tumor growth. It captures signals from 511 keV photons emitted when tumor-marking nutrients are absorbed by cells.

Since cancer cells consume 5 to 70 times more nutrients than healthy ones, a PET device capable of efficiently capturing all valid radiation signals at minimal cost and radiation dose is the most effective tool for early diagnosis.

2. Why Solving Radiation Signal Filtering Benefits Many Fields, including saving millions of lives

Solving this challenge—accurately detecting all valid radiation signals at the lowest cost per signal—has sweeping benefits.

This document addresses the high-throughput signal filtering from radiation domains in multi-billion-euro particle physics experiments and life-saving medical imaging—because they both depend on the same technological foundation: the ability to extract value from massive radiation-based datasets in real time.

A data acquisition system that helps physicists discover new particles more efficiently can also enable earlier, cheaper cancer detection, saving millions of lives. This is exactly what the 3D-Flow architecture was designed to do.

3. Why Has the Inventor Not Been Funded After 32 Years?

The 3D-Flow system, invented by the Italian-American scientist Dario Crosetto and formally recognized as a scientific breakthrough by an international public review at Fermilab in 1993 [10], solves both of the challenges described above.

And yet, after 32 years, despite its potential to save billions of euros and millions of lives, the inventor has never been funded for experimental implementation.

Why?

The 3D-Flow architecture, when applied to medical imaging in the 3D-CBS (Complete Body Screening) device, has the potential to reduce premature cancer deaths by 50% or more. This is a societal failure that cannot be explained by science alone. [4].

The quick answer below, and the more detailed discussion in Section 6.5, address only the scientific aspect of why the inventor of the 3D-CBS has not been funded. Broader issues in healthcare planning, policy, and resource allocation require a much more extensive analysis.

From a scientific standpoint, the lack of funding can be partly explained by the fact that the $2 trillion annual global R&D budget is largely allocated to the ‘best connected,’ as stated by Scientific American in its October 2018 article [11]. Sections 6.7 and 10.1.2. provide further details on this point.

4. Can a Politician, Administrator, Lawyer, Layperson, or Taxpayer Understand This Inconsistency?

Yes. The inconsistency is so clear that any informed citizen—regardless of technical background—can evaluate it with common sense in the two fields of High Energy Physics and Medical Imaging.

4.1 In High-Energy Physics:

The choice is between:

• A system capable of executing thousands of programmable operations (e.g., addition, subtraction, multiplication, data movement) on each dataset arriving every 25 nanoseconds, without losing data among the 8 billion events per second generated by the LHC
• A system limited to just 66 programmable operations per dataset
  
  

4.2 In Medical Imaging:

The choice is between:

• A medical imaging device capable of accurately detecting tumors made up of fewer than 100 cancer cells, over the entire body, in 2 minutes, with a radiation dose no greater than that received by an airline pilot in a month, and at a cost affordable to most people?
• A device that can only detect tumors after they contain over 1,000,000 cancer cells detectable by CT, MRI and mammograms, when survival chances are greatly reduced?
  
  

The answer is obvious. The inconsistency in funding priorities is not only indefensible—it’s dangerous.

5. What Is the Logical Step or Criterion to Ensure That Leaders and Politicians Fund the Most Cost-Effective Projects for Humanity?

The most logical step to make the scientific truth for the benefit of humanity emerge is simple:

Convene a public, transparent meeting—either in person or virtually—bringing together the leaders and policymakers responsible for allocating taxpayer funds, the designers of the systems currently receiving those funds, and the inventors of superior yet unfunded solutions that remain scientifically unchallenged:

Specifically, this meeting should include:

5.1. Funding Physics Experiments to Provide Powerful Tools for Experimental Physicists and Reduce Costs to Taxpayers

Current and past recipients of public funding for CERN’s FPGA-Based Level-1 Trigger systems, alongside independent inventors and engineers who have proposed technically superior alternatives—such as systems capable of executing significantly more programmable operations per dataset without data loss. The 3D-Flow architecture, recognized a breakthrough, has never been scientifically refuted (see two-page evidence summary [2]).

5.2. Funding Medical Imaging Devices to Significantly Reduce Premature Deaths and Healthcare Costs

Current and past leaders of publicly funded cancer research and diagnostic projects, along with scientists or inventors whose 3D-CBS [7] design and proposals offer greater reductions in cancer deaths and healthcare costs, backed by unrefuted calculations and a clear, testable implementation plan in a defined population once funding is provided [4].

In such a meeting, public funds should be directed to whoever can verifiably demonstrate the highest life-saving and cost-saving outcomes, especially when their claims remain unrefuted after decades of scrutiny.

6. Why This Matter Must Be Addressed Logically and Transparently—Respecting Scientific Integrity and Public Trust

Science is governed by logic, evidence, and transparency—not politics or personal interests. The following questions should be answered using clear reasoning, scientific methods, and adherence to codes of conduct and ethics in research.

6.1 How Was Real-Time Data Processing on Ultra-High-Speed Data Streams Handled Before the 3D-Flow Invention?

Before Crosetto’s invention, Level-1 Trigger systems were implemented using hardwired (cabled) logic based on fast transistors to execute as many operations as possible within the 25-nanosecond window between data arrivals.

Examples include:

• The 7-step [¹²] Level-1 Trigger algorithm used in CERN-ATLAS
• The sliding window trigger system developed by CERN-CMS
  
  

Both were presented at conferences in or before 1992 and implemented with non-programmable ASIC (Application-Specific Integrated Circuit) logic.

By contrast, Crosetto presented his programmable 3D-Flow architecture at the same 1992 conferences, showing it could execute hundreds of programmable operations on each dataset arriving every 25-nanoseconds—introducing a new paradigm in trigger design. For documentation, see Slide 6 [¹³] of Crosetto’s presentation at the IEEE-NSS-MIC-RTSD Conference on 31 October 2024, which references the 1992 ATLAS and CMS articles as well as his own 3D-Flow publications.

6.2 Under What Circumstances Was the 3D-Flow Architecture Invented?

Crosetto’s journey began with formal recognition at CERN in 1990 as a leading expert in the use of Digital Signal Processors (DSPs) in high-energy physics, following 17 years of work on CERN experiments—primarily designing and building instrumentation for real-time data acquisition and triggers, as well as instrumentation for offline analysis of the acquired data. That year:

• He was invited to present at the ECFA Workshop on the LHC in Aachen, Germany.
• He was invited to lecture at the CERN School of Computing [14] where he compared the performance of various computer architectures (see Slide 4 of [13]).
  
  

In 1991, Crosetto was invited to the Superconducting Super Collider (SSC) in Texas to design the Level-1 Trigger for the GEM experiment (Gamma, Electron, Muon), a project with a budget of over $500 million.

Within a year, Crosetto had solved the real-time processing bottleneck by inventing the 3D-Flow system—not only for GEM, but solving the problem for all collider experiments, including competing ones. His architecture introduced:

• Programmability over hardwired logic
• Neighboring data exchange
• Elimination of detector boundary constraints
• Extended data-processing time beyond single input intervals
  
  

This shifted the challenge for physicists from designing custom cabled logic algorithms to designing programmable algorithms and optimizing detector geometry, which could be implemented or updated on the same reusable 3D-Flow hardware platform after the first data acquisition.

With this invention, the challenge for physicists from different experiments to find new particles was no longer the design of a different cabled logic circuit to implement their specific Level-1 Trigger algorithm. Instead, the circuit was the same, and their talent and challenge shifted to the design of the detector and the programmable algorithm they could execute and change on the same 3D-Flow platform after acquiring and analyzing initial data.

6.3 [TECHNICAL] What features does the 3D-Flow Architecture Provide to Solve the Stumbling Problem Never Resolved Before?

Crosetto’s innovative 3D-Flow architecture overcomes the speed limitations in acquiring and processing data arriving at ultra-high speed with complex, programmable pattern-recognition algorithms with fast neighboring data exchange in real time.

The 3D-Flow invention goes beyond just its processor and system architecture—it includes a practical implementation that offers a revolutionary, transformative solution to a problem that no one has solved before: the real-time execution of complex, programmable pattern recognition algorithms with neighboring data exchange (3×3, 4×4, 5×5, n×n) for durations longer than the interval between two consecutive input data sets, arriving at ultra-high speed without any data loss. Its capabilities include:

• Executing over 8,000 programmable operations on each dataset arriving every 25 nanoseconds with no data loss.
• Supporting complex pattern recognition algorithms across neighboring detector elements seamlessly, with no boundary limitations.
• Modular, scalable hardware design, adaptable to any number of channels, boards, or crates.
• Implementation features that enable ultra-high-speed, low-cost data processing, including:
  
  
  • Unique bypass switch and bypass register
  • Efficient electronics-to-detector coupling
  • Optimized Integrated Circuit (IC) pin assignments
  • Strategic IC placement on printed circuit boards (PCBs)
  • Effective board interconnection strategies
    
    

This architecture was designed not only for physics applications, but also offers significant advantages in other fields such as quality control in manufacturing, face and object recognition, and more.

6.4. How Crosetto’s invention was recognized within a public, transparent, open scientific procedure, and who officially signed this recognition

Crosetto’s innovative 3D-Flow architecture was first validated following his presentations at three international conferences [12] [15], [16] held within the span of a single month (see Slide 6 of [13]). Discussions with experts in the field further confirmed the value of his invention, with several specialists—including those from competing experiments—publicly endorsing [17] it in writing through formal letters (https://crosettofoundation.org/testimonials/).

The strong recognition and support for Crosetto’s invention led the Director of the Superconducting Super Collider (who was also the Director of Fermilab) to allocate funding for a major public scientific review, held on 14 December 1993, at Fermilab.

The review consisted of a 90-minute presentation by Crosetto in the Fermilab auditorium, followed by an in-depth, full-day Q&A session with a panel of experts. At the conclusion, the reviewers took formal responsibility by signing an official report [10] acknowledging the disruptive, transformative advantages of Crosetto’s invention.

The report recognized that the 3D-Flow architecture overcame the speed limitations in acquiring and processing data arriving at ultra-high speed with complex, programmable algorithms in real time.

This breakthrough enabled Level-1 Trigger systems to execute algorithms previously reserved for Level-2, where more than 99% of the data had already been discarded.

The review panel included:

• Roger Bartley, ASIC Designs Inc.
• Dan Edmunds, Michigan State University, expert on Level-1 Triggers for the D-Zero experiment at Fermilab
• Don Machen, Scientific Systems International
• Livio Mapelli, leader of the UA2 experiment at CERN, representing CERN
• Vivian O'Dell, Fermi National Accelerator Laboratory
• Greg Sullivan, University of Chicago
• Silvio Turrini, Digital Equipment Corporation (DEC), Palo Alto Research Center, inventor of the first 400 MHz processor (see two validating letters from Turrini [18], in addition to his joint endorsement in the official report)
  
  

The review was chaired by Robert Downing from the University of Illinois, who formally signed the report recognizing the 3D-Flow breakthrough.

6.4.1. [TECHNICAL] What the 1993 Fermilab Review Said About the innovative 3D-Flow Architecture

The first sentence of the Fermilab review report [10] reads:

‘The committee finds this project an interesting and unique concept for constructing programmable Level-1 Trigger systems.’

This is a formal recognition of the 3D-Flow invention.

Additional committee statements include:

• ‘We do not believe that there are any major flaws in the proposed system.’ → Validation of feasibility
• ‘The committee was impressed with the work already completed by an essentially one-person operation.’ → Recognition of Dario Crosetto as the inventor
• ‘The added flexibility provided by the programmability of this system... given this feature experimenters would probably think of clever uses not now possible. Better Level one triggering will reduce the data rate into Level two. If a large enough reduction could be achieved, Level two triggers could be replaced by a processor farm.’
  
  

This final statement confirms that Crosetto’s system could execute Level-2 algorithms at Level-1, removing the need for Level-2 altogether—something CERN's FPGA system has never demonstrated.

6.4.2. The 3D-Flow Led to the 3D-CBS Invention for Early Cancer Detection, Also Validated in Numerous Public Scientific Reviews

In the years that followed, additional public scientific reviews and endorsement letters from leading experts [17] supported Crosetto’s 3D-Flow and 3D-CBS inventions, often accompanied by calls to fund the inventor.

Among these endorsements are three letters from Jerry Merryman, inventor of the pocket calculator, confirming Crosetto’s calculations and claims and urging funding for the 3D-CBS invention for early cancer detection. Two of these letters are handwritten dated 2002, 2005, and 2008 [19].

6.4.3. $1 Million Awarded to Crosetto for a feasibility Study of his invention, Successfully Completed and Approved for Peer-Reviewed Publication

After successfully passing the 1993 Fermilab review, Crosetto was awarded $150,000 to document his invention during the closure of the SSC. He later received a $1 million grant [22] from the U.S. Department of Energy (DOE) to conduct a feasibility study, which he completed successfully. The results were published in 1999 in a 45-page peer-reviewed article in Nuclear Instruments and Methods in Physics Research [20].

6.4.4. [TECHNICAL] Proof that a 3D-Flow implementation in 120 nm CMOS could execute 400 programmable operations on each dataset arriving every 25 ns, meeting all LHC experiment requirements until 2026

That article detailed the design of boards and crates for a universal, flexible 3D-Flow system—with analog or digital inputs—capable of meeting the requirements of all Level-1 Triggers in high-energy physics experiments, as well as applications in Positron Emission Tomography. The system was fully simulated from the system level down to the gate and transistor level.

Had it been funded and implemented using 120 nm CMOS technology, it could have executed over 400 programmable operations per event, efficiently filtering 1.2 billion events per second, as required by LHC experiments through 2026.

A single 3D-Flow implementation could have supported all experiments, eliminating the need for the repeated and costly redesigns of multiple failed FPGA-based Trigger systems.

6.5. [TECHNICAL] Explanation of the Invention for Scientists in the Field: Verifiable Advantages with No Substantiated Scientific Refutation to Date

The 3D-Flow architecture invented by Dario Crosetto stands unrefuted after 32 years. No individual or institution has provided a valid scientific counter-example or a superior system that could match its performance when subjected to side-by-side public comparison. The following milestones and validations demonstrate the invention’s unique and scalable capabilities:

• 1993: Crosetto’s 3D-Flow architecture invention was formally recognized as a breakthrough during a public scientific review at Fermilab on 14 December 1993. The system resolved fundamental challenges in real-time processing ultra highspeed data streams introducing:
  • Full programmability
  • Execution of complex algorithms involving neighboring data exchange
  • Execution of Pattern recognition algorithms for a time longer than the time interval between two consecutive input datasets,
  • Zero data loss
• Educational analogy: The two key technical features—the 3D-Flow bypass switch and the bypass register—are so intuitive that even high school students can understand them. At minute 4:28 in the video [21], the bypass switch is represented by a student at a classroom door, while the bypass register is represented by a box between classrooms.
• 1995: The U.S. Department of Energy (DOE) awarded Crosetto $1 million to conduct a feasibility study on his 3D-Flow invention.
• 1997: [Technical] The 3D-Flow architecture was validated via simulation using three major FPGA simulators: Altera, Xilinx, and ORCA.
• 1998: [Technical] Crosetto simulated the 3D-Flowcomplete system with thousands of processors, modeling it:
  • From the system level (C++)
  • Down to the gate level (VHDL)
  • And further to the transistor level matched to a specific CMOS technology
• 1998: [Technical] Synopsys engineers were commissioned to port 16× 3D-Flow processors per chip (IC) using 300 nm CMOS technology, creating a tape-out for fabrication.
  However, despite this progress, the DOE did not pay the silicon foundry to manufacture the IC.
  Instead, over $50 million was allocated to another scientist to implement FPGA-based Level-1 Trigger, without requiring full-system simulation as was done for 3D-Flow.
• 1999: [Technical] The DOE-funded feasibility study [22] was published in a 45-page peer-reviewed article [20].
  This publication describes a universal, scalable 3D-Flow system with analog or digital input boards.
  Built in 120 nm CMOS, the architecture could meet the Level-1 Trigger requirements for all LHC experiments through 2026, as well as Positron Emission Tomography (PET) applications.
  The entire system was fully simulated from system to transistor level.
• 2003: [Technical] Crosetto successfully demonstrated feasibility and functionality in hardware in a 3D-Flow system with 144 processors, which Crosetto presented at the IEEE -NSS-MIC-RTSD conference in Portland, Oregon [23].
• 2015: [Technical] Manufacturing quotes were obtained for 64× 3D-Flow processors per chip (IC) using 40 nm CMOS technology.
  A comprehensive 274-page proposal [24] outlined both a Level-1 Trigger system and a 3D-CBS medical imaging device, supported by 59 industrial quotes providing cost and build timelines for every component—from ICs and boards to system integration.
  Despite this, Crosetto was denied funding, while additional funding was awarded to CERN’s FPGA-based Level-1 Trigger systems—even though their predecessors had already failed to meet performance and efficiency goals.
  In parallel, a $15.5 million grant—along with several other previous grants—was awarded by National Institutes of Health to U.S. researchers who copied and plagiarized the 3D-CBS concept, even using in their abstract to obtain the $15.5 million grant, wording from Crosetto’s book cover page.
  Their project, named EXPLORER. However, because they did not know how to build it, these recipients of the $15.5 million grant gave the money to a Chinese enterprise, giving them the wrong instructions to build a device focusing on measuring spatial resolution using expensive thin 18.1 mm LYSO crystals to the detriment of sensitivity, which is the basic, uncontestable principle of operation of PET, which measures a variable within a time unit.
• 2025: [Technical] The 3D-Flow design is now scalable to 128 x 3D-Flow processors per chip (IC) using 20 nm CMOS technology, reducing cost to $0.50 per processor.
  Key documentation includes:
  • Pages 34–44 of [25]: Detailed architecture, features, specifications, examples of algorithms execution (up to 26 programmable operations per cycle, average 13 per cycle)
  • Pages 74–76 of [25]: Cost and performance summaries for an ATCA crate with 68,352 processors. Estimated cost: $86,000 per crate, configurable for various use cases:
    • 1,024 channels / 9,672 programmable operations per input dataset
    • 2,048 channels / 4,836 programmable operations
    • 4,096 channels / 2,418 programmable operations

 

Additional documentation includes:

• A 2-page technical comparison between 3D-Flow and CERN’s FPGA-based systems [2].
• A separate 2-page technical brief on single-board [3] 3D-Flow Level-1 Triggers, offering various form factors for use in both physics experiments (to 2042) and PET imaging, adaptable to any detector crystal at superior performance and significantly lower cost
  
  

6.6. Explanation of the 3D-Flow Invention for Students, Journalists, and Non-Experts: A Verifiable Analogy Anyone Can Understand

The 3D-Flow concept is not only accessible to scientists—it can be understood by middle school students, journalists, administrators, politicians, lawyers, and any logical thinker. The basic principle can be explained using common analogies.

