Scientific Integrity Concerns Raised Over CERN's $16 Billion Trigger System at International Conference

During the IEEE-NSS-MIC-RTSD 2025 Conference in Yokohama, where over 1,500 scientists gathered to discuss medical imaging and high-energy physics technologies, compelling evidence emerged questioning the scientific integrity and technical capability of CERN's newly constructed trigger system. The Crosetto Foundation for the Reduction of Cancer Deaths presented documentation showing that the 20-trillion-transistor CERN CMS FPGA-based Level-1 Trigger system, built for data selection at the 2026-2036 High-Luminosity Large Hadron Collider, appears fundamentally incapable of performing the required number of operations on data arriving every 25 nanoseconds to filter 8 billion events per second without data loss.

The significance of this revelation extends beyond theoretical physics, with more than $4 billion in taxpayer funds already spent and over $12 billion projected to be wasted in the next decade on a system that may not meet HL-LHC requirements. Despite multiple presentations by CERN representatives from the CMS and ATLAS collaborations, none could specify how many basic operations the FPGA system can execute per dataset or provide technical proof that the system can efficiently perform Level-2 trigger algorithms required at the HL-LHC at Level-1. Researchers claiming system capability failed to support these assertions with verifiable, reproducible calculations or simulation evidence.

This situation represents a substantial escalation from previous CERN controversies, including the AXIAL-PET project in 2010, the 2011 claim that neutrinos travel faster than light, and the 2018 WPET full-body wearable imaging coat weighing over 350 kg. While those missteps cost millions, the current FPGA Level-1 Trigger issue involves significantly greater scientific and economic consequences. The foundation has distributed technical documentation (https://bit.ly/437YX7H) to conference participants and is calling for immediate action from the European Parliament, national science funding agencies, and media organizations worldwide to freeze additional funding until scientific questions are resolved.

The foundation's outreach reaches over 800 million potential readers through more than 5,000 published articles and communications (https://bit.ly/3HtisQv), emphasizing the urgent need for public accountability. During the conference's first three days, over 1,200 copies of a two-page technical document were distributed, posing the central scientific question about whether sufficient evidence exists to dismiss the CMS-FPGA system as ineffective at filtering 8 billion events per second. The distribution generated supportive feedback from conference attendees, including encouragement to continue telling the truth about the technical limitations.

On the conference's fourth day, a formal request (https://bit.ly/4nJRsvc) was submitted to organizers and field leaders for a transparent technical workshop to compare the number of operations per dataset achievable by the CERN FPGA system versus the 3D-Flow system, along with comparing the cost per electronic channel of each architecture. The foundation has invited scientists supporting the current FPGA approach to defend their claims through open dialogue and simulation-based comparison, emphasizing that scientific progress depends on transparent evaluation of competing technologies.

The 3D-Flow architecture, recognized as a breakthrough in 1993, presents a proven cost-effective alternative that has demonstrated capability to perform either 2,400 operations per dataset at approximately $13 per channel or 9,600 operations per dataset at about $54 per channel when implemented on an ATCA board. Technical details of this system (https://bit.ly/4qKVar8) show it remains unchallenged in cost-effectiveness and performance for Level-1 real-time triggering applications. The ongoing controversy highlights the critical importance of scientific transparency and rigorous technical validation before committing substantial public resources to large-scale research infrastructure projects.