AI Advances in Particle Physics at CERN
CERN researchers have deployed cutting-edge AI and novel experimental techniques to achieve unprecedented progress in particle physics, including the search for rare Higgs decays and the manipulation of short-lived particles.
In a major leap for particle physics, CERN scientists have integrated advanced artificial intelligence (AI) systems and innovative experimental setups to push the boundaries of what can be observed and measured at the Large Hadron Collider (LHC). These efforts have led to significant milestones, such as setting the most stringent limits yet on the Higgs boson's decay into charm quarks and the first successful observation of double crystal channeling, both of which promise to illuminate new physics beyond the Standard Model.
Machine Learning Unlocks Rare Higgs Decays
The CMS experiment at CERN has leveraged sophisticated machine learning algorithms, including graph neural networks and transformer models, to tackle the formidable challenge of detecting Higgs boson decays into charm quarks—a process considered nearly impossible just a few years ago. By training on hundreds of millions of simulated particle collision events, the AI systems now identify charm jets with unprecedented precision and distinguish genuine Higgs events from background noise. This approach has resulted in a 35% improvement in the limits on the Higgs-charm interaction, marking a critical step toward understanding how the Higgs boson imparts mass to quarks and testing the very foundations of particle physics. Researchers anticipate that future LHC runs and further AI refinements could ultimately confirm these elusive decays, providing crucial insights into the Standard Model's validity and possible extensions.
Crystal Channeling and Novel Particle Manipulation
Simultaneously, CERN's TWOCRYST experiment has achieved the first successful observation of double crystal channeling, a technique that uses bent silicon crystals to steer and manipulate the trajectories of short-lived particles such as charm baryons. This method allows for the precise measurement of properties like magnetic and electric dipole moments, which are essential for probing fundamental questions about matter-antimatter asymmetry and dark matter. The experiment's initial results at 450 GeV have validated the concept, with researchers now preparing to scale up to higher energies. These advances open new avenues for fixed-target experiments and beam-control strategies at the LHC, potentially revealing physics phenomena that have so far eluded detection.
Controversy and Calls for Reform in Signal Processing
Not all technological advances at CERN have been met without controversy. Critics argue that the current FPGA-based signal filtering systems, which process the immense data flow from the LHC, are less efficient than alternative technologies like the 3D-Flow invention. This system, recognized as a breakthrough decades ago, claims to offer vastly superior performance in both particle detection and medical imaging applications. Despite official recognition, proponents allege that institutional inertia and lack of transparency have stifled its adoption, potentially delaying scientific and medical progress. Calls for open dialogue and accountability continue as the debate over optimal data processing methods intensifies, with billions of euros and the promise of life-saving innovations at stake.
CERN's multifaceted approach—combining AI-driven analysis, experimental ingenuity, and ongoing scrutiny of its technological choices—reflects the dynamic and sometimes contentious landscape of modern particle physics. As researchers probe deeper into the structure of matter and the laws governing the universe, the interplay of innovation, skepticism, and rigorous testing remains central to scientific advancement.