6.6.1. The Montessori Middle School Analogy (2000)

In 2000, middle school Montessori students helped illustrate the core idea of the 3D-Flow architecture using a bottling water analogy. Working alongside Crosetto and their teachers, they co-authored the educational book:

Understanding a New Idea for a Cancer Screening Device (ISBN 0-9702897-1-5)

This book explained how the 3D-Flow system efficiently detects tumor markers through real-time data processing, enabling cost-effective early cancer detection by capturing more meaningful signals with fewer losses [26].

6.6.2. The High School Envelope Analogy (2009)

In 2009, high school students in San Antonio, Texas, worked with Crosetto on a simplified but powerful analogy:

• Suppose you must process each envelope in a stream of incoming envelopes.
• Each envelope requires 30 seconds of analysis.
• But envelopes arrive every 6 seconds.
  
  

How can you process every envelope thoroughly for 30 seconds, without falling behind or skipping any?

After learning about the 3D-Flow architecture, which enables to extend the processing longer than the time interval between two consecutive input datasets with no data loss, students quickly understood that it solves the problem even as the complexity of the analysis or the rate of arrival increases, and they did not have to run from one end of the corridor to each class to deliver the envelop as it is performed in a classical parallel-processing system architecture.

Not one student advocated discarding envelopes (data) just to run a longer algorithm.

These students later helped create a video explaining the analogy, including a visual representation of the bypass switch and bypass register at minute 4:28 (See video) [21].

6.6.3. Expert-Level Validation but Institutional Suppression

Despite the clarity of the concept and its appeal to young minds, Crosetto's invention faced rejection at the institutional level—not because of scientific flaws, but because of non-scientific suppression.

Crosetto’s inventions have undergone rigorous validation, including the landmark public scientific review of the 3D-Flow breakthrough at Fermilab in 1993 [10], subsequent independent reviews of the 3D-CBS, publication in peer-reviewed literature (NIM-Sec. A, vol. 436, 1999, pp.341-385 [20]), endorsements in letters from leading experts [17], detailed simulations, and successful implementation in a 144 processors 3D-Flow hardware system [23].

In 2000, Crosetto distributed 200 free copies of his technical book:

400+ Times PET Efficiency Improvement for Lower-Dose Radiation, Lower-Cost Cancer Screening [26].

He presented rigorous technical calculations, validated architectural diagrams, and performance comparisons at major scientific conferences.

Although none of his designs or data were scientifically refuted, the community:

• Suppressed his conference presentations
• Ignored his published work (despite widespread circulation)
• Copied and plagiarized many of his ideas without acknowledgment (see the 2015 entry in Sec. 6.5).
  
  

The terms ‘suppression,’ ‘copying,’ and ‘plagiarism’ are used here not lightly, but with full evidentiary backing.

(See Section 14 of this document for additional backing to the use of these words).

6.7 Why Has No One Refuted the 1993 Fermilab Review Panel or the 45-Page Peer-Reviewed Article—Yet Billions Were Spent on Inferior FPGA-Based Level-1 Trigger Systems?

The answer lies in a combination of lack of transparency, suppressed dialogue, a rigged peer-review system, and a critical institutional error: choosing to pursue FPGAs for Level-1 Triggers without first verifying—at the conceptual and simulation level—whether the architecture could handle the job efficiently.

Despite the U.S. Department of Energy (DOE) funding Crosetto’s $1 million feasibility study, and despite its approval and publication in a peer-reviewed journal [20], the DOE:

• Refused multiple requests by the inventor to hold a technical discussion
• Denied funding for fabrication of the validated 3D-Flow IC
• Instead gave over $50 million to a single scientist to develop FPGA-based Level-1 Triggers, without any requirement to simulate the full system
  
  

This triggered a cascade of funding from other public agencies, often through anonymous peer review processes, which:

• Continued funding for FPGA-based approaches even after prior failures
• Suppressed Crosetto’s publications, presentations, and funding opportunities
• Never required the rigorous simulations or comparisons that Crosetto had already provided
  
  

The reason billions were ultimately wasted due to the inefficiencies of FPGA-based Level-1 Trigger systems, which are inadequate for the job, lies in the refusal to allow open scientific dialogue, coupled with the suppression of Crosetto’s presentations, articles, and funding—shielded by anonymous review processes lacking accountability, political influence, and institutional inertia.

6.8 [TECHNICAL] How CERN Scientists Were Captivated by the Word ‘Programmable’ in FPGA (Field Programmable Gate Array)

For over three decades, many CERN scientists were captivated by the appealing term ‘programmable’ in Field Programmable Gate Arrays (FPGAs).

This led to a widespread promotion of ‘programmability hype’ in conferences and publications—often without conducting rigorous evaluations of performance, power consumption, or cost for Level-1 Trigger systems and other applications requiring the execution of complex real-time pattern recognition algorithms on ultra-high-speed data streams.

Yet ‘programmable’ does not mean ‘suitable’ for real-time, high-performance applications. A desktop or laptop computer is programmable—but it cannot process in real-time 8 billion events per second from a particle detector. The same holds for GPUs, ARMs, Hypercubes, and FPGAs when used inappropriately.

FPGA architectures—such as the Xilinx devices used in CERN’s Level-1 Triggers—are organized into Basic Logic Elements (BELs) (see Figures 37–40, pp. 48–49, [25]).

Only about 13% of the transistors are available for logic; the remainder are used for routing and interconnect, which are essential for prototyping and verifying new circuit designs—such as a CPU—before committing to fabrication.

However, the enormous number of routing and interconnect transistors introduces delays, making FPGAs inefficient and costly for dedicated tasks, and unable to execute complex algorithms in real time at the ultra-high input data rates required by CERN Level-1 Trigger experiments without data loss.

This limitation is conceptually evident and does not require billions of dollars or 30 years to confirm. For example, Table VI (Section X.C.6, p. 48 of [25]) compares performance, power, and cost between an Intel i7-8550U CPU and a Xilinx FPGA Virtex Ultrascale VU19P:

Table VI Example: Comparing FPGA vs. CPU Performance

Metric	Intel i7-8550U	Xilinx FPGA VU19P
Transistors	3.5 billion	35 billion
Technology	14 nm FinFET	7 nm FinFET
Frequency	3.9 GHz	300 MHz
Power	15–35 W	300 W
Cost	~$100	~$10,000

Despite having 10× more transistors, the FPGA:

• Consumes 10× more power
• Costs 100× more
• Delivers 10–100× slower performance per core (depending on application)
  
  

No computer manufacturer (HP, Dell, Lenovo, Acer, Asus, Toshiba) installs an FPGA in place of a CPU for general-purpose computing. The same logic applies even more strongly in cost- and energy-sensitive physics experiments.

Appropriate Use of FPGAs

FPGAs are excellent tools for:

• Ancillary logic
• Testing CPU/GPU/3D-Flow functions
• Prototyping, as Crosetto did for the 3D-Flow (20 MHz FPGA-based prototype at $500 per processor, while the 3D-Flow implementation in 20 nm CMOS runs at 620 MHz and costs $0.50 per processor at a much lower power consumption).
  
  

But FPGAs are not the best choice for:

• High performance
• Low cost
• Low power
• Real-time computation under extreme data throughput (such as the LHC’s 40 MHz rate).

6.9 How CERN Scientists Were Captivated by the Market Hype Around Xilinx FPGAs and Transistor Count

CERN’s decision-makers were captivated not by verified performance, but by marketing-driven metrics such as increasing transistor counts per FPGAs chip and new process technologies:

• 2010: Xilinx FPGA 28 nm CMOS
• 2013: Xilinx FPGA 16 nm FinFET
• 2019: Xilinx FPGA 7 nm FinFET
  
  

Instead of questioning whether the FPGA architecture itself was suitable for real-time Level-1 Trigger applications, they focused on raw chip size and speed—a misleading distraction.

6.9.1. The 3D-Flow Architecture Was Deliberately Excluded and Crosetto Systematically Silenced

Meanwhile, Crosetto’s 3D-Flow architecture was deliberately excluded from critical scientific forums. He was:

• Denied access to major workshops and conferences
• Denied the opportunity to present comparative data
• Ignored or blocked by influential CERN scientists involved in managing billions in public funds
• Actively suppressed, even as others copied and plagiarized key elements of his designs
  
  

Rather than engage in a healthy scientific debate, the community allowed these inconsistencies to fester, leading to the construction of systems with:

• 20 trillion transistors
• Over 650 kW of power consumption
• Yet still unable to meet basic requirements for Level-1 Trigger real-time pattern recognition.
  
  

6.9.2. Denied the Right to Challenge

Crosetto was denied even the basic scientific right to ask questions and demand justifications from CERN designers—such as:

• Why was the Level-2 Trigger eliminated, without first proving that the Level-1 system using FPGAs could handle full-scale data filtering by executing Level-2 Trigger algorithms with zero data loss?
• How did they justify continuing with sliding window techniques, 3×3 cluster ASICs, and later FPGAs, without providing simulation benchmarks for the number of programmable operations that their FPGA-Based Level-1 Trigger could execute on each dataset arriving every 25 nanoseconds?
  
  

6.9.3. Misleading Language and Marketing Hype on CERN's Website

CERN’s official communications [27] continue to promote the FPGA-based Level-1 Trigger upgrades with vague, qualitative claims, such as:

‘Relying on state-of-the-art FPGAs (with 8 times more resources than today)’

This does not inform experimental physicists how many programmable operations per dataset can actually be executed in real time at 40 MHz.

CERN website further states:

‘High-speed optical links reaching up to 28 Gb/s (compared to 10 Gb/s in Phase-1). Directly inspired by the current system, The data processing is carried out by more than 250 generic-processing cards based on Advanced Telecommunications Computing Architecture (ATCA) technology.’

These are technical-sounding advertisement but meaningless specifications that provide no numerical data in the context of the Level-1 Trigger’s core objective: executing complex filtering algorithms in real time on datasets arriving every 25 nanoseconds.

And finally:

‘…this system will offer extraordinary ways to select interesting physics and expect the unknown.’

This is hype and promotional language, not science. The only ‘extraordinary’ metric that matters is how many programmable operations can be executed per dataset to accurately resolve pile-ups and perform accurate pattern recognition on 8 billion events per seconds without data loss.

6.9.4. The Dangerous Oversight of Transistor Count Without Architectural Validation

Slides presented by CERN scientists (see Figures 34 and 35 of [25]) continue to emphasize the rapid growth in transistor count in modern FPGA chips, reinforcing a technology hype rather than addressing core architectural limitations.

In Figure 35, a red vertical bar illustrates a fivefold increase in logic cells—but still fails to answer the most critical question for experimental physicists:

Exactly how many more programmable operations can now be executed per dataset?

Statements like ‘FPGAs are growing and can embed complex algorithms’ remain vague and offer no actionable information for those tasked with real-time event selection at the LHC.

6.9.5. Where Is the Evidence-Based Review?

The CERN website further [27] states that:

‘The Phase-2 Upgrade Level-1 Trigger project is described in a Technical Design Report. The project was reviewed and approved recently by the LHC Committee (LHCC) and has now entered its construction phase.’

This raises urgent questions:

• Who are the members of the LHCC?
• Did they request a full simulation of Level-2 Trigger algorithms implemented on the new FPGA-Based Level-1 Trigger system before eliminating Level-2 entirely?
• Were they informed of Crosetto’s 3D-Flow architecture, which was formally recognized in 1993 as a breakthrough, offering true programmability with the ability to execute complex, long algorithms at Level-1 Trigger, including Level-2 Trigger algorithms without data loss?
  
  

Why was Crosetto not invited to present and compare his invention alongside the FPGA-based Level-1 Trigger proposal?

Why was there no open scientific discussion between proponents of both approaches to present their data and cost analyses to funding agencies, enabling them to make an evidence-based and cost-effective decision?

Conclusion: CERN’s FPGA obsession has been driven by marketing metrics, not scientific rigor. In contrast, Crosetto’s 3D-Flow system provides a clear, measurable, and scalable solution that should have been tested publicly, side-by-side, long ago.

7. [TECHNICAL] CERN FPGA-Based Level-1 Trigger vs. 3D-Flow Architecture: Technical, Economic, and Scientific Comparison

7.1. Inadequacy of FPGAs for Level-1 Trigger Systems

A Level-1 Trigger is a crucial component in high-energy physics experiments at CERN's Large Hadron Collider (LHC).

Its primary function is to provide the necessary input bandwidth and computational power to execute the Level-1 Trigger algorithm, as defined in the Technical Design Reports (TDRs) for CERN's CMS, ATLAS, and other experiments, and summarized in slide 3 of [13] on each dataset [16].

This process must handle data arriving from thousands of electronic channels every 25 nanoseconds without data loss.

The number of electronic channels originating from detector units known as Trigger Towers:

• CERN-CMS: approximately 3,888 Trigger Towers, plus additional towers from the forward calorimeter.
• CERN-ATLAS: approximately 7,200 Trigger Towers.
  
  

To be more efficient in filtering the valuable data from radiation the algorithm would need to increase in complexity and the number of input variables must increase.

This is a capability the 3D-Flow architecture offers, with the potential to execute over 8,000 programmable operations per dataset in parallel on each electronic channel.

In stark contrast, the current CERN FPGA-Based Level-1 Trigger can only offer approximately 66 programmable operations.

7.2. The Flawed choice of FPGA for Level-1 Trigger Systems

CERN scientists have overlooked a fundamental flaw in FPGA architecture for this specific application. A large percentage of an FPGA's transistors are dedicated to routing and interconnects.

This overhead introduces inherent delays in signal propagation, severely limiting the execution of filtering algorithms on ultra-high-speed input data streams.

The Reality: Approximately 66 Operations per Dataset

Detailed calculations based on CERN Phase-2 Upgrade of the [16] show that the current FPGA-based Level-1 Trigger system for 2026–2036 is limited to approximately 66 programmable operations per dataset.

This number can be challenged and verified through transparent, replicable scientific methods—a challenge that no FPGA proponent has publicly answered to date.

The FPGA architectural inefficiency for Level-1 Trigger application is the core reason for the system's limitation to approximately 66 operations per dataset arriving every 25 nanoseconds.

Despite these limitations—and the existence of the 3D-Flow architecture, which was recognized as a superior solution since 1993—CERN took an incorrect path by adopting FPGAs, a technology that has demonstrably inadequate for Level-1 Trigger applications for over three decades.

7.3. Methodology to Quantify Operational Limits

To demonstrate the disparity in computational power, a clear and transparent methodology is required to quantify the number of programmable operations each architecture can perform on a single dataset arriving every 25 nanoseconds.

7.3.1. Mapping Computational Resources to Each Detector Channel

In this conceptual analysis, the computational unit executing the Level-1 Trigger algorithm is referred to as a Processing Element (PE).

• FPGA implementation: A PE consists of a sufficient number of Xilinx Basic Logic Elements (BELs) (see Figures 37–40, pp. 48–49, [25]) capable of executing the most complex Level-1 Trigger algorithm among the ~500 designed by CMS physicists.
• 3D-Flow implementation: A PE is a 3D-Flow processor.
  
  

Examples:

• CERN FPGA-Based: Mapping of FPGA resources to electronic channels for the CMS Level-1 Trigger (comprising several PEs) is shown in Figure 2.7, p. 38 of the CMS-TDR [28].
• 3D-Flow architecture: Mapping of 3D-Flow resources to electronic channels is shown in Table XII, p. 76 ([27]), with board-level designs in Figures 57–58 and the system design in Figure 59.
  
  

A 3D-Flow board (Figures 57–58, [25]) can be configured as:

• 512 channels: 2,148 operations; 12 PEs × 100,000 logic gates each = 1.2 M gates per Trigger channel.
• 128 channels: 9,672 operations = 4.8 M gates per channel.
  
  

7.3.2. Determine Parallel Operations per Clock Cycle within a PE

Identify the maximum and average number of independent logical operations (e.g., add, subtract, multiply, compare, move) that each PE can execute simultaneously in a single clock cycle.

• CERN FPGA-Based: Exact values can be obtained using a Xilinx simulator; providing these results is the responsibility of the CERN FPGA-Based Level-1 Trigger designers.
• 3D-Flow Architecture: Simulations and hardware tests show each 3D-Flow PE can execute up to 26 operations per clock cycle, with a typical average of 13 when running Level-1 Trigger algorithms (see Figures 25–26, pp. 40–41, [25]).
  
  

7.3.3. Calculate Operations Executed by Each PE per Bunch Crossing

This step links the hardware’s processing speed to the LHC’s data rate. Multiply the average number of operations per clock cycle by the ratio of the PE’s clock frequency to the LHC bunch crossing frequency (40 MHz).

• CERN FPGA-Based: The clock frequency of FPGAs used in the CMS Level-1 Trigger typically ranges from 240 MHz to 480 MHz, as indicated in the CMS-TDR [28], with limits imposed by power dissipation when using air cooling. (See video of a water-cooled board with a single Xilinx Virtex Ultrascale VU13P FPGA running at 300 MHz, drawing 300 A and consuming 300 W [29]). The specific number of operations per bunch crossing must be determined by the CERN FPGA-Based Level-1 Trigger designers through simulation or experimental measurement.
• 3D-Flow Architecture: A 3D-Flow PE, fabricated in 20 nm CMOS technology, can operate at 620 MHz. With an average of 13 operations per clock cycle, this provides 201.5 programmable operations per PE per bunch crossing (13 operations × 620 MHz / 40 MHz = 201.5).
  
  

7.3.4. Account for Algorithm Complexity and PE Replication

For algorithms requiring more operations than a single PE can provide, multiple PEs can be replicated in parallel for a single channel.

• CERN FPGA-Based: The estimated 66 programmable operations per dataset for the current system is a hardware-limited figure that already includes some degree of PE replication.
• 3D-Flow Architecture: The 3D-Flow system can be configured with a specific number of replicated PEs per channel, determined by the computational power required to execute any complex Level-1 Trigger programmable algorithm envisioned by experimental physicists or by AI analysis. Crosetto designed a universal board with 8,448 3D-Flow PEs, within board and crate power dissipation limits, detailed in Figures 58–59, p. 74 ([25]) and described in a two-page article ([3]). Configurations include:
  • 512 channels / 2,418 operations (201.5 operations per PE × 12 PEs = 2,418 operations/ channel)
  • 256 channels / 4,836 operations (201.5 operations per PE × 24 PEs = 4,836 operations/channel)
  • 128 channels / 9,672 operations (201.5 operations per PE × 48 PEs = 9,672 operations/channel)
    
    

This demonstrates how the 3D-Flow architecture scales with PE replication, providing a significant advantage for implementing complex algorithms.

7.3.5. Calculate Aggregate Capability per Dataset Arriving Every 25 Nanoseconds

This step determines the total number of programmable operations that the system can perform on each dataset arriving at the LHC’s 40 MHz bunch crossing rate.

• CERN FPGA-Based: With an estimated 66 programmable operations per dataset (including some PE replication), the total capability depends on the number of electronic channels and PEs implemented in the CMS Level-1 Trigger. Exact figures must be provided by the designers through detailed simulation or hardware measurement.
• 3D-Flow Architecture: Using 201.5 operations per PE per dataset and scaling by PE replication per channel, the 3D-Flow system can be configured with the capability to execute:
  • 512 channels: 2,418 operations on each dataset arriving every 25 ns
  • 256 channels: 4,836 operations on each dataset arriving every 25 ns
  • 128 channels: 9,672 operations on each dataset arriving every 25 ns
    
    

This represents the sustained processing capability per dataset, and shows how 3D-Flow can be scaled to handle more complex algorithms without loss of data.

7.3.6. System-Level Comparison: Transistors and Power

A simple comparison of raw transistor count and power consumption can be misleading. The key is to evaluate these metrics relative to the achieved computational capability.

• FPGA-Based: For approximately 66 programmable operations on each dataset arriving every 25 nanoseconds, the CMS Phase-2 Upgrade Level-1 Trigger uses about 20 trillion transistors, implemented in 1,648 FPGAs across 130 ATCA crates, consuming 650 kW.
  • Transistors: The 20 trillion total is derived by summing the transistor counts of all FPGAs. This figure is supported by the number of FPGAs reported by CMS-TDR in Table 3.2, p. 46 of the CERN-CMS TDR [30], and the approximate per-device transistor counts provided by Xilinx (Table X, p. 71 of [25]). The high total results from the immense routing overhead in FPGA architectures.
  • Power: Estimated at 5 kW per ATCA crate, totaling 650 kW for all 130 crates (Table 3.2, p. 46 of the CERN-CMS TDR [30]).
• 3D-Flow: A 3D-Flow system capable of 2,418 to 9,672 programmable operations on each dataset arriving every 25 ns would use 27.3 billion to 109.3 billion transistors, implemented in 68,352 to 273,408 3D-Flow PEs, and consume 4 kW to 12 kW respectively—while being designed to handle more channels than CMS and delivering far higher computational capability.
  • Transistors: A configuration with 12 PEs per channel (2,418 operations) for all 4,096 channels—exceeding the 3,888 CMS channels—would require ~27.3 billion transistors (calculated as 100,000 logic gates per PE × 4 transistors per gate × 68,352 PEs = 27,340,800,000). A configuration with 48 PEs per channel (9,672 operations) would require ~109.3 billion transistors. Even the higher figure is only a fraction of the FPGA system’s 20 trillion transistors, while delivering significantly greater operational capability.
  • Power: For 4,096 channels, power is ~3 kW (66 3D-Flow ICs per board × 4 W each = 264 W, plus 66 W ancillary logic, total 330 W per board × 8 boards = 2,640 W, plus 260 W CPU and 100 W pyramid channel-reduction board). Achieving 9,672 operations would require four crates, totaling 12 kW—orders of magnitude lower than the FPGA-based system.
    
    

7.3.7. The Hidden Cost of CERN’s FPGA-Based Level-1 Trigger System

The financial and human cost of CERN’s FPGA-based Level-1 Trigger system is enormous:

• Boards and crates costing millions of dollars.
• Thousands of hours of labor from hundreds of scientists, engineers, and technicians.
• Annual electricity consumption measured in Terawatt-hour.
• A system that still only executes approximately 66 operations per dataset—despite the existence of a verified, unrefuted alternative, 3D-Flow, capable of over 8,000 operations per dataset, using dramatically fewer transistors, lower power, and validated hardware.
  
  

CERN pursued the FPGA-Based Level-1 Trigger path despite 3D-Flow’s official recognition, validated simulations, hardware demonstrations, peer-reviewed publications, and complete absence of scientific refutation.

The inefficiency of CERN’s FPGA-Based Level-1 Trigger has not only wasted billions [31] in research funds but also squandered electricity on a massive scale—directly contributing to unnecessary CO₂ emissions.

Since the LHC began operating in 2010, its annual electricity consumption has ranged from roughly 0.5 to 1.3 terawatt-hours (enough to power 115,000–300,000 homes, average home in Europe consumes 3,500 kWh/year), meaning that even a conservative estimate of 50% efficiency gains in filtering the same number of valuable events—by adopting the 3D-Flow system—could have saved billions of kilowatt-hours each year, significantly reducing both costs and carbon footprint.

With the HL-LHC expected to consume about 1.6 terawatt-hours annually once fully operational (enough to power over 370,000 homes), achieving at least a 50% efficiency gain through 3D-Flow—capable of over 8,000 operations per Level-1 Trigger dataset compared to just 66 operations for CERN’s FPGA-Based system—could save enough electricity every year to power more than 185,000 homes, cutting costs and CO₂ emissions in one stroke.

Crosetto’s inventions have undergone rigorous validation, including the landmark 1993 public scientific review of the 3D-Flow breakthrough at Fermilab [10], subsequent independent reviews of the 3D-CBS (3D-Complete Body Screening), publication in peer-reviewed literature (NIM-Sec. A, vol. 436, 1999, pp.341-385 [20]), endorsements in letters from leading experts [17], detailed simulations, and successful implementation in a 144 processors 3D-Flow hardware system [23].

For future HL-LHC applications, detailed information is provided in the 274-page document [24] supported by 59 quotes from industry.

The 3D-Flow system—featuring a processor updated to a 20-nanometer CMOS technology implementation—is further described in an 82-page article [25] and in two concise 2-page summary articles [2], [3]. All of these publications remain scientifically unrefuted.

8. Estimated €4 Billion in Wasted Public Funds on CERN FPGA-Based Level-1 Triggers

The estimate of over €4 billion in taxpayer money wasted on inefficient CERN FPGA-based Level-1 Trigger systems over the past 30 years is conservative and supported by the following calculations:

• 1999: The Initial Wrong Turn

CERN selected FPGA-based Level-1 Triggers over the more efficient 3D-Flow architecture, despite the latter’s formal recognition as a breakthrough. Each system for large experiments cost roughly $100 million, leading to an estimated $400 million waste. Even CERN-CMS scientists later admitted that their Level-1 Trigger system had to be discarded in 2016 because it was ineffective [32].

• 2016: Mistakes Repeated

Despite mounting technical evidence, CERN pursued new FPGA-based Level-1 Trigger systems, incurring another estimated $300 million in costs—again without properly evaluating performance through full-system simulations as had been done for the 3D-Flow system.

• 2025: Same Architecture, Same Mistakes

A third round of FPGA-based upgrades for the 2026 HL-LHC phase is underway, costing over $100 million per experiment. Across multiple trigger systems, this results in an additional $300 million in public funds.

• Scientific Workforce Costs

Over 14,000 scientists, engineers, postdocs, and technicians involved in LHC experiments at CERN are largely funded by public institutions. If conservatively 15% of these individuals (approximately 2,100 people) spent the past 32 years working on Level-1 Trigger developments—and on analyzing mainly ‘garbage’ data because the Level-1 Trigger was ineffective—then, at a conservative salary of $45,000 per year, this amounts to over $3 billion in salary expenditures, not including lost time and opportunity costs.

Total: Over $4 Billion Wasted

These financial losses and the time of thousands of scientists can be traced to one root issue: the suppression of transparency and the silencing of Crosetto's efforts to present and compare his 3D-Flow architecture in a public, scientific setting alongside FPGA-based alternatives.

Given the loss of thousands of research hours, over $4 billion in experiments at CERN, and millions of lives that could have been saved through cost-effective early detection of abnormal biophysiology at a curable stage using the 3D-CBS, combined with the 3D-Flow invention, the magnitude of the loss—financial, intellectual, and human—makes it imperative to end the suppression of logical, well-substantiated challenges.

Crosetto should be permitted to present his case and be funded to build at least two 3D-CBS devices to experimentally prove that his invention can cut premature cancer deaths and costs by half. (More supporting evidence in Section 7.3.7.)

9. The Doomed Failure of the Monster CERN FPGA-Based Level-1 Trigger for 2026-2036—and Why It Must Be Halted and Trashed

The nearly completed CERN FPGA-Based Level-1 Trigger, built for the 2026–2036 HL-LHC upgrade, boasts an astonishing 20 trillion 7 nm FinFET transistors and consumes over 650 kW of power. But its design is inadequate for the scale of the problem it was built to solve.

It cannot:

• Efficiently filter massive radiation noise
• Execute the thousands of programmable operations needed per dataset
• Meet the Level-1 requirements of HL-LHC, which will generate 8 billion events per second
  
  

Even if this system were upgraded to 200 trillion transistors on 5 nm or 3 nm nodes, consuming MW, it would still fail due to inherent architectural inefficiency.

This project must be halted immediately and trashed to avoid wasting an additional $12+ billion [31] in the next decade.

Funding CERN’s CMS and ATLAS upgrades—including all FPGA-based Level-1 Trigger systems requiring high performance real-time processing at LHC—should be frozen, and resumed only after:

An open, public, scientific meeting comparing these systems with Crosetto’s 3D-Flow architecture, which was formally recognized a breakthrough invention by the 1993 Fermilab review panel as solving the very problems CERN’s systems are still struggling with today.

The Consequences of Eliminating Level-2 Trigger Without a Valid Substitute

CERN’s decision to eliminate the Level-2 Trigger was made without:

• Demonstrating that Level-1 algorithms could handle the increased complexity
• Proving that thousands of programmable operations per dataset could be executed at 40 MHz
  
  

Would result in:

• Over 99% of the data is discarded, including many potentially valuable events
• Current Level-1 Trigger algorithms are limited to operating on only a narrow subset of data, making efficient filtering impossible
  
  

This was a critical mistake when the LHC was generating 1.2 billion events per second—and it is an even more serious flaw with the HL-LHC’s projected 8 billion events per second, which require real-time execution of thousands of operations per dataset to perform accurate pattern recognition and noise rejection.

What Should Have Been Done—And What Must Be Done Now

Before removing Level-2, the 14,000 scientists and engineers involved in LHC experiments should have simulated typical Level-2 algorithms on their FPGA-Based Level-1 Trigger systems and proven the entire system feasible.

They should have:

• Evaluated the ability to perform hundreds of operations per dataset (1999-2026)
• Evaluated the ability to perform thousands of operations per dataset (2026-2036)
• Used standard simulation tools (as Crosetto did) to model power, cost, and scalability
  
  

This was never done.

Now, before another €12+ billion is wasted, this must be done.

9.1. [TECHNICAL] Why CERN’s FPGA-Based Level-1 Trigger Systems Will Waste Over $12 Billion if Not Halted and Trashed Immediately

The approximately 66 operations per dataset currently achievable by CERN’s FPGA-Based Level-1 Triggers for the HL-LHC are grossly inadequate when compared to the thousands of operations required to replace Level-2 Trigger algorithms effectively.

As shown in Section 7.3, this limitation can be verified using manufacturer-provided FPGA simulators, which allow precise evaluation of how many operations a specific FPGA can execute on each dataset on each channel, arriving every 25-nanoseconds. Even if CERN’s current 20-trillion-transistor, 7 nm FinFET-based CMS Level-1 Trigger were upgraded tenfold—to 200 trillion transistors at 5 nm or 3 nm—it would still struggle to exceed 100 operations per dataset.

This is not just a theoretical shortcoming, it is supported by decades of evidence including wasted hardware, failure to capture key events, and massive inefficiencies in human and financial resources.

9.1.1. Experimental Evidence: The Higgs Boson Data Loss

When the Higgs boson-like particle was announced on 4 July 2012, CERN had generated over 1,000 trillion proton collisions (events) in two years, which statistically should have contained about 100,000 Higgs boson events.

Yet only 40 events were ultimately used to confirm the discovery—an efficiency of 0.04%. It is likely these 40 were captured by chance, not through the effectiveness of the Level-1 Trigger.

This confirms, by experimental result, the fundamental inadequacy of the Level-1 Trigger used at the time.

This same Level-1 Trigger system was officially decommissioned in 2016, as acknowledged by the CMS collaboration itself on page one of their publication CMS CR-2016/121 [32], which described trashing 4,000 FPGAs and ASICs Level-1 Trigger boards due to its limitations and inefficiencies stating: ‘The legacy Level-1 trigger system is composed of approximately 4000 data processor boards, of several custom application-specific designs … This large proportion of subsystem-specific software resulted in high long-term maintenance costs, and a high risk of losing critical knowledge through the turnover of software developers in the Level-1 trigger project. … So, the Level-1 trigger system has been upgraded during 2015 and early 2016, in order to improve its efficiency for searches and precision measurements, compared with the previous run…’.

Yet, instead of correcting course, CERN replaced it with new FPGA-Based systems that were similarly flawed.

9.1.2. Repeated Failures and Contradictions

The repeated cycle of building and then scrapping FPGA-based Level-1 Triggers demonstrates their failure.

The original justification for adopting FPGAs was their programmability. If this were true, one universal FPGA-based trigger system could have served multiple experiments. Instead, each experiment chose to design its own, further proving that FPGAs are unsuitable for the Level-1 Trigger task.

Now, for the HL-LHC (2026–2036), CERN is building yet another massive FPGA-based Level-1 Trigger system—such as the CMS design [30] with 20 trillion transistors—a project that will waste over $12 billion [31] if not halted.

ATLAS and other experiments could not use the supposedly ‘programmable’ CMS FPGA system and developed different FPGA-based Level-1 Triggers, incurring additional costs each time for new boards, crates, and systems.

The concept of solving a problem with programmable operations (add, subtract, multiply, etc.) requires hardware capable of meeting these requirements—similar to calculating the volume of a cylinder or solving other equations on a smartphone, PC, Apple Power Book, workstation, or mainframe.

In the case of the Level-1 Trigger, the challenge is to determine if an FPGA ‘black box’ can do something all other computers cannot: sustain an input bandwidth of 40 MHz across thousands of electronic channels, while processing each dataset independently with hundreds or thousands of programmable operations for pattern recognition and fast neighboring data exchange—without data loss.

Since 1999, CERN has built several of these FPGA-based black boxes for LHC experiments, but none met the requirements.

The first designs combined ASICs and FPGAs, later replaced by FPGA-only systems claiming ‘full programmability.’ All had to be scrapped—such as the 4,000 CMS FPGA boards trashed in 2016 [32].

The most recent CMS FPGA-based Level-1 Trigger with 1,226 boards (Table 3.2, p. 46 of the CMS-TDR [32]) consuming 650 kW will also fail. The same has occurred in ATLAS and other experiments, wasting many thousands of boards and millions—if not billions—of dollars.

These failures could have been predicted before construction simply by running a simulation—a step that was never performed.

By contrast, Crosetto’s 3D-Flow design, funded with a $1 million DOE grant [22] to conduct a feasibility study, demonstrated in a 45-page peer-reviewed article [20] that he could build a black box for 1,024 channels (analog or digital input), sustaining 40 MHz input data rate and executing up to 400 programmable operations per dataset in parallel on each channel every 25 ns.

Four such 3D-Flow black boxes (32 boards total) could have met the LHC requirement of 1.2 billion events per second until 2026, without redesign, replacing several generations of 4,000-board FPGA-based systems developed since 1999.

Instead of endorsing and funding this single 3D-Flow black box—capable of meeting the requirements of all experiments, reducing development costs, and ensuring effectiveness—CERN allowed each experiment to develop its own FPGA-based trigger without requiring a full simulation to prove it could execute Level-2 Trigger algorithms at Level-1.

From 1999 onward, Crosetto’s presentations and journal articles in leading LHC instrumentation venues were suppressed. In 2015, his former supervisor from the 1993 Superconducting Super Collider who was holding the position of Director of the U.S. Department of Energy, Office for High Energy Physics (DOE-HEP), handling approximately $1 billion per year, solicited Crosetto to submit a proposal for a 3D-Flow black box meeting all experiments’ needs. Crosetto designed the system, submitted the 274-page proposal [24], supported by 59 industrial quotes, but the project was again blocked.

Suppression occurred again on 3 July 2025, when Crosetto’s universal modular 3D-Flow board [3]—512 channels / 2,418 operations × 8, creating a 3 kW black box to replace the 1,226-board, 650 kW CERN CMS FPGA-based Level-1 trigger—was suppressed together with the two-page article comparing the 3D-Flow architecture with CERN FPGA-Based Level-1 Trigger [2], without any scientific reason by anonymous reviewers of the 2025 IEEE-NSS-MIC-RTSD Conference in Yokohama, Japan.

The papers were not ‘rejected’ because a rejection would require a valid scientific reason, but simply suppressed, as confirmed in written and verbal communication with the conveners [33].

This latest modular 3D-Flow board, designed in 20 nm CMOS with 128 processors per IC, can sustain a 40 MHz input rate. One black box can execute 2,418 operations per dataset; four black boxes can execute 9,672 operations per dataset at a cost of $86,000 each—serving all CERN experiments until 2042.

The reason for 32 years of suppression is clear: if the 3D-Flow black box described in Crosetto’s 1999 peer-reviewed article [20] had been funded, thousands of scientists over 27 years would have lost the justification to request slices of the $2 trillion/year global R&D budget to develop thousands of boards, then seek more funds for ‘upgrades’ and maintenance after each failure. A single $100,000 3D-Flow black box per experiment would have eliminated the need for this cycle.

In 2025, the same logic applies: Crosetto’s modular board can build a black box sustaining 40 MHz, capable of 2,418 operations per dataset for $86,000, or 9,672 operations per dataset for $344,000 (four boxes). Funding it would remove the pretext for thousands of scientists to request ongoing hardware, software, and maintenance funds over the coming years.

Thus, each experiment has developed its own ‘programmable’ FPGA-based Level-1 Trigger not for technical necessity, but as a way to justify continual funding requests from the $2 trillion/year R&D budget.

The apparent objective is not to fund the project that solves the problem most cost-effectively, but to maintain an excuse for funding flows.

Scientists best connected to funding sources, as stated by Scientific American [11] rely on the fact that taxpayers cannot easily judge which project is in their best interest. They leverage the prestige of their universities, institutions, and CERN itself—while collectively suppressing transparency and blocking any public meeting with Crosetto that could expose the scientific truth.

To better understand the forces driving this process, the next section presents data on CERN’s annual funding and how these resources are allocated.

9.1.3. Supporting the claimed over $12 Billion in Waste in the next decade

The estimated $12 billion [31] in public funding likely to be wasted is a conservative calculation based on:

CERN’s Annual Budget (Average: $2.5–3 Billion)

• $1.4 Billion/year in general costs funded by member states
• $1.1–1.6 Billion/year from:
  • EU Horizon Europe program (e.g., €95.5 billion between 2021 and 2027, a portion funding CERN projects)
  • U.S. DOE and NSF
  • National labs and universities (INFN, CNRS, STFC, etc.)
  • Over 100 contributing countries
    
    

Approximately 90% of this budget is allocated to LHC-related activities, while the remaining 10% supports other experiments and operations.

Estimated annual amount of $2.0 Billion to $2.5 Billion for CERN LHC activities

Other Activities (10% of Budget) in the range of $250 million to $500 million per year

include:

• Smaller CERN experiments (e.g., ISOLDE, COMPASS, NA62, ALPHA, AEGIS, GBAR, AWAKE, CLEAR)
• Technology development (superconductivity, cryogenics, WWW, medical applications)
• Education and training
• Administrative overhead
• Future R&D (e.g., FCC studies)
  
  

LHC Operating Costs

• The current operating cost per day of the LHC generating 1.2 billion event per second is approximately $2.63 million per day.
• The estimated operating cost per day of the upgraded HL-LHC generating 8 billion event per second is approximately $4 million per day.
  
  

Therefore, the estimated waste of $12 Billion over the next decades—driven by the inefficiency of CERN’s FPGA-Based Level-1 Triggers, which cannot execute the thousands of operations typical of Level-2 Trigger algorithms—are accounted by the following resource losses.

This include operating the HL-LHC accelerator at a cost of $4 million per day while failing to maximize valid event selection, wasting the salaries of approximately 70% of the 14,000 scientists involved in the HL-LHC, who spent their time and computing resources analyzing mainly ‘garbage’ data.

These expenses are a portion of CERN’s annual LHC budget of $2.5 billion/year, making the $12 billion total waste in the next decade a very conservative estimate.

This waste arises not only from hardware and operational inefficiency but also from the suppression of a far more capable alternative: the 3D-Flow system (see Section 7.3.7 for supporting evidence).

10. [TECHNICAL] The Proven Superiority of Crosetto’s 3D-Flow Electronics vs. CERN FPGA-Based Level-1 Trigger for 2026-2036 HL-LHC

A two-page article [3] by Crosetto describes a 3D-Flow electronic board available in multiple form factors. It can be configured with:

• A variable number of electronic channels
• A flexible number of programmable operations per dataset
• Compatibility with virtually any detector in High Energy Physics, including any crystal detector for medical imaging applications
  
  

This system is proven to deliver higher performance at a fraction of the cost of FPGA-based approaches.

Its practical implementation and scientific superiority are supported by:

• A two-hour IEEE-NSS-RTSD conference presentation (31 Oct. 2024) using 102 detailed slides [13]
• An 82-page scientific article [25] providing simulation, hardware schematics, and detailed analysis
• Zero known refutations or valid scientific objections in over 30 years
  
  

Crosetto simulated the 3D-Flow system with thousands of processors [20], down to the:

• Gate-level (VHDL) simulations
• Transistor-level linked to a specific CMOS technology
  
  

He successfully demonstrated feasibility and functionality in hardware in a 3D-Flow system with 144 processors [23].

Industry-Validated Feasibility and Cost Proposal

In 2015, Crosetto submitted a 274-page proposal [24] that includes:

• A complete Level-1 Trigger system
• A full 3D-Flow system for the 3D-CBS medical imaging device for early cancer detection
• 59 cost quotes from reputable companies, detailing:
  
  
  • Total system costs
  • Component timelines
  • Manpower and fabrication stages
    
    

This proposal provided full traceability from design to implementation, enabling public accountability.

3D-Flow Cost and Efficiency Details

• 3D-Flow IC implemented in 20 nm Ultra-Low power consumption CMOS can accommodate 128 processors per chip at $0.50 each, consuming less power than 7 nm FinFET FPGAs used by CERN.
• A single 3D-Flow system with 68,352 processors housed in an ATCA crate, costs approximately $86,000 and can meet any Level-1 Trigger requirements for all physics experiments through 2042, thanks to its flexible configuration.
• Flexible Configuration:
  
  
  • 4,096 electronic channels Capable of 2,418 programmable operations per dataset. (If double operations per dataset are needed, either halve the number of channels within the same crate, or use two crates for the same number of channels).
  • 2,048 electronic channels Capable of 4,836 programmable operations per dataset. (Same flexibility as before to double the number of programmable operations).
  • 1,024 electronic channels Capable of 9,672 programmable operations per dataset
    
    

For technical board designs and system schematics, see Figures 58–59, pages 74–76 of [25].

Comparison with CERN CMS FPGA-Based Level-1 Trigger (from CMS-TDR-022)

Crosetto published another two-page article [2] summarizing a direct comparison between the 3D-Flow and CERN’s FPGA-based trigger systems.

Feature	3D-Flow System	CERN CMS FPGA-Based System
Power Consumption	6 kW (3 kW, 3D-Fow; 3 kW Receivers)	Over 650 kW
Programmable Operations	Over 8,000 per dataset	~66 per dataset
Cost	~$86,000 per crate	Hundreds of millions USD
Architecture	Fully deterministic, programmable, scalable	FPGA not suitable for sustaining high input data rate
Hardware	8 x 3D-Flow boards in a crate	1,226 boards across 130 crates
Source	pp. 74-76 of scientific article [25]	Table 3.2, p. 46 of CMS-TDR-022 [30]

Conclusion

The continued preference for FPGA-based Level-1 Trigger systems—despite 30 years of scientific evidence showing it to be inadequate for Level-1 Trigger—has led to an estimated waste of over $4 billion to date, with an additional $12 billion at risk in the coming decade.

Crosetto’s 3D-Flow system, backed by:

• Simulation of the full 3D-Flow system for Level-1 Trigger, feasibility and functionality in hardware of a 144 processors 3D-Flow system
• Industry-supported implementation quotes
• Peer-reviewed feasibility
• IEEE-recognized presentations, unrefuted to date
  
  

...offers a verifiably superior and cost-effective alternative that meets all current and future physics requirements until 2042, while also holding the potential to revolutionize early cancer detection.

This is a turning point. Funding the inventor of the 3D-Flow system and 3D-CBS device must not be delayed.

11. Misuse of Trust, Funds, and Scientific Authority: Did CERN Betray Its Mandate to Serve the Public and Advance Science?

Guiding Question:

Did CERN, entrusted by taxpayers and parliamentarians with the mission to advance science with integrity and transparency [34]—including through initiatives such as advocating for progress in healthcare—instead use this trust to promote internal agendas, fund inferior projects, and suppress scientifically sound alternatives such as Crosetto’s inventions aimed at reducing cancer deaths through cost-effective early detection?

A Pattern of Deliberate Suppression and Self-Dealing

Contrary to its stated mission: ‘To conduct world-class research …to advance scientific knowledge and technology for the benefit of all’ and vision ‘To be a global leader in scientific discovery, technological innovation, and international cooperation, inspiring future generations and contributing to a deeper understanding of the universe’, CERN has, over the course of more than a decade, taken decisions that are not only inconsistent with logic and scientific rigor but also detrimental to public health and fiscal responsibility.

These actions were not occasional oversights, but rather deliberate and conscious choices, repeated over the years—often suppressing more promising and cost-effective innovations.

2010: ‘Physics for Health’ Workshop—Self-Awarding, Lack of Transparency

From February 2–4, 2010, CERN organized the high-profile ‘Physics for Health’ workshop, attracting hundreds of scientists from around the world. Rather than fostering open scientific dialogue and evidence-based evaluation of competing technologies, the event became a platform to promote internal projects for funding advantage, notably:

• The first prize was awarded to the ‘AXIAL-PET’ project, despite it being less efficient and more expensive than other commercially available PET technologies.
• The CERN Director of Research and Director of Scientific Computing, who awarded the prize, did not disclose that he himself was the head of the AXIAL-PET project, nor that he was also chair of the workshop’s scientific committee—effectively awarding the prize to himself.
• The AXIAL-PET detector module, with its low sensitivity, required a higher radiation dose to patients, making it inappropriate for clinical use and incompatible with improving measurements of minimal abnormal bio-physiology.
  
  

When Crosetto attempted to raise these issues—pointing out that the AXIAL-PET design was inadequate for measuring bio-physiology and that the project misrepresented the goals of PET technology—his microphone was cut off in the middle of a packed CERN auditorium.

Despite Crosetto distributing a well-documented article co-authored with 14 scientists and signed by over 1,000 supporters—titled ‘Progress in the Domain of Physics Applications in Life Science…’[35]—it was ignored by the organizing committee.

The abstract was translated into ten languages and copies of the full article were disseminated throughout the conference.

Further Evidence of Misconduct:

• The AXIAL-PET project was later abandoned as shown on the now-defunct CERN webpage: https://twiki.cern.ch/twiki/bin/view/AXIALPET/WebHome
• Nevertheless, the project received European Commission funding (Marie Curie IEF grant 237620) and secured the support of nine universities and research institutes—misled by the false endorsement and visibility it received at CERN.
  
  

2011: CERN Director of Research Acknowledges in a Meeting the Validity of Crosetto’s Claims

On 12 January 2011, Crosetto visited CERN with an Italian cardiac surgeon and held an in-depth, technical discussion with the CERN Director of Research. The transcript of this meeting confirms that Crosetto clearly explained:

• The fundamental differences between his 3D-CBS system and the flawed AXIAL-PET approach.
• Why measuring spatial resolution is not the correct objective for improving PET efficacy in early cancer detection.
• The electronics and detector requirements for a cost-effective system capable of significantly reducing premature cancer deaths.
  
  

The Director acknowledged the scientific distinctions, but no action was taken to initiate further review or invite a public comparison of the two approaches.

2016: Still No Transparency, Despite Acknowledgment of Scientific Merit

At the IEEE-NSS-MIC-RTSD conference in Strasbourg (3 November 2016), the same former CERN Director of Research approached Crosetto, expressing interest in his 274-page proposal [24] and 59 quotes from reputable industries that he had submitted on 22 December 2015 to the U.S. Department of Energy.

The proposal outlined a detailed plan for:

• An experimental test of the 3D-Flow system at CERN for a universal Level-1 trigger application.
• The complete construction of a 3D-Flow system for the 3D-CBS device for early cancer detection.
  
  

Despite the fact that:

• No element of Crosetto’s proposal was scientifically refuted, and
• The Director of Research was fully aware of the suppressed opportunity to benefit science and public health…
  
  

…he took no initiative to arrange the requested public scientific meeting to compare the 3D-Flow with CERN FPGA-Based Level-1 Triggers used at CERN.

Conclusion
The cumulative evidence of misconduct, suppression of transparency, and self-serving promotion of inferior technologies points to a serious breach of public trust by influential CERN leadership figures. Rather than leveraging their institutional power to advance life-saving innovations and uphold scientific ethics, they:

• Promoted inferior internal projects through deceptive practices,
• Silenced dissenting but scientifically supported voices, and
• Ignored superior alternatives like the 3D-Flow and 3D-CBS systems, despite widespread support and clear potential to reduce cancer deaths and healthcare costs.
  
  

Immediate corrective action is needed:

• A public scientific comparison between Crosetto’s invention and CERN’s FPGA-Based systems.
• Freezing of funding for flawed CERN projects [9] until full transparency and accountability are restored.
  
  

Only then can CERN reclaim the moral and scientific authority it once held in the eyes of the public and the global research community.

11.1. European Funds Misused: CERN’s ATTRACT Program Funded Flawed Projects While Suppressing Validated, Life-Saving Innovations

Guiding Question:

Did CERN’s ATTRACT initiative, funded by European taxpayers under Horizon 2020, fulfill its mission to support breakthrough imaging and detection technologies—or did it serve to promote unscientific and impractical projects while deliberately suppressing the superior and validated 3D-CBS innovation?

A Timeline of Scientific Suppression and Funding Misallocation

2018 – €17 Million from Europe Horizon 2020 Misused

In 2018, the European Commission granted €17 million to the CERN-ATTRACT consortium (H2020 Grant No ATTRACT-777222) with the task to provide ‘funding to projects aiming at breakthrough innovations in detection and imaging technologies that could be achieved in the next decade and have a solid starting point today.’

Despite fully meeting these criteria—having been recognized as a breakthrough for particle detection at Fermilab in 1993, validated in peer-reviewed literature, and applied to cancer detection since 2000—Dario Crosetto’s 3D-CBS project received no funding. Crosetto had personally:

• Informed the former CERN Director of Research, head of the ATTRACT initiative, and the only person to hold two leadership positions in the ATTRACT organization: Head of R&D&I (Research, Development and Innovation) and Chair of the ATTRACT Scientific Review Committee, during meetings in 2010, 2011, and 2016,
• Submitted a detailed proposal with solid scientific justification,
• Sent a copy of the application to ATTRACT scientific reviewers.
  
  

No scientific objection or refutation was provided—only silence and an unexplained refusal to fund.

2019 – Funding Awarded to the Unscientific WPET Project

On 21 May 2019, the ATTRACT program instead funded the WPET (‘Wearable PET’) project—proposing a 350+ kg coat to be worn continuously for 24 hours for screening to detect cancer. The project was:

• Scientifically implausible,
• Logistically and medically impractical,
  
  

When Crosetto attempted to raise these concerns in the CERN public auditorium to comment on the WPET slide during the award presentation [³⁶], he was silenced once again.

The same WPET authors later submitted another proposal for a ‘wearable PET jacket’, equally ineffective for early cancer detection. Crosetto thoroughly refuted the submission point-by-point [37]). He never received any response regarding the outcome of this review.

2021 – European Parliament Demands Accountability

On 21 June 2021, Hon. Alessandro Panza, MEP, submitted a Parliamentary Question [38] (translated in 24 languages) to the European Commission demanding:

• Transparency from CERN-ATTRACT regarding the unjustified funding the impractical and scientifically inconsistent WPET project,
• Explanation for the suppression of the scientifically validated 3D-CBS project.
  
  

Parliamentary Question [38]: https://www.europarl.europa.eu/doceo/document/E-9-2021-003244_EN.html

2022 – European Commission Doubles Down

Rather than investigating these concerns or requiring a public comparison of WPET vs. 3D-CBS, the European Commission awarded another €28 million to the CERN-ATTRACT [39] consortium.

Announcement: https://cerneu.web.cern.ch/attract-unveils-projects-will-benefit-its-eu28-million-fund-innovation

This further validates the concern that CERN was informed about the ATTRACT funding that was used to reward unjustified, impractical projects while suppressing evidence-based, life-saving alternatives.

The Scientific and Moral Case for the 3D-CBS

Crosetto’s 3D-CBS device combines the 3D-Flow architecture with PET detectors to identify early cancer markers—detecting as few as 100 cancer cells, long before traditional methods (CT, MRI, mammography) which require tumors with over 1 million cells, equivalent to about 1 millimeter in size.

This project:

• Has never been scientifically refuted,
• Was supported by over 1,000 signatories,
• Is documented in peer-reviewed articles, a 274-page proposal with 59 industry quotes, and an IEEE conference presentation,
• Has the potential to halve cancer mortality rates, based on conservative estimates and sound biostatistical modeling.
  
  

These chronological facts and circumstances demonstrate that CERN was informed about the 3D-CBS invention—cost-effective for early cancer detection and scientifically unrefuted since 2000—with the potential to save millions of lives. Nevertheless, taxpayer money was instead used to fund projects that, by common-sense analysis, could not significantly reduce cancer deaths or costs.

Only transparency, accountability, and cooperation through open dialogue can save CERN.

12. Accountability in Cancer Research: The Burden of Proof Belongs to Those Claiming Lives Saved

Organizations and researchers who raise public funds under the premise of reducing cancer deaths must be held to a basic standard: demonstrate measurable, evidence-based reductions in mortality in defined populations.

12.1. How to Prove a Cancer Reduction Claim Scientifically

A scientifically credible proposal for reducing cancer deaths must include:

• A defined geographic population, e.g., 10,000 people aged 55–74 from a region with stable cancer mortality rates.
• A quantified mortality baseline over 20+ years.
• A specific innovation or intervention (e.g., early detection device, treatment, or lifestyle plan).
• An implementation plan reaching at least 75% of that population.
• A statistically and ethically robust plan for comparing pre- and post-intervention mortality.
  
  

Annual measurements of cancer mortality in the test population, with participation rates above 75%, will update the interactive ROADMAP table [40] values each year, enabling progressively more accurate projections of 30-year mortality reduction before the study concludes.

Randomized trials on populations scattered across regions do not isolate the effects of a specific intervention and are susceptible to confounding variables, therefore, they cannot provide indisputable results.

12.2. Italy’s President, Head of the Italian Army, and Ministry of Defense as a Model Pilot Group

Scientist Dario Crosetto proposed such a test to:

• President of Italy, Hon. Sergio Mattarella (via hand-delivered letters on April 25, annually since 2023),
• Minister of Defense, Hon. Guido Crosetto.
  
  

He requested that 0.1% of the national defense budget be allocated to build two 3D-CBS devices to screen Italian military personnel annually. With over 800 cancer-related deaths annually among Defense personnel, he projected:

• A reduction of 400 deaths per year using the 3D-CBS for early cancer detection, followed by a prompt existing successful treatment.
• A model test group that can yield clear, measurable impact results within three years.
  
  

Last letter to the President (25 April 2025): Open letter to the President of Italy and to the public [41].

Final Observation

To fund projects that claim to reduce cancer deaths without requiring evidence, while rejecting innovations like the 3D-CBS that are supported by logic, peer review, and feasibility data, is not only a scientific failure—but an ethical one.

Only transparency, accountability, and cooperation through public, evidence-based evaluation can restore public trust in institutions like CERN and the European Commission’s research funding bodies.

12.3. Verifiable Roadmap to Save Millions of Lives: Quantifying Results Year by Year

Scientist Dario Crosetto has developed a data-driven ROADMAP to defeat cancer [4], rooted in experimental and epidemiological evidence. The model provides verifiable, year-by-year estimates of cancer deaths and costs that can be prevented through the adoption of the 3D-CBS early cancer detection system.

Key Elements of the Study

• Based on official survival data from the World Health Organization (WHO), National Cancer Institute (NCI), American Cancer Society (ACS), and leading universities, early-stage cancer detection yields up to 98% survival.
• Using a conservative 58% success rate for the 3D-CBS system (early detection combined with timely treatment), a single 3D-CBS device screening 90,000 people per year in the 55–74 age group is estimated to save over 260 lives annually:
  
  

450 expected annual deaths × 58% survival improvement = 261 lives saved/year/device

• The roadmap [4] applies a conservative success curve starting at 13% life-saving impact in the first years, rising to 58% after 10 years of population screening.
• Over 30 years, the model projects:
  • Over 100 million lives saved
  • Over $27 trillion saved in global cancer treatment and productivity losses.
    
    

This makes 3D-CBS one of the most cost-effective life-saving technologies ever proposed in oncology.

13. The 2011 CERN Blunder on the Neutrino Fiasco: When Scientific Ego Overruled Scientific Rigor

The infamous 2011 claim by CERN scientists that neutrinos had been measured traveling faster than the speed of light—later disproven—was not simply a bold experiment gone wrong. It was a case of scientific incompetence, poor experimental design, and a failure to apply fundamental principles of measurement accuracy.

Background

On 23 September 2011, Antonio Ereditato, spokesperson for the OPERA experiment, publicly announced what he called a ‘crazy result’ and made an appeal for help in understanding his measurement:

‘We are not claiming things, we want just to be helped by the community in understanding our crazy result—because it is crazy.’ — Antonio Ereditato, BBC News [42].

Crosetto’s Timely Scientific Explanation of a Flawed Experimental Setup

In response to this public appeal, Crosetto, on 2 October 2011—just one week later—sent a detailed response [43] to Ereditato’s appeal for help, explaining that the setup of the OPERA experiment to measure neutrino speed was flawed and could never provide an unambiguous result.

Crosetto also sent copies of his response to the BBC, The Washington Post, The New York Times, and CERN leaders, urging them to explain the flaws to the public, retract the alarming news, and reassure people that the speed of light had not been challenged. However, the BBC and other outlets did not publish Crosetto’s response, leaving the public in limbo for an additional five months, although Crosetto continued to correspond with CERN scientists [44] and provided proof that five years before their electronics in 2008, he had designed and built electronics hundreds of time more accurate [45].

Crosetto’s letter [43] to Ereditato and media explained that the 730 km baseline used for Time of Flight (TOF) comparison between neutrinos and photons in the OPERA experiment introduced uncontrollable variables due to:

• Unpredictable satellite position in GPS synchronization — the exact distance from a satellite to two points on Earth cannot be relied upon a resolution of picoseconds because its position is affected by gravitational perturbations, solar radiation pressure, and atmospheric drag.
• Clock drift of satellite-based timing systems relative to ground-based atomic clocks.
  
  

He argued that GPS-based synchronization over such distances inevitably introduces systematic uncertainties that prevent truly unambiguous results.

Crosetto proposed that a valid experimental setup to eliminate these uncertainties would involve:

• Using two ultra-precise synchronized timers over a 3–7 km baseline, measuring a direct light beam between two towers on the Earth’s surface, sent in parallel with a neutrino beam over the same distance.
• Swapping the timers between the light and neutrino beam measurement setups to eliminate systematic biases from cable lengths and electronics delays.
  
  

Crosetto provided supporting documentation showing that, in 2003, he had designed, built, and tested hardware with a timing resolution of 10 picoseconds and a maximum skew of 40 picoseconds between any clock in a system with thousands of boards—hundreds of times more precise than OPERA’s 2008 electronics.

He achieved this performance during the board design [46] stage by integrating a programmable delay line chip MC100EP195, which has a minimum delay step of 10 picoseconds, and by connecting the output pin from this chip to all other chips on the board using traces of equal length.

During calibration, a clock signal is sent to all boards in the system. Any board that does not respond within the required timing window is adjusted by changing the programmable delay to compensate for differences in cable length between boards and for delays introduced by other circuits.

On February 2012, Crosetto personally handed the above schematics [46] and showed the electronic printed circuit board with equal-length traces to CERN Director-General Rolf Heuer during a meeting in Geneva.

It was only on 23 February 2012 that Ereditato and his colleagues—who had disseminated the initial claim on 23 September 2011—admitted there might have been possible errors in the measurement. Ultimately on 30 March 2012, Ereditato was forced to resign following the public exposure of the flaws, but by then the damage to public trust and taxpayer funds was done. Only on 6 June 2012, did CERN’s Director of Research officially announced that neutrinos are not faster than light.

Summary of the Scientific Failure

• The OPERA team repeated 16,000 measurements over three years without addressing the fundamental design flaws.
• The setup was incapable of yielding unambiguous experimental results—a prerequisite in high-stakes physics.
  
  

As Crosetto warned using the well-known quote:

‘Insanity is doing the same thing over and over again and expecting different results.’

Despite the widely publicized explanation that the OPERA experiment's false result on faster-than-light neutrinos was due to a faulty master GPS clock and a loose connection on the electronic board as publicly stated [47], the root cause was more serious: a fundamental failure in scientific integrity and experimental design. CERN’s scientists never issued a clear admission of responsibility for having conceived and approved an experimental setup that could never yield unambiguous results—even if the GPS clock and the loose connection had been fixed.

13.1. When Scientific Integrity Fails: Blunders from 2010 ‘Axial-PET’, 2019 ‘WPET-coat’, 2020 ‘WPET-jacket’, 2021 ‘Neutrino faster than light’, to the FPGA-Based Level-1 Trigger Waste of Billions in Taxpayer Money Over Three Decades

These blunders serve as a stark reminder: without scientific transparency, proper experimental controls, and openness to external critique, even the most prestigious institutions can mislead the public and waste resources.

From One Costly Failure to Another: The FPGA-Based Level-1 Trigger at CERN

It is urgent to freeze CERN funding [9] for CMS and ATLAS Level-1 Trigger upgrades and to organize a public scientific review comparing Crosetto’s 3D-Flow architecture with CERN’s FPGA-Based architecture.

The Counterpart in Scientific Challenges Is Nature—Not Colleagues Competing for Funding

Scientific progress is achieved by outperforming nature’s complexity through rigorous experimental setups that are:

1. feasible,
2. testable,
3. reproducible under controlled variables,
4. robust against invalidation by irrefutable calculations,
5. able to provide unambiguous results that resolve dilemmas or controversies, and/or
6. advantageous in advancing science for humanity compared to existing ideas or products—without wasting vast amounts of taxpayer money.
   
   

The OPERA debacle is not an isolated case. It reflects a larger problem at CERN: a lack of scientific accountability that continues to this day with CERN’s FPGA-Based Level-1 Trigger projects. For 30 years, Crosetto’s 3D-Flow invention—recognized in 1993 at Fermilab as a breakthrough [10] capable of executing Level-2 trigger algorithms at Level-1 speed—has been ignored, despite unmatched efficiency, power savings, and feasibility demonstrated down to transistor-level simulation and real hardware.

Instead, CERN has continued to pursue inefficient, power-hungry FPGA-based systems, now culminating in the HL-LHC FPGA-Based Trigger systems, such as the monster 20-trillion transistor, 650 kW CMS [30] Level-1 Trigger system [28].

This lack of transparency and accountability is not limited to measuring neutrino speed and Level-1 Triggers; several other cases also reveal a lack of scientific rigor in the design and execution of experiments, as illustrated by the examples listed above and summarized below:

• 2010: Axial-PET — Awarded first prize at CERN’s ‘Physics for Health’ workshop, yet calculations show it is less efficient (d), more expensive than commercial modules (f), and unsafe for human PET use.
• 2019: WPET-coat — Funded by CERN-ATTRACT. A 350 kg coat [36] intended for 24-hour cancer screening: not feasible (a), not testable (b), ineffective for early detection (d), incapable of reducing premature deaths (f). Basic calculations on crystal weight should have revealed its impracticality.
• 2020: WPET-jacket — Submitted for €2 million by the same authors as WPET-coat. Scientifically rejected [37] point-by-point by Crosetto, but his analysis was ignored. Ineffective for screening (d) and could not significantly reduce premature cancer deaths (f).
• 2021: CERN-OPERA neutrino faster than light experiment [43] — Not feasible (a), not testable (b), not reproducible (c), invalidated by calculations (d), ambiguous in results, which could be obtained instead with Crosetto’s proposed 3–7 km swapped-timer setup (f).
• 1999–2025: CERN FPGA-Based Level-1 Trigger — Invalidated by calculations and experimental evidence [25]. Fails to meet requirements for cost-effectively filtering 1.2 billion events/sec (LHC) or 8 billion events/sec (HL-LHC) (d), wasting billions of taxpayer euros while suppressing 3D-Flow, which has been proven to meet these requirements cost-effectively (f).
  
  

13.2. The Root Cause: Lack of Transparency, Accountability, and Open Scientific Dialogue

The core issue is not just poor technical choices—it is systemic scientific malpractice:

• Suppression of valid challenges.
• Denial of proposals without technical justification.
• Refusal to organize public scientific reviews like the one held on 14 December 1993 at Fermilab, where Crosetto’s invention was reviewed openly.
  
  

For decades Crosetto has repeatedly requested such a meeting. No one has ever refuted his calculations, simulations, or hardware implementations. Yet CERN and its review panels have chosen to ignore or silence his work, funding instead FPGA-based designs whose inefficiencies are now well documented.

13.3. A Path Forward: Restore Scientific Integrity to Restore Public Trust

The challenge in science is not to convince an influential colleague to give you a slice of the annual $2 trillion in global R&D [11], but to understand the laws of nature—through rigorous experiments—that your idea works. Reputation, career advancement, and funding should follow experimental success, not failure.

Today, the opposite often occurs: projects with no verifiable results continue receiving funding, while proposals like Crosetto’s 3D-CBS—capable of halving cancer deaths in a defined population—are suppressed without review.

If all projects seeking public or donor funds were required to submit a verifiable roadmap [4] (see Section 12) and demonstrate year-by-year results, the best ideas would prevail, billions would be saved, and millions of lives could be spared.

Final Call

Scientific progress must be built on:

• Transparency
• Accountability
• Public, open, evidence-based dialogue
  
  

Only by restoring these values can institutions like CERN regain the public’s trust, and humanity gain the full benefit of scientific discovery.

The time is now to stop the waste, support breakthrough innovations, and turn rhetoric about ‘advancing science for humanity’ into real action.

14. On the Use of the Words ‘Suppression,’ ‘Waste,’ ‘Plagiarism,’ ‘Copying,’ and ‘Corruption’

These terms should never be used lightly. They carry serious weight and should only appear in scientific or public discourse when supported by clear and documented facts. This document has presented substantial evidence and verifiable events that fully justify their use in the context of the treatment of the 3D-Flow and 3D-CBS inventions over the past 30 years.

A Clarification for the Reader

Some readers may form the impression when reading this document—especially this section—that Crosetto has always pointed out issues that do not comply with transparency, the laws of nature (science), the code of conduct and ethics of scientists, and accountability.

This is not the case. Many facts and actions demonstrate otherwise.

None of Crosetto’s articles before the year 2000 mentioned any complaint mentioned above, they only presented technical-scientific matter. Facts and documents also prove that not all his colleagues suppressed his inventions, presentations, articles, and funding.

For example:

• Recognition: His 3D-Flow invention was acknowledged as a breakthrough in a public scientific review at Fermilab in 1993 [10].
• Funding: He received a $1 million grant [22].
• Publications: His peer-reviewed articles, such as in NIM [20], contained no complaints of suppression of transparency or science.
• Outreach: At the 2000 IEEE-NSS-MIC Conference in Lyon, France, he distributed 200 free copies of his book [7], trusting that transparency and honesty among leading scientists would ensure his innovations were recognized and supported.
• Education: He believed that by explaining clearly his inventions in ways accessible even to middle- and high-school students, leaders handling the annual $2 trillion R&D funds would support innovations beneficial to humanity that no one refuted. Together with a Montessori school, he co-authored the 2000 book Understanding a New Idea for a Cancer Screening Device (ISBN 09702897) [26].
• Trust in institutions: Believing that leaders in the scientific community would promote honest science and that the judicial system would enforce the rule of law, he protected his innovations with patents, hoping to secure funding by protecting investors, accelerate development, and ultimately bring the benefits of his work to patients.
  
  

Notably, his work up to 1999—and in some cases afterward—received praise and support from prominent figures, including:

• Jerry Merryman, inventor of the pocket calculator [19]
• Silvio Turrini, Inventor of the first 400 MHz ECL processor [18]
• A Nobel Prize winner
• A former Director of Fermilab
• CERN division and group leaders
• General Chairs of IEEE-NSS-MIC-RTSD Conferences
  
  

These individuals and many others [17] endorsed Crosetto’s work and inventions. Some IEEE Conference Chairs even attempted to restore transparency in the scientific process—but these efforts were overpowered by more influential scientists who control privileged access to the $2 trillion global annual R&D funding. As Scientific American (Ioannidis, Oct. 2018, p. 54) [11] observed:

‘Funding is largely concentrated in the hands of a few investigators... not necessarily genuine superstars; they may simply be best connected.’

That article also noted that 75% of top cancer drug papers are not reproducible. This aligns with John Horgan’s article, The Cancer Industry: Hype vs. Reality (Scientific American, Dec. 12, 2020).

14.1. When the Usual Channels Are Blocked

Crosetto eventually faced the reality that differed from the ideal world that he imagined, that the scientific community would continue to recognize and fund his innovations, and that the judicial system in a civilized world would enforce the rule of law, transparency and fairness. Instead, his conference presentations, articles, and funding applications were suppressed. His only alternative was to attempt to disseminate his inventions by distributing documentations directly to his colleagues at Conferences and through direct emails and social media platforms.

From 2014 onward, beginning at the IEEE-NSS-MIC-RTSD Conference in Seattle, WA, he distributed his articles and proposals at CERN and at scientific conferences worldwide, directly to thousands of participants—sometimes within CERN and conference premises when permitted by the Chair. Since traditional channels (publication, funding, and conference presentations) were systematically blocked or ignored, this became the only viable means of informing colleagues.

Despite widespread dissemination (thousands of printed documents between 2014–2023), his peer-reviewed studies, breakthrough designs, and books received little to no citations—even as key concepts were copied or plagiarized in later projects.

14.1.1. Suppressed Recognition of the 3D-Flow Valid Breakthrough (33 Years of Lost Benefits)

• 1993: The 3D-Flow invention was recognized at Fermilab [10] as a breakthrough, capable of executing programmable algorithms at Level-1 Trigger speed, previously thought possible only at Level-2.
  
  
  • Yet today, there is no public traceable record of the official Fermilab report signed by the review panel chair.
  • Crosetto has been informed that the report must exist internally, as the review was an official, budgeted Fermilab event.
    
    

This invention which overcame the speed limitations in acquiring and processing data arriving at ultra-high speed with complex, programmable pattern-recognition algorithms in real time, could have transformed multiple fields, including medical imaging for early cancer detection. Instead of being disseminated, it was suppressed and obscured.

14.1.2. Ignored Peer-Reviewed Board-Level Design (33 Years of Lost Benefits)

• 1999: Crosetto published a 45-page peer-reviewed article [20] with 37 references describing 3D-Flow boards and crates. Using 120 nm CMOS, these could execute 400+ programmable operations (with data exchange among neighbors) on each dataset arriving every 25 nanoseconds—meeting requirements to cost-effectively filter 1.2 billion events per second from LHC-Detectors apparatus at Level-1 Trigger until 2026.
  • Despite distribution of thousands of copies at IEEE-NSS-MIC-RTSD conferences in 2014, 2016, 2017, 2018, 2019, 2022, 2023, at presentations, press releases, social media, it has received only nine citations.
  • Meanwhile, CERN spent hundreds of millions of euros on inferior FPGA-based Level-1 Triggers, resulting in a documented waste of over $4 billion (See Section 8).
    
    

14.1.3. Unfunded 3D-CBS Breakthrough (25 Years of Lost Benefits in Saving Lives)

• 2000: Crosetto published the book ‘400+ Times Improved PET Efficiency for Lower-Dose Radiation, Lower-Cost Cancer Screening‘ [7] (ISBN 0-9702897-0-7), registered with the U.S. Library of Congress (Card No. 00-191510).
  • He presented his book, together with two articles [48], [49] at the 2000 IEEE-NSS-MIC Conference in Lyon, France, and distributed 200 free copies of his book to leading experts.
  • As of August 2025, Not a single citation of his book has followed, despite evidence of replication, copying, and plagiarism in later projects.
     

14.1.4. Blocked a Universal 3D-Flow System Requested by DOE-HEP Director (33 Years of Lost Benefits, >$4 Billion Wasted)

• 2015: Crosetto’s former supervisor from the Superconducting Super Collider in 1993 and serving as Director of the U.S. DOE-HEP in 2015, invited him to submit a proposal for a universal 3D-Flow programmable Level-1 Trigger system capable of meeting the needs of all LHC experiments.
  • Crosetto designed the system and, on 22 December 2015, formally submitted a 274-page proposal [24], supported by 59 industrial quotes. However, the project was again blocked.
  • Meanwhile, CERN continued spending hundreds of millions of euros on inferior FPGA-based Level-1 Triggers, a decision that has resulted in a documented waste of more than $4 billion (see Section 8).
    
    

14.1.5. No Action on 3D-CBS from Science for Humanity (25 Years of Lost Benefits, 39 Million Lives Lost)

• 2023: After Crosetto’s meeting at the Vatican on 5 July 2023 with the Secretary of the Dicastery for Promoting Integral Human Development, and his correspondence with the President of the Pontifical Academy of Sciences (PAS)—which counts 86 Nobel Laureates among its past and present members, including CERN’s Director General (who is a current Council member) —PAS President suggested that Crosetto submit documentation of his 3D-CBS invention for inclusion in the 20 September 2023 PAS Council agenda.
  • On 31 August 2023, Crosetto submitted the document ‘Opportunity to save over 5 million lives per year using new technology for early cancer detection’, which he updated on 18 September [⁵⁰]. The document was circulated to PAS Council members and included in the 20 September agenda. In the same year, Crosetto submitted to the IEEE-NSS-MIC-RTSD Conference in Vancouver the article ‘Over 39M lives needlessly lost from cancer in the past 23 years, and 69M more over the next 7 years because scientists’ goal for PET is to take beautiful pictures and crushed my invention to cost-effectively measure bio-physiology’, [⁵¹] which was later accepted by the following year’s conference.
  • After the PAS meeting, Crosetto spoke directly with the President, who stated that—despite no one refuting his calculations or scientific evidence demonstrating the 3D-CBS’s potential to save millions of lives—the PAS would be unable to host a cancer-focused conference to evaluate in depth his documentation until 2025 due to resource limitations. The President assured him the matter would be re-analyzed at the 2025 PAS Council meeting. However, when Crosetto inquired on 24 May 2025, the day after the Council meeting about the outcome of their evaluation, his submission was again ignored rather than refuted.
    
    

14.1.6. All Six Crosetto Papers Approved for IEEE Presentation, No Refutation, But No Action (33 Years of Lost Benefits)

• 2024: Six of Crosetto’s scientific papers were approved by the seven Chairs of the IEEE-NSS-MIC-RTSD Conference.
  • He was granted two hours to present a 102-slide presentation [13], with both video and slides made publicly available to all scientists.
  • Crosetto answered all questions, and provided an 82-page article [25] that addressed his claims and calculations in depth. None of these were refuted. Yet, no action was taken.
    
    

14.1.7. Suppressed 3D-Flow for HL-LHC by Anonymous Reviewers (50 Years of Lost Benefits, >$12 Billion Future Waste-Section 9.1.3)

• 2025: On 8 May, Crosetto submitted two 2-page articles to the IEEE-NSS-MIC-RTSD Conference, scheduled for 1–8 November 2025 in Yokohama, Japan.
  • The first article [2] compared the universal 3D-Flow programmable Level-1 Trigger system—capable of over 8,000 operations per dataset using 6 kW, and serving all HL-LHC CERN experiments until 2042—with the CERN CMS FPGA-Based Level-1 Trigger, which executes only ~66 operations, consumes 650 kW, and is designed for a single experiment, while still failing to meet HL-LHC requirements. The second article [3] described a modular 3D-Flow board for PET or physics applications, configurable with 512–128 channels and 2,418–9,672 operations, requiring 8–32 boards for a full Level-1 Trigger system—compared to over 1,000 boards in the CMS Level-1 Trigger limited to 66 operations (see Table 3.2, page 46 of CMS-TDR [30]).
  • On 3 July 2025, Crosetto received an email from the IEEE conveners that his paper had been denied by anonymous reviewers. The email stated that reasons could be provided upon request. Within an hour, Crosetto responded, asking for the reasons. After eight hours, Crosetto called the convener, Akira Yoshikawa, in Japan. Yoshikawa acknowledged receiving the request and promised to provide the reasons within two days. When no response was received, Crosetto called again on 8 July 2025, and spoke with Yoshikawa's assistant, who promised to relay the request. Still no response to date.
  • On 16 July 2025, Crosetto wrote a 12-page letter [33] to 41 leaders and CERN funding bodies, including the conveners, as well as current and past IEEE Presidents and conference Chairs, and 720 parliamentarians. The email system confirmed that his message sent to the 41 leaders was opened by 13 recipients, including the IEEE President, but no one responded. The same message was sent to 720 parliamentarians and was opened only by 36 recipients.
  • Efforts have been made to maintain scientific integrity and defend the interests of both taxpayers and cancer patients. To achieve this, press releases have been issued to inform them and the parliamentarians who manage public funds. To raise broader awareness about this critical issue that affects everyone, donations are needed. The following are a few actions taken during the last 2 months:
    • On 23 June 2025, the message [52] was sent to many people, including the 720 parliamentarians and opened by 420 parliamentarians,
    • On 4 July 2025, after suppression of the two articles by IEEE anonymous reviewers, the message [53] was sent via a PR agency to 720 parliamentarians, opened by 461 parliamentarians and was published by 441 outlets in English [53], 421 in French [54], 487 in German [55] and fewer than ten in Italian [56].
  • This pattern of denial without explanation exemplifies a rigged peer-review system that has persisted for decades. A denial without providing any reason is not a rejection—it is suppression. At previous conferences, conveners promised Crosetto the names of anonymous reviewers so he could clarify or support his calculations and claims, but they never followed through. (Proof supporting this statement are available upon request).

Call to Action — Why Your Donation Matters

Your donation is not just financial support—it is the driving force that enables wider PR announcements, reaching more journalists, parliamentarians, and citizens who deserve the truth. Every contribution strengthens this fight for transparency, accountability, and scientific integrity. Without donations, the message risks being silenced; with them, we can amplify awareness by increasing the number of outlets that already published the inconsistencies in science harming all of us that need to be addressed and resolved and make it impossible to ignore.

Without donations, this vital message risks being silenced. With support, we can expand awareness through more media that have already exposed harmful scientific inconsistencies (see the partial list of the outlets that have already published it [66])—making them impossible to ignore and helping save lives.

Please consider making a donation today—because the truth must be heard, and together we can ensure it reaches the world.

Conclusion of Section 14.1.7.

For over three decades, the flawed FPGA-Based Level-1 Trigger system for LHC at CERN has resulted in a staggering waste of billions of dollars, a figure projected to exceed $12 billion in the next decade (see Section 9.1.3).

This persistent financial mismanagement, coupled with the suppression of the 3D-Flow solution—a recognized breakthrough since 1993—represents a profound betrayal of scientific integrity and public trust.

Approving these articles and fostering an open, evidence-based dialogue is no longer optional. It is now essential to protect public funds, restore confidence in scientific governance, and prevent further damage to CERN's credibility before it's too late.

14.2. Denying Presentation, Publication, and Funding Without Scientific Refutation or Reference to Superior Ideas Is Not Rejection—It Is Suppression of Progress

Crosetto’s presentations were denied at several conferences attended by influential scientists who decide the direction of research in both High Energy Physics and Medical Imaging. Written proof of these suppressions is available upon request (some of which are from 2008, 2016, 2017, 2018, 2019, 2022, 2023), along with audio and video recordings of events where his calculations and claims were denied with no scientific reasons. This includes instances when he was asking legitimate scientific questions to colleagues after their talks and to keynote speakers, and the microphone was removed from him.

Scientific Rejection vs. Suppression

Denying a paper or presentation without addressing its scientific content, without identifying errors, and without referring to alternative superior methods does not qualify as legitimate scientific rejection. It constitutes suppression.

When institutions refuse to respond with counter-calculations or evidence, and when authors are denied a fair review process, innovation is not being challenged—it is being silenced. This not only impedes scientific progress but violates the ethical responsibility of the scientific community to foster open, evidence-based dialogue.

14.3. Exclusion from the Review Process Without Scientific Justification

Crosetto’s work has also been excluded from peer review, even after being solicited by journals and platforms operating in his technical field. These exclusions were administrative or procedural in nature—never grounded in scientific refutation.

Example 1: Journal of Medical Imaging (JMI – SPIE)

• On 6 July 2020, Crosetto submitted a 147-page manuscript [57] to the Journal of Medical Imaging (JMI) SPIE) which was assigned ID #20178V from JMI.
• This comprehensive article identified critical flaws in the widely cited SPIE ‘Review Paper’: ‘History and Future Technical Innovation in Positron Emission Tomography’ (JMI 4(1), 011013, 2017).
• The SPIE ‘Review Paper’ misleadingly focused on spatial resolution and supported the partial ring (ART/PRT-1) concept as cost-effective—despite the fact that PET measures biophysiological time-based variables, not dimensions with high spatial resolution to the detriment of sensitivity. Full-body sensitivity is critical for early detection.
• Crosetto provided specific references to non-scientific, incorrect statements contained in the ‘Review Paper’. In several sections, the article mentions reducing the solid angle, like the ART partial ring detector, stating: ‘…Attaining a 10-ps timing would open up an entirely new concept of static partial ring scanner. The partial ring scanner (PRT-1) shown in Figure 6 rotated to collect a complete data set for tomographic reconstruction. However, with 10-ps timing, reconstruction would not be required and thus a partial ring design could be static, potentially a more cost-effective way to achieve a total-body PET scanner.’ This approach is detrimental to providing relevant information on anomalous biological processes to the doctor.
• Crosetto formally requested SPIE to retract the misleading ‘Review Paper’ and to proceed with the scientific review of his correction manuscript.
  
  

On 12 August 2020, JMI informed Crosetto that the review of the manuscript with ID: #20178V was closed without explanation.

• The JMI Editorial Office and Editor in Chief ignored Crosetto’s request and excluded his manuscript from review without providing any reason. Crosetto requested via email and phone for them to provide a reason. On 13 August 2020, the Editorial Office responded that the manuscript was administratively withdrawn because pre-approval had not been requested via a brief proposal—even though the full manuscript already included a title and abstract.
  
  

No scientific comment was ever provided for refusing Crosetto’s analysis. The scientific issues raised were simply ignored, and the original misleading ‘Review Paper’ (JMI 4(1), 011013, 2017) remains published and unchallenged, despite its demonstrable errors.

Example 2: Exclusion from TechRxiv (IEEE)

• Following an invitation from the editor of a major IEEE journal in physics, Crosetto submitted his 82-page article [25] to TechRxiv, an open IEEE preprint platform.
• TechRxiv prevented colleagues from reading the preprint stating that it ‘does not fall within TechRxiv’s scope’—despite the clear overlap with their listed subject areas.
• Crosetto appealed and pointed to multiple scope areas engaged by his article (e.g., high-speed electronics, data acquisition, medical imaging, detector design).
• A senior IEEE journal editor wrote:
  
  

‘I do not understand. The TechRxiv scope on their website includes multiple areas overlapping your manuscript. Have you considered appealing with a list of topics in their scope that your manuscript engages?’

• Crosetto resubmitted two additional times, each time referencing applicable scope areas, but was excluded again—without a scientific explanation or specific editorial comment.
  
  

Conclusion of Section 14.3

The consistent exclusion of Crosetto’s scientifically sound manuscripts—without review, rebuttal, or feedback—demonstrates a troubling pattern.

These are not isolated oversights. They indicate systemic suppression, shielding established but inefficient, misleading or even flawed approaches from critical evaluation, while blocking innovation that threatens existing funding and institutional control.

In science, progress is made through open validation or falsification of ideas—not by gatekeeping, silencing, or administrative evasion. The denial of peer review and publication without transparent reasons is itself a form of corruption of the scientific process.

14.4. Crosetto’s Work Has Been Copied and Plagiarized

Multiple documented cases clearly demonstrate that Crosetto’s inventions and ideas have been copied or plagiarized. Two key examples illustrate this:

Case 1: The EXPLORER Project and NIH Funding

After Crosetto published his 3D-CBS invention in 2000, described in his 234-page book [7] ‘400+ times improved PET efficiency for lower-dose radiation, lower-cost cancer screening’ and distributed 200 copies free of charge to university leaders, reviewers and government funding agencies in the field during the 2000 IEEE-NSS-MIC conference in Lyon, instead of funding him to build the device, U.S. universities appropriated his ideas. These institutions not only copied his core concept, but 15 years later even reused language from the cover of Crosetto’s book in their grant application abstract to the National Institutes of Health (NIH), securing in 2015, $15.5 million in taxpayer funding.

Lacking the technical capability to implement the system themselves, they subcontracted a Chinese company to copy Crosetto’s invention. The resulting device, known as EXPLORER, is now used mainly for drug development and research—a direction that favors the commercial cancer industry rather than fulfilling Crosetto’s original humanitarian goal of enabling cost-effective public health screening to reduce premature deaths.

The EXPLORER system is less efficient and over six times more expensive than Crosetto’s original 3D-CBS design, which is explicitly designed to significantly reduce premature cancer deaths through a cost-effective early detection. (EXPLORER vs. 3D-CBS cost, is supported by slide 70 of [13] showing the EXPLORER device sold for €21 million to the San Orsola hospital in Bologna, Italy in 2024, while the 3D‑CBS is estimated to cost €3.5 million, based on the €2 million cost of components quoted by industries).

Case 2: Plagiarism of 3D-Flow Features Confirmed at IEEE and in Shanghai

On 11 November 2023, during the IEEE-NSS-MIC-RTSD Conference, an employee of the Chinese company United Imaging Healthcare (UIH)—which had been contracted by the U.S. university receiving $15.5 million in NIH funding—presented a slide describing the features of an integrated circuit using neighboring data exchange, a patented feature of Crosetto’s 3D-Flow architecture. This evidence is documented in Slide 86 of Crosetto’s conference presentation [13].

Further confirmation came during a seminar on 19 November 2019, at UIH’s headquarters in Shanghai, where Crosetto had been invited to present his invention to UIH’s leadership and engineers. During that session, UIH personnel explicitly acknowledged that they had adopted Crosetto’s neighboring data exchange technique in their ASIC (Application-Specific Integrated Circuit) designs.

Despite this, the same key feature was later attributed to UIH’s own work by Yang Lyu, who presented it at the 2023 IEEE-NSS-MIC-RTSD Conference without acknowledging Crosetto as the original inventor.

14.5. Anonymous Reviewers Continue to Suppress Science Without Accountability

Crosetto has encountered persistent, systemic obstacles in the scientific peer-review process—particularly involving anonymous reviewers who deny publication of his work without scientific justification and with no accountability (Proof supporting this statement are available upon request).

Pattern of Obstruction

For many years, except 2024, when all six of Crosetto’s submissions were accepted by IEEE, his papers were consistently suppressed under the following recurring conditions:

• Reviewers failed to provide scientific counterarguments, or gave superficial or unsubstantiated reasons for not accepting the paper.
• In many cases, no reviewer feedback was provided at all, despite written promises to authors.
• Final decisions were signed by conveners, who later transferred full responsibility to anonymous reviewers, refusing to override their decision—even when the flaws in the review were conclusively demonstrated. (Proof supporting this statement are available upon request).
  
  

Two Typical Scenarios:

a) No Feedback Is Provided

• Crosetto requests either feedback or the names of the reviewers so he can address potential misunderstandings directly.
• The convener promises to provide this information but never follows through, effectively shielding the reviewers from scrutiny.
  
  

b) Feedback Is Provided but Scientifically Flawed

• Crosetto rebuts the anonymous reviewer’s comments in detail, demonstrating scientific inaccuracies or misunderstanding of basic principles.
• The convener admits Crosetto’s rebuttal is valid, but claims he is powerless to overrule the anonymous review decision. (Proof supporting this statement are available upon request).
  
  

This rigged, non-transparent peer-review system undermines the scientific method. It functions as a gatekeeping mechanism to protect the status quo, especially for projects competing for large-scale funding—like the $2 trillion in annual global R&D expenditures. It enables entrenched reviewers and institutions to:

• Suppress innovation
• Avoid open comparison with alternative approaches
• Continue to receive funding despite poor results or inefficiencies
  
  

In short, it creates a closed-loop of unaccountable control, operating outside the principles of scientific integrity, reproducibility, and merit-based review.

14.6. Challenging the Rigged Peer-Review Process: Crosetto’s 2025 Appeals for Transparency at IEEE-NSS-MIC-RTSD Conference in Japan

Despite the long-standing suppression of his scientifically validated 3D-Flow innovation, Italian-American scientist Dario Crosetto continues to challenge the opaque peer-review process through documented efforts to demand accountability and transparency from scientific institutions.

Immediate Response to 2025 Notification Blocking Crosetto’s work

As soon as Crosetto received the notification on 3 July 2025 that his two papers were not accepted and therefore his innovations would be blocked from being presented and compared with other approaches at the upcoming IEEE-NSS-MIC-RTSD Conference in Yokohama, Japan, he took swift action to ensure that the decision was backed by scientific reasoning, not politics or prejudice.

The email from the conference conveners included the statement:

‘If you would like detailed feedback regarding why your submission was not accepted, please respond to this message.’

Crosetto immediately responded, requesting the promised reviewer feedback to understand and clarify any misunderstandings or technical misinterpretations, despite several inquiries as reported in Section 14.1.7.

As of this writing, nearly two months later, no feedback or justification has been received.

This silence exemplifies the lack of transparency and due process that has plagued the review of Crosetto’s work for decades.

Summary

The terms suppression, waste, plagiarism, copying, and corruption are fully justified based on the following:

• Decades of documented suppression and silencing without scientific refutation.
• Copying and plagiarism of Crosetto’s concepts without acknowledgment.
• Massive public funding ($4 billion past, $12 billion future) spent on demonstrably inferior technologies which fails to meet LHC and HL-LHC requirements.
• Deliberate omission of references to Crosetto’s peer-reviewed work, even when closely related concepts were discussed or implemented.
• Systematic exclusion from scientific dialogue despite strong evidence supporting the superior scientific and economic value of the 3D-Flow and 3D-CBS inventions.
  
  

The use of these words is not rhetorical—it is evidence-based, supported by verifiable documents, timelines, and technical data. If scientific institutions are to restore public trust and fulfill their missions, they must urgently address such patterns with accountability, transparency, and integrity.

15. Public Appeal to Japanese Scientific Leadership and Formal Appeal to IEEE Global Leadership

15.1. Public Appeal to Japanese Scientific Leadership

Given that the 2025 IEEE conference is hosted for the first time (physically) in Japan—a nation esteemed for a rich scientific tradition and strong principles of rigor and ethics—Crosetto issued a public appeal to Japanese scientific leaders:

‘Will the esteemed scientists of Japan bear the responsibility of hindering and suppressing genuine innovation and progress, or will they uphold the principles of transparency, evidence, and scientific integrity?’

This message was circulated through an open letter titled ‘Appeal to Japanese Scientific Leadership’, published here [33].

15.2. Formal Appeal to IEEE Global Leadership

Given the long-term pattern of blocking the presentation, discussion and comparison of scientific work without scientific refutation, Crosetto also escalated the issue to global leadership within the IEEE:

IEEE represents over 480,000 members worldwide, all of whom, upon joining, accepted a professional duty to uphold the IEEE Code of Conduct and Ethics [8] and the standards of scientific integrity. Suppression of an innovation that has not been scientifically refuted, but repeatedly ignored by anonymous reviewers, constitutes a serious breach of these principles.

Crosetto’s open letter urges IEEE Presidents, Editors-in-Chief, and conveners to ask publicly:

• Can any reviewer, or any CERN designer, present scientific calculations or evidence that substantially refute Crosetto’s claims?
• If not, is it ethical to continue to block, suppress, or ignore those claims? (see letter at [33]).
  
  

16. A Reasonable Proposal: Reallocate 0.00000067 of R&D to Experimentally Validate the 3D-CBS

As Crosetto has documented extensively, over $30 trillion has been spent globally on research and development since his 3D-Flow and 3D-CBS inventions were introduced.

Crosetto now proposes a modest but impactful investment: as the inventor, allocate him just 0.00000067 of that amount to fund the construction of two 3D-CBS devices so he can test them on a specific group or geographic population, as outlined in Section 12.1, and quantify experimentally the number of premature cancer deaths that the 3D-CBS can save.

This would provide experimental, population-based proof that the 3D-CBS can halve premature cancer deaths and related costs (or whatever number will result from the test), offering a clear, data-driven path forward for global health.

By contrast, continuing to fund the flawed and energy-intensive FPGA-Based Level-1 Triggers—as seen in the CMS and ATLAS upgrades—will waste billions more without advancing the science or saving lives.

17. Taxpayers and Cancer Patients Are Paying the Price for Suppressed Transparency and Accountability: A Call for Action

The failure to implement transparency, dialogue, and cooperation in scientific research at CERN has caused tangible harm to both taxpayers and cancer patients in Europe, the United States, and around the world.

Taxpayers fund these research, while cancer patients depend on this research to deliver advancements in science and life-saving innovations—not to perpetuate the suppression of proven, cost-effective technologies like the 3D-Flow and 3D-CBS systems, which could reduce public spending and prevent countless premature deaths.

17.1. CERN Must Be Held Accountable

CERN receives over $2.5 billion annually in taxpayer funding—predominantly from European countries, followed by the United States and other non-member states. Yet, these funds have supported projects such as the FPGA-based Level-1 Trigger systems, which have been proven inefficient, while more effective solutions—like Crosetto’s inventions—have been systematically ignored and suppressed without scientific rebuttal.

U.S. Contributions to CERN

U.S. taxpayers have invested heavily in CERN, including:

• $531 million initial contribution to the LHC infrastructure (per original U.S.-CERN agreement)
• $250 million from the Department of Energy (DOE)
• $81 million from the National Science Foundation (NSF) for CMS and ATLAS experiments
  
  

Each year, U.S. taxpayers continue to cover hundreds of millions in computing, hardware, and personnel costs associated with CERN operations and experiments.

European Contributions to CERN

Annual national contributions include:

• €258 million from Germany
• €185 million from France
• €164 million from the UK
• €120 million from Italy
• Comparable contributions, proportional to GDP, from all 24 CERN member States.
  
  

Horizon Europe and IEEE Projects

Many projects presented annually at IEEE-NSS-MIC-RTSD conferences receive public funding through Horizon Europe, which is allocating €95.5 billion from 2021 to 2027 for these and other projects across various fields.

These figures highlight how public money is being spent. Citizens and elected representatives deserve to know whether their money is going toward the most scientifically effective, life-saving solutions.

17.2. The true answer to the questions posed in Section 4.1 does not come from the opinions of millions of scientists but from the results of simulation and experimentation

The answer to the two questions is grounded in evidence not consensus:

a) Is CERN reducing the cost (the number of HL-LHC operating days at $4 million/day) to find new particles with a 3D-Flow Level-1 system executing filtering algorithms with over 8,000 operations per dataset, or with the CERN FPGA-Based Trigger executing filtering algorithms with approximately 66 operations per dataset?

b) Is there a higher probability of saving lives with the 3D-CBS which can detect anomalous biophysiological processes—including cancer at ~100 cancer cells—or with CT, MRI, PET, and mammography that can only detect cancer after it has grown to over1,000,000 cells (~1 mm)?

The answer does not come from the opinions of influential scientists among the >480,000 IEEE members or the >14,000 CERN scientists involved in LHC experiments; it lies in the results from simulations and experiments.

The answer to the first question regarding HL-LHC experiments comes from simulation:

a) HL-LHC physics question—evidence-based answer.
Crosetto’s simulations show that the 3D-Flow Level-1 Trigger can execute >8,000 operations on each dataset arriving every 25 ns. For the CERN FPGA-Based Level-1 Trigger, Xilinx FPGA simulations would determine how many operations can be performed on each dataset arriving every 25 ns, but that number has never been provided; and over two decades of experimental results have proved to be inadequate and ultimately failed.

• LHC operating cost is $2.5 million/day.
  The inefficiency of the CERN FPGA-Based Level-1 Trigger has cost taxpayers >$4 billion (see Section 8). Further proof of this failure is that only 40 Higgs boson-like events were detected out of 100,000 generated by the LHC from 2010 to 2011. This outcome was announced on 4 July 2012, and these 40 events were likely detected by chance, which is supported by the need to build several versions of the FPGA systems, which all failed.
• HL-LHC operating cost is $4 million/day.
  The new CERN FPGA-Based Level-1 Trigger—~20 trillion transistors, ~650 kW, ~66 operations per dataset—is destined to fail like the previous system, wasting >$12 billion over the next decade (see Section 9.1.3 [31]).

b) Question on the Medical Application—evidence-based answer.
The answer is to fund Crosetto—the 3D-CBS inventor, not copycat teams—to build two devices and conduct an experimental test on at least 75% of a defined population, to demonstrate its cost-effectiveness for early detection across multiple diseases, and its potential to halve premature cancer deaths and costs.

Context on costs/benefits:

• Global cost of cancer: ~$1.5 trillion/year; >10 million deaths/year, and increasing.

Instead of funding the inventor, taxpayer funds went to influential scientists who were well-connected to the annual $2 trillion R&D budget, as highlighted by Ioannidis in an October 2018 Scientific American [11]. Ioannidis also stated that ‘Funding is largely concentrated in the hands of a few investigators... not necessarily genuine superstars.’

In fact, none of the scientists who received a grant of $15.5 million from the NIH in 2015—fifteen years after Crosetto's invention—had any experience or publications in particle detection, a field that is essential for improving PET technology.

Crosetto, by contrast, was a recognized world-leading expert in this field (see Section 6.2) with years of experience on multi-million and multi-billion-dollar experiments at major global research laboratories.

The copycat team that received the $15.5 million grant, along with several others, lacked the technical capability to implement the system themselves, so they subcontracted a Chinese company to copy Crosetto’s invention.

The resulting device, known as EXPLORER, is less efficient and costs approximately six times more than the 3D-CBS (see slide 70 of [13]) and the price of an exam is $5,000-$9,500 (see UCDAVIS [⁵⁸]). After six years of EXPLORER use, there has been no demonstrated reduction in cancer deaths in a specific territory, as Crosetto proposed to measure (see Table III, pp. 95-98 of [57]).

What adequate funding could deliver now.

With less than the €21 million commercial price of one EXPLORER device sold in May 2024 in Italy (Slide 70 of [13]), or 0.00000067 of the $30 trillion already spent on R&D since Crosetto’s inventions, the inventor could build two 3D-CBS prototypes that would have a commercial cost of ~€3.5 million, based on €2 million in industry-quoted component costs.

The screening test—capable of detecting tumors at ~100 cancer cells (long before they grow to ~1 mm ≈ 1,000,000 cells detectable by CT/MRI/mammography), and requiring lower radiation than a pilot receives in one month—would cost ~€200, as detailed on pp. 5-6 of [4].

Conclusion.

After 25 years, the inventor should be provided with the resources to experimentally test his invention, which has the potential to halve premature cancer deaths and save millions of lives and billions of euros.

By unlocking these medical applications, we can save countless lives, significantly reduce the global financial burden of cancer care, and ensure fewer families lose loved ones too soon.

Honesty; the humility to accept experimental failure; scientific integrity; adherence to the codes of conduct and ethics that scientists pledge to uphold; and openness to dialogue and cooperation in understanding and respecting nature’s laws—these ensure transparent, reliable progress, benefit taxpayers and patients alike, foster public trust, and save lives.

When people who once opposed or mishandled the issue choose openness, they can articulate what they believe best serves science and humanity, acknowledge mistakes, and collaborate on remedies. Such respectful truth-seeking toward former counterparts restores public trust and confidence.

We need an open, public dialogue between the 3D-Flow inventor and all relevant institutions, with CERN and IEEE taking a leading role, to uncover the scientific truth for the benefit of humanity.

17.3. What You Can Do: Take Action

a) Contact Your Representatives

Make your voice heard. Urge action from officials entrusted with funding and guiding scientific research:

In the United States:

• U.S. citizens can write to their representatives and demand oversight of CERN funding, as well as a public scientific comparison between CERN's and Crosetto’s systems. You can find their address at this link [59].
• Contact Texas Secretary of State Jane Nelson, at secretary@sos.texas.gov (or apierce@sos.texas.gov). She played a key role in securing $6 billion in taxpayer funding for cancer eradication through CPRIT (the Cancer Prevention and Research Institute of Texas), as affirmed in her video [60] and recognized by an award she received from the American Cancer Society.
  
  Crosetto has been in contact with Texas Senator Jane Nelson—now Texas Secretary of State—for more than two decades. In 2000, when he gave her one of the first copies of his 3D-CBS book [7], she expressed her intention to fight cancer with State funding, promising to ensure that he could present his 3D-CBS invention to the scientists responsible for awarding projects with the funds she would secure. Indeed, in 2009, Nelson was instrumental in the approval of the first $3 billion dedicated to eradicating cancer.
  
  Crosetto submitted his 3D-CBS project but it was not funded by the anonymous reviewers, and he was not given the opportunity to answer their questions in a public, face-to-face meeting. These may have been the same anonymous reviewers who suppressed his presentations at IEEE conferences, journal articles, and funding from other government agencies that appoint the same pool of international reviewers. Proofs supporting this statement is available upon request.
  
  The recent suppression of the two 2-page articles at the 2025 IEEE-NSS-MIC-RTSD Conference in Yokohama, Japan, without providing any scientific counterarguments, is just a continuation of this practice.
  
  Beyond science, Crosetto and Nelson shared an interest in cultural exchange, which fostered continuous contact between them since 1997.
  
  This connection began after Crosetto’s experience spending a year in the U.S. at age 17, when he was awarded an American Field Service scholarship.
  
  When he returned to the U.S. at age 40, he embraced President Eisenhower's vision of promoting peace through mutual respect and dialogue, which led to the creation of Sister Cities International in 1956. Inspired by this, Crosetto organized a cultural exchange program for a decade, providing a ten-day experience for over 100 Texans and Italians from his native town.
  
  Senator Nelson and her family and staff also participated in this program.
  
  On 5 March 1997, Senator Nelson signed Texas State Resolution S.R. No. 284 [61] honoring Crosetto’s mother for hosting her son’s Texan friends in her home in Monasterolo di Savigliano, Italy. Later, in 2018, Monasterolo di Savigliano conferred Honorary Citizenship to Texas Senator Jane Nelson [62].
  
  Over the years, Nelson was able to double CPRIT’s budget from $3 billion to $6 billion for cancer research. In light of the scientific evidence presented in this document—which demonstrates that Crosetto’s inventions have been valuable for three decades and remain superior to any other approach today, with the potential to advance science, reduce costs, and significantly lower cancer mortality—Texas Secretary of State Nelson, because of her commitment, is well-positioned to organize a public meeting between Crosetto and CPRIT scientists, who have already allocated most of the $6 billion to cancer research projects.
  
  Given this history and these circumstances, writing to the Texas Secretary of State to express your support for transparency in science and the need for public scientific procedures may encourage all parties to pursue science for the benefit of cancer patients. This public meeting between Crosetto and CPRIT scientists would allow the scientific truth to emerge.

In Europe:

• Write to your national parliamentarians: Find their addresses at this link [63].
• Write to EU representatives: The full list of all 720 Members of the European Parliament (MEPs) is available at this link [64].
  
  

A template letter addressed ‘To Whom It May Concern’ is downloadable here [6]. Send it to your representative and/or to the person listed above who holds a position of responsibility for advancements in science for the benefit of humanity and who is committed to eradicate cancer. Send also a copy of your letter to jcolburn@crosettofoundation.org, so that the Foundation can forward it to relevant funding agencies and record your support for transparency in science.

b) Donate to the Crosetto Foundation

Help us build two 3D-CBS prototypes and carry out an experimental trial to demonstrate that we can cut premature cancer deaths and related costs in half.

Donate online: https://crosettofoundation.org/donate-now/
Donate via Zelle: donate@crosettofoundation.org

The Crosetto Foundation has received GuideStar’s Gold Seal for Transparency for eight consecutive years.

Why Your Donation Matters

Your contribution empowers transparency in science and supports the acceleration of life-saving innovations.

A donation is not just financial support—it is the driving force that enables broader PR campaigns, reaching more journalists, parliamentarians, and citizens who deserve the truth.

Without donations, this vital message [65] risks being silenced. With your support, we can expand awareness through more media outlets—many of which have already exposed harmful scientific inconsistencies (see the partial list of the outlets that have published it [66])—making these issues impossible to ignore and thereby help save lives.

Please consider making a donation today—because the truth must be heard, and together we can ensure it reaches the world.

c) Spread the Word

• Share this information with your networks.
• Forward it to scientists, journalists, policymakers, and advocacy groups.
• Use social media to call for a public, evidence-based comparison of CERN’s and Crosetto’s technologies.
  
  

Contact

Jennifer Colburn

Crosetto Foundation for the Reduction of Cancer Deaths
DeSoto, Texas
jcolburn@crosettofoundation.org
https://crosettofoundation.org/

Blog: https://crosettofoundation.org/blog/
Facebook: https://www.facebook.com/profile.php?id=100064846172129
Instagram: https://www.instagram.com/dariocrosetto/
Linkedin: https://www.linkedin.com/in/dario-crosetto-4b69a1227/
X: https://x.com/crosettodario

Key References

[10] The official report from the Fermilab public scientific review on December 14, 1993 affirmed the 3D-Flow invention's feasibility and found no major flaws. (https://bit.ly/41i4ace).

[20] Crosetto, NIM A (1999), 45 pp. Peer-reviewed article reporting the successful results of the feasibility study of the 3D-Flow. (https://bit.ly/45Mw6pM).

[13] A 102-slide, 2-hour presentation by Crosetto at the IEEE-NSS-RTSD conference on October 31, 2024. The presentation compares the ATLAS/CMS 1992 logic and the 3D-Flow paradigm, including operational examples (https://bit.ly/45uaZtz).

[2] A two-page technical comparison from 2025 that summarizes the performance, power consumption, and costs of the 3D-Flow versus the FPGA Level-1 Trigger systems. (https://bit.ly/45K6BFz).

[3] A two-page brief from 2025 about the modular single-board 3D-Flow Level-1 Trigger, detailing its form factors and applications in physics and PET applications. (https://bit.ly/41hKwgk),

[21] An educational video showing the bypass switch/register analogy to illustrate the conceptual invention of the 3D-Flow architecture at minute 4:28 (https://bit.ly/4oN7Xbx), (https://www.youtube.com/watch?v=HwMnHRuWo4o).

[8] The IEEE Codes of Conduct and Codes of Ethics, which serve as a basis for governance and transparency requests to scientists. Code Conduct (https://www.ieee.org/about/corporate/governance/code-of-conduct) and Code of Ethics (https://www.ieee.org/about/corporate/governance/p7-8).

[31] An analysis of budget and waste, including CERN's cost ranges, operating-day costs, and daily expenditure estimates for the LHC/HL-LHC. (https://bit.ly/45XONYW),

Callouts:

1. “Only transparency, accountability, and cooperation through open dialogue can save CERN”
2. “To receive benefits from your taxpayer money, demand your representatives to require a public meeting between inventor Crosetto and CERN designers”
3. “No favoritism on $6B to eradicate cancer, demand Nelson organize a public meeting between inventor Crosetto and CPRIT and let science truth emerge”
4. “Donate $10+ to help fund outreach demanding a public comparison of Crosetto’s 3D-Flow & 3D-CBS inventions to CERN’s costly, ineffective approach”
5. “3D-Flow using 6 kW executes >8,000 operations, meets 8B events/sec CERN HL-LHC needs until 2042, while CERN-FPGA ~66 operations at 650 kW does not”
6. “Same 3D-Flow electronics filters valuable data from radiation detecting new particles at CERN and detecting tumor markers with 3D-CBS to save lives”
7. “>$4B wasted by CERN to date, and >$12B more will be wasted in the next decade unless the 20 June 2025 CERN Council funding approval is halted”
8. “>39M lives lost prematurely to cancer, with millions more projected—despite 3D-CBS, a cost-effective early detection invention available since 2000”
9. “Your contribution empowers transparency in science and supports the acceleration of life-saving innovations”
10. “Crosetto’s 3D-CBS can detect tumors with <100 cancer cells at €200, 2-min safe whole-body test with the potential to save >260 lives/device/year”
    
    

Additional References

The complete list of references follows, providing full citations for all sources supporting the statements, calculations, and claims in this document.

[1] Donate: Support the Crosetto Foundation online (https://crosettofoundation.org/donate-now/) or if you have Zelle app on your phone or computer, send your donation directly to donate@crosettofoundation.org.

[2] A two-page technical comparison from 2025 that summarizes the performance, power consumption, and costs of the 3D-Flow versus the FPGA Level-1 Trigger systems. (https://bit.ly/45K6BFz) (https://drive.google.com/file/d/1BLB6z0r3W-RYl4jVgv0k8Kdtqs-kz99x/view?usp=sharing).

[3] A two-page brief from 2025 about the modular single-board 3D-Flow Level-1 Trigger, detailing its form factors and applications in physics and PET applications. Details on form factors; applications in physics and PET. (https://bit.ly/41hKwgk), (https://drive.google.com/file/d/1Ceb2NWaY9TU4_-oGa1olB5VG00r7mLSI/view?usp=sharing).

[4] A roadmap table and supporting data estimating the lives saved and projected revenues over 30 years from using the 3D-CBS device. (https://bit.ly/47eqiIh) (https://drive.google.com/file/d/1qYC3vzGm2CO37ZVsCUM05Op4Je_zz_GF/view?usp=sharing).

[5] Links to the webpages of representatives in Europe and the United States (https://bit.ly/4mqfTO5), (https://drive.google.com/file/d/1zSgLZin69ZaSFcuzc_HjITkbQ8iTe1Pa/view?usp=sharing).

[6] A template letter designed for sending to parliamentarians (https://bit.ly/4fHe7FP) (https://drive.google.com/file/d/1zSgLZin69ZaSFcuzc_HjITkbQ8iTe1Pa/view?usp=sharing), (https://bit.ly/4lBO6ZR), (https://drive.google.com/file/d/1MXbTWsTX9D4TslIKoYHaIigf87Jzqlak/view?usp=sharing)

[7] A description of Crosetto's 3D Complete Body Screening (3D-CBS) invention from the year 2000. It is detailed in the book, ‘400+ times improved PET efficiency for lower-dose radiation, lower-cost cancer screening’ (https://bit.ly/45U2Wqv), ISBN 0-9702897-0-7, (https://drive.google.com/file/d/0BxWfo2ViJ6r5WVFVWnJteENqMWc/view?usp=sharing), which is also catalogued with the U.S. Library of Congress, Catalog-in-Publication Data Card Number: 00-191510

[8] The IEEE Codes of Conduct and Codes of Ethics, which serve as a basis for governance and transparency requests to scientists. Code Conduct (https://www.ieee.org/about/corporate/governance/code-of-conduct) and Code of Ethics (https://www.ieee.org/about/corporate/governance/p7-8).

[9] A 15-page email titled ‘Only Transparency and Accountability can Save CERN,’ sent on 30 June 2025 to 720 European parliamentarians (English PDF: https://bit.ly/3TMnDNI HTML: https://bit.ly/46iPCMA), (https://drive.google.com/file/d/1BugJdzkbSj_LODiEmuiQqZJx349QxNqe/view?usp=sharing).

[10] The official report from the Fermilab public scientific review on December 14, 1993. The committee recognized the 3D-Flow invention as a breakthrough that allows a programmable Level-2 pattern recognition algorithm to be executed at Level-1 on datasets arriving every 25 nanoseconds without data loss. The report affirmed the invention's feasibility and found no major flaws. (https://bit.ly/41i4ace), (https://drive.google.com/file/d/0BxWfo2ViJ6r5amx4ZlN2OTJqMmM/view?usp=sharing&resourcekey=0-oYLJQocSy9BOTGb68vsu9A).

[11] An article titled ‘HOW TO FIX SCIENCE’ by Ioannidis PA, published in the October 2018 issue of Scientific American. (https://bit.ly/3KWqoWD), (https://www.scientificamerican.com/article/whats-wrong-with-science-and-how-to-fix-it/?fbclid=IwAR16ApljYDGnNAIOb_lK-wUFcm61Uix05NwMidY_-kcPUXnejGaxdNuLGO0). It was later translated and published in the December 2018 issue of the Italian magazine ‘Le Scienze’.

[12] A publication by Crosetto DB. on the invention of the 3D-Flow, titled ‘3D-Flow Processor for a Programmable Level-1 Trigger,’ which appeared in the proceedings of the Computing in High Energy Physics conference (CHEP92) pp. 803-806, in Annecy, France.

[13] A 102-slide, 2-hour presentation by Crosetto at the IEEE-NSS-RTSD conference on October 31, 2024. The presentation compares the ATLAS/CMS 1992 logic and the 3D-Flow paradigm, including operational examples (https://bit.ly/45uaZtz), (https://drive.google.com/file/d/1X82XVQbOgHjeHF8OpkIJo-Cfz8AuhMec/view?usp=sharing).

[14] A lecture given by Crosetto DB. at the CERN School of Computing in 1990. (https://bit.ly/3UIKEBP) (https://drive.google.com/file/d/0BxWfo2ViJ6r5Z3Z4bHFLRWU5bDQ/view?usp=sharing&resourcekey=0-HjIXpAMAgWc2mKakRobqsA).

[15] A publication by Crosetto DB. on the invention of the 3D-Flow, titled ‘Calorimeter Programmable Level-1 Trigger,’ which was included in the proceedings of the III International Conference on Calorimetry in High Energy Physics in Corpus Christi, Sept. 29-Oct. 2, 1992. SSCL-Preprint 180, pp. 553-566.

[16] A publication by Crosetto DB. on the invention of the 3D-Flow, titled ‘3D-Flow Processor for a Programmable Level-1 Trigger,’ which appeared in the proceedings of the IEEE Nuclear Science Symposium (NSS) and Medical Imaging Conference (MIC) in Orlando, Florida, October 1992, pp. 25-31.

[17] A collection of letters and testimonials by leading experts in the field that endorse and praise Crosetto's inventions and research (https://bit.ly/3HHbOWS), (https://drive.google.com/file/d/0BxWfo2ViJ6r5MHBteWhGX1hkS0U/view?usp=sharing&resourcekey=0-00Gwu97PoU8eVNgM19-YyQ) (https://crosettofoundation.org/testimonials/)

[18] Two letters from S. Turrini, the inventor of the first 400 MHz Microprocessor, endorsing Crosetto’s invention (https://bit.ly/40voRkm), (https://drive.google.com/file/d/0BxWfo2ViJ6r5ZU1fSkluN0p6QjA/view?usp=sharing&resourcekey=0-tYia2vkryxewcl0UdKGm9A),.

[19] Three letters from J. Merryman, the inventor of the pocket calculator, endorsing Crosetto’s inventions (https://bit.ly/4okyEnM), (https://drive.google.com/file/d/0BxWfo2ViJ6r5THl2VjNxdTQ2aXc/view?usp=sharing&resourcekey=0-J3hgVDm3pCSujdPY423A0w),

[20] Crosetto, NIM A (1999), 45 pp. Peer-reviewed article published on Nuclear Instruments and Methods in Physics Research Sec. A, vol. 436, (1999) pp.341-385. The article is reporting the successful results of the feasibility study from system level to gate and transistor level of Crosetto’s 3D-Flow Architecture that he performed with a $1 million grant received from DOE. (https://bit.ly/45Mw6pM), (https://drive.google.com/file/d/0BxWfo2ViJ6r5NlVSWHhoTl9jZXc/view?usp=sharing&resourcekey=0-NPvfp2wWcJrD0ins-cx4Cw).

[21] An educational video showing the bypass switch/register analogy to illustrate the conceptual invention of the 3D-Flow. A classroom demonstration of this concept is shown at minute 4:28 (https://bit.ly/4oN7Xbx), (https://www.youtube.com/watch?v=HwMnHRuWo4o).

[22] The U.S. Department of Energy (DOE) awarded a $1 million grant to Crosetto to conduct a feasibility study of his 3D-Flow invention (https://bit.ly/3Pszu1y), (https://drive.google.com/file/d/0BxWfo2ViJ6r5anZtOG1rY250dEk/view?usp=sharing&resourcekey=0-GhQN7cqFP2z7kI9XLfrRlQ)

[23] Crosetto DB article ‘The 3-D Complete Body Screening (3D-CBS) Features and Implementation’ Conf. Rec. IEEE-NSS-MIC, Portland, Oregon, IEEE 2003-M7-129. (https://bit.ly/43Rlk0s), (https://drive.google.com/file/d/0BxWfo2ViJ6r5RDQ2UURPeHBIYnc/view?usp=sharing&resourcekey=0-6MP6-KUT13Y2b8rSCqFtjQ),

[24] A 274-page proposal by Crosetto DB. detailing the 3D-Flow OPRA and 3D-CBS projects. The proposal was submitted to the U.S. Department of Energy on 22 December 2015, after Crosetto was solicited by the Director of the Office of High Energy Physics of the Office of Science of DOE, to design a universal programmable Level-1 Trigger that would meet the requirements of all LHC experiments. (https://bit.ly/4myTwpY) (https://drive.google.com/file/d/0BxWfo2ViJ6r5MlpkbUpjbEIybUk/view?usp=sharing&resourcekey=0-8RpD1TC0IGKAEZ9L5-DrJw)

[25] An 82-page article by Crosetto DB. from April 14, 2025, which documents and details the content of his 2-hour, 102-slide presentation at the IEEE-NSS-MIC-RTSD conference in Tampa, Florida on 31 October 2024 (https://bit.ly/4oNUOyT) (https://drive.google.com/file/d/1JyAw9Ba9DWRjlKwsSoz8j4KEPGDoiDwR/view?usp=sharing)

[26] A book from 2000, co-authored by Crosetto DB., and teachers and students from a Montessori school, titled ‘Understanding a new idea for a Cancer Screening device. Written in collaboration with middle school students and their teachers from St. Alcuin Montessori school in Dallas, Texas, the book explains how the 3D-Flow architecture's advantages enable the efficient and cost-effective detection of tumor markers for early cancer screening.

[27] The CERN website describes the features and implementation of the CMS FPGA-Based Level-1 Trigger (https://cms.cern/news/real-time-analysis-cms-level-1-trigger) (https://bit.ly/47leuDQ), (https://drive.google.com/file/d/12QLLNHTsl8MeC9SmohrEVc6F-LcEAClu/view?usp=sharing)

[28] The 383-page CERN official document, CMS-TDR-021, titled ‘The Phase-2 Upgrade of the CMS Level-1 Trigger Technical Design Report,’ dated 10 March 2020 (https://cds.cern.ch/record/2714892/files/CMS-TDR-021.pdf)

[29] A video demonstrating the power consumption of a water-cooled FPGA Virtex Ultrascale VU13P, which is 263 Watts (https://bit.ly/4mYKp1J), (video https://www.youtube.com/watch?v=qm1zWlWiHs8)

[30] The 378-page CERN official document, CERN-CMS-TDR-022, titled ‘The Phase-2 Upgrade of the CMS Data Acquisition and High-level Trigger Technical Design Report,’ dated 17 June 2021, (https://cds.cern.ch/record/2759072/files/CMS-TDR-022.pdf)

[31] An analysis of budget and waste, including CERN's cost ranges, operating-day costs, and daily expenditure estimates for the LHC/HL-LHC. These figures are consolidated in Section 9.1.3 of this document. (https://bit.ly/45XONYW), (https://drive.google.com/file/d/1vhlFDBXukvzZIAq93JRohgOOwCAv595x/view?usp=sharing).

[32] The CERN document, CMS CR-2016/121, titled ‘SWATCH Common software for controlling and monitoring the upgraded CMS Level-1 trigger,’ which states that the upgraded Level-1 Trigger was ineffective and was subsequently dismissed in 2016. (https://cds.cern.ch/record/2194548/files/CR2016_121.pdf)

[33] A letter from Crosetto DB., dated July 16, 2025, sent to IEEE conveners. The letter concerns the alleged suppression of his two presentations and article by anonymous reviewers at the 2025 IEEE-NSS-MIC-RTSD Conference in Yokohama, Japan. A copy of this letter was also sent to leaders in the field. (https://bit.ly/4lHiJ0b) (https://drive.google.com/file/d/1gj0tuWBtJcElYAQY_g-1NJ2R51Zk2IPY/view?usp=sharing).

[34] A letter from Crosetto DB. dated 19 June 2025, titled ‘A Call for Scientific Transparency and Accountability,’ sent to leaders in the scientific field. (https://bit.ly/4naZUEm), (https://drive.google.com/file/d/18pwKpfjey5AlM8aWZflzlDAI8iK3jkAQ/view?usp=sharing).

[35] A presentation by Crosetto DB. and others, titled ‘Progress in the Domain of Physics Applications in Life Science with an invention for Substantial Reduction of Premature Cancer Deaths: The Need for a Paradigm Change in Oncology Research,’ given at the CERN Workshop ‘Physics for Health’ on 2 February 2010. (https://bit.ly/47crLii), (https://drive.google.com/file/d/0BxWfo2ViJ6r5djJtLUlrMW90UXc/view?usp=sharing&resourcekey=0-Sjh0HYRryYDNsSemReVQdg).

[36] A slide presented at the CERN auditorium on 21 May 2019, describing the WPET (Wearable PET) project. This project, which received funding from the CERN-ATTRACT Consortium and utilized EU taxpayer money, involves an impractical, absurd 350+ kg coat intended for 24-hour cancer screening. (http://bit.ly/2JWsxG2), (https://drive.google.com/file/d/1-CWKfAWi5sTOD2USvVFQOYie_6d-1IdT/view?usp=sharing).

[37] Crosetto DB., provided a paragraph-by-paragraph refutation of the article requesting funding for the €2 million WPET-Jacket project, but he never received a feedback from his review. (https://bit.ly/3iydDp3), (https://drive.google.com/file/d/1mHoX59_lklPHj95JCCpVPLUlsUYFDwjj/view?usp=sharing)

[38] A parliamentary question submitted to the European Parliament on June 21, 2019, by the Honorable Alessandro Panza. The question demanded accountability from CERN regarding its decision to fund the WPET project for cancer screening instead of the 3D-CBS project. (https://bit.ly/3HKjreL), (https://drive.google.com/file/d/1XwNqFk_2XU7Mjvw0tPFBtkzuiaX1g8jL/view?usp=sharing), (https://www.europarl.europa.eu/doceo/document/E-9-2021-003244_EN.html).

[39] Instead of stopping funding CERN-ATTRACT and requesting CERN accountability by organize a public meeting between the author of the WPET and 3D-CBS for cancer screening, the European Commission awarded an additional €28 million grant to the CERN-ATTRACT program https://cerneu.web.cern.ch/attract-unveils-projects-will-benefit-its-eu28-million-fund-innovation

[40] An interactive roadmap table that estimates the number of lives saved and the projected revenues over 30 years from using the 3D-CBS device: This interactive table can be used to create a roadmap for other projects to verify efficacy of drugs, devices, healthy style programs, and others. (http://bit.ly/2XI2OFz), (https://drive.google.com/file/d/1nAD6e4lbU-v7X91fA5yatn1YC8GdG_SO/view?usp=sharing).

[41] An open letter from Crosetto to the President of Italy and the public, dated 25 April 2025 (https://bit.ly/3QbTLt4), (https://drive.google.com/file/d/1-ei6Qf-gkg3NtlAy5RgUP1H3kcw_Fej6/view?usp=sharing)

[42] A BBC article reporting on Ereditato’s appeal for help in understanding the results of his measurements of neutrinos traveling faster than light (https://bit.ly/4ogjGPw), (https://www.bbc.com/news/science-environment-15017484).

[43] A response letter from Crosetto to Ereditato's appeal, explaining that Ereditato's experimental setup was flawed and could not provide an unambiguous result (https://bit.ly/4mYC7H3). (https://drive.google.com/file/d/0BxWfo2ViJ6r5RkFsOFIzdlpsR1k/view?usp=sharing&resourcekey=0-71AfuiuSj6qxdbjTCerd6w)

[44] A document detailing a discussion between Crosetto and a CERN scientist about the OPERA experiment's measurements on breaking the speed of light (https://bit.ly/45MdRkh), (https://drive.google.com/file/d/0BxWfo2ViJ6r5ajN2NVVLSXhyanM/view?usp=sharing&resourcekey=0-o0VMU4nMe8l2sH15dhmz8w).

[45] Proof that Crosetto designed, built, and tested hardware electronics in 2003 that were hundreds of times more accurate than the 2008 electronics used for the OPERA experiment to measure the claimed faster-than-light neutrinos. (https://bit.ly/4ogrHDU), (https://drive.google.com/file/d/0BxWfo2ViJ6r5cDJsdnRyN2lhRWc/view?usp=sharing&resourcekey=0--_7bsdhnPvvXnhL2Mp6lDQ).

[46] Crosetto's schematics and PCB layouts for electronics he designed and built, which have a 10 picosecond resolution and a 40 picosecond maximum skew across thousands of boards in many crates. (https://bit.ly/4l64nWP), (https://drive.google.com/file/d/0BxWfo2ViJ6r5Wl82SG0xSC1hakU/view?usp=sharing&resourcekey=0-pd-KaM-vdJmBKgVzHXsRDA).

[47] Untrue public statement claiming that the error in measuring neutrino speed was due to a faulty master GPS clock and a loose connection on the electronic board. (https://bit.ly/3UCn3T8), (https://en.wikipedia.org/wiki/2011_OPERA_faster-than-light_neutrino_anomaly).

[48] Crosetto, DB.: ‘A modular VME or IBM PC based data acquisition system for multi-modality PET/CT scanners of different sizes and detector types.’ Presented at the IEEE Nuclear Science Symposium and Medical Imaging Conference, Lyon, France, 2000, IEEE-2000-563. Short URL (https://bit.ly/3JRlRZZ), (https://drive.google.com/file/d/0BxWfo2ViJ6r5MTBoTVRucF9CREU/view?usp=sharing&resourcekey=0-2ofmkGvM39MMc-R3A8mQjw).

[49] Crosetto, DB.: ‘Real-time, programmable, digital signal-processing electronics for extracting the information from a detector module for multi-modality PET/SPECT/CT scanners.’ Presented at the IEEE Nuclear Science Symposium and Medical Imaging Conference, Lyon, France, 2000, IEEE-2000-567. Short URL ( https://bit.ly/4fZTzZC), Full URL (https://drive.google.com/file/d/0BxWfo2ViJ6r5d1NENTRkSUg2NVU/view?usp=sharing&resourcekey=0-HBFHiHO9nHghdaEHxZoaDQ)

[50] A 63-page open letter from Crosetto DB. to the Pontifical Academy of Sciences, dated 31 August 2023, and updated on 18 September 2023. The letter is titled ‘Opportunity to save over 5 million lives per year using new technology for early cancer detection.’ (https://bit.ly/3qii6Dv), (https://drive.google.com/file/d/1xV1n7xiOhzskDFAILUnypfrIonzuuo7o/view?usp=sharing).

[51] Crosetto DB.: ‘Over 39M lives needlessly lost from cancer in the past 23 years, and 69M more over the next 7 years because scientists’ goal for PET is to take beautiful pictures and crushed my invention to cost-effectively measure bio-physiology’. 2024 IEEE-NSS-MIC-RTSD Conf. N-29-05, (#2586), (https://bit.ly/3AbUghP), (https://drive.google.com/file/d/1xKUPBdaiGLuS7_3O7_Wia8A_EVN17KSs/view?usp=sharing).

[52] Email sent on 23 June 2025 to 720 European Parliamentarian and various news outlets (https://bit.ly/4era28b), (https://drive.google.com/file/d/1-QUEhAYNma3lpRhFY1tXc0_HZ8_Xz1WW/view?usp=sharing).

[53] A press release titled ‘Only Transparency and Accountability Can Save CERN,’ sent in English on 4 July 2025, to 720 parliamentarians and published by 441 news outlets (https://bit.ly/44cIbVQ) (https://www.globenewswire.com/news-release/2025/07/03/3109825/0/en/Only-Transparency-and-Accountability-Can-Save-CERN-Stop-Billions-in-Waste-Unlock-Life-Saving-Innovations.html)

[54] A press release sent in French on 4 July 2025, and published by 421 news outlets. (https://bit.ly/4lfjnTe), (https://www.globenewswire.com/news-release/2025/07/04/3110462/0/fr/Seule-la-transparence-et-la-responsabilit%C3%A9-peuvent-sauver-le-CERN-une-condition-essentielle-pour-mettre-fin-au-gaspillage-de-milliards-et-acc%C3%A9l%C3%A9rer-les-innovations-m%C3%A9dicales-vitale.html)

[55] A press release sent in German on 4 July 2025, and published by 487 news outlets. (https://bit.ly/3TTV0yb), (https://www.globenewswire.com/news-release/2025/07/04/3110384/0/de/Nur-Transparenz-und-Rechenschaftspflicht-k%C3%B6nnen-das-CERN-retten-Milliardenverschwendung-stoppen-lebensrettende-Innovationen-erm%C3%B6glichen.html).

[56] A press release sent in Italian on 4 July 2025, and published by fewer than ten news outlets. (https://bit.ly/4kpbDN0), (https://drive.google.com/file/d/1gS-BQ5YuTxSp9uMqSnds_YBa2cS8_YAN/view?usp=sharing)

[57] A 147-page article by Crosetto DB. on the 3D-CBS technology for measuring bio-physiology. The article was submitted on 6 July 2020 to the Journal of Medical Imaging (JMI) along with a request for JMI to withdraw a previous article by other authors that Crosetto claims was misleading researchers. The Journal of Medical Imaging excluded Crosetto's article from review without providing a scientific reason and did not withdraw the other article (http://bit.ly/2QdgdTx), (https://drive.google.com/file/d/1jcMBP43bPooy9t94ZxRdHOkFtaN6zsXZ/view?usp=sharing)

[58] A document detailing the cost of an exam using the EXPLORER device at UCDAVIS. (https://bit.ly/45ugUir) (https://drive.google.com/file/d/161ohRha5sJTvB0DLNkF0gHIDqBiIWtO1/view?usp=sharing)

[59] A link to find U.S. representatives. https://www.house.gov/representatives/find-your-representative

[60] A video of the Texas Secretary of State stating her commitment to eradicating cancer. (https://bit.ly/3HyiPt3), (https://www.youtube.com/watch?v=v7VJhz7easo).

[61] A Texas State Proclamation (S.R. No. 284) from 5 March 1997, which praises Crosetto’s mother in Monasterolo di Savigliano, Italy, for hosting his friends from Texas as part of his efforts to create a sister-city relationship with his native town (https://bit.ly/4mrXq3U), (https://drive.google.com/file/d/1qD4svUZvnMoKu41nxyA7k-D2WIlSt6k2/view?usp=sharing).

[62] A document showing that the town of Monasterolo di Savigliano conferred honorary citizenship on Texas Senator Jane Nelson. (https://bit.ly/470EaWp), (https://drive.google.com/file/d/1-xEfHJYFKRAdu_kQ4kctByGDHdj4qbPX/view?usp=sharing).

[63] A link to a list of the national parliamentarians of all European states: https://secure.ipex.eu/IPEXL-WEB/parliaments/list_parliaments

[64] A link to a list of the 720 members of the European Parliament. https://www.europarl.europa.eu/meps/en/full-list/all

[65] A link to this specific document (https://bit.ly/3UCW8XE), (https://drive.google.com/file/d/1ixCMjupsJIDdAhe7-RFIKiKtuKEVqqM1/view?usp=sharing)

[66] A list of thousands of news outlets that have published articles on the 3D-CBS and 3D-Flow over the past three months (https://bit.ly/3HtisQv), (https://drive.google.com/file/d/1H44Um48RhMhs1Mpv5nEQFMyie9XCSUCA/view?usp=sharing)

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