collider physics

Physicists have claimed that anomalies in particle collision data from the Large Hadron Collider could be explained by the existence of a fifth dimension. The proposal suggests unusual measurements at CERN's collider might be evidence of physics beyond the Standard Model, though the idea remains speculative and would require further experimental confirmation.

Physicist and science commentator Sabine Hossenfelder has weighed in on suggestions that the Large Hadron Collider at CERN may have found evidence of a fifth dimension. Her video asking 'Fifth Dimension Found At LHC?' has drawn hundreds of thousands of likes, fueling debate about what the collider's data actually shows and how extra-dimension claims should be interpreted.

Physicists present Machine-Learned Particle Flow as a foundation model for collider physics, arguing that a single machine-learned representation of particle-flow information could serve as a reusable base for many collider analyses, much as foundation models do in other fields. The work, published in an APS journal, points toward more transferable AI tools for processing data from particle colliders.

Physicists have reported a new computational route for calculating gluon production in proton–nucleus collisions. Gluons are the particles that bind quarks together, and predictions of their production in collisions involving protons and heavy nuclei are central to tests of quantum chromodynamics and to interpreting results from colliders such as the LHC. The work offers an alternative approach where previous calculations were difficult, and is being noted by researchers in high-energy nuclear physics.

Physics Today reports that two research teams have independently tackled the problem of atomic collisions using different approaches. The work concerns how atoms interact and scatter when they collide, a foundational question in physics with implications for fields such as ultracold atomic gases and quantum chemistry. Details of the teams' methods and results were not provided in the coverage.

The Association of American Medical Colleges is publishing a profile of a surgeon's career, examining how the physical demands of the profession collide with a lifelong commitment to surgical practice. The piece reflects on what it means to sustain a calling in medicine when the body itself imposes boundaries, and speaks to broader questions of aging, resilience and career longevity among practicing physicians.

Physicists at the Large Hadron Collider report detecting evidence of matter from the Big Bang in collisions far smaller than previously thought capable of producing it. The findings suggest quark-gluon plasma, a state of primordial matter, can form in compact particle interactions, challenging existing models of how the early-universe state arises. Researchers say the result could prompt a rethinking of how such matter behaves under extreme conditions.

Scientists explain that galaxies rotate because of angular momentum generated when ancient gas clouds and dust collided off-center in the early universe. These initial spiraling motions were conserved over billions of years, amplified through generations of cosmic mergers and shaped by the gravitational pull of early matter, producing the spinning structures seen across the universe today.

Engineers are developing artificial intelligence capable of deciding, in real time, which of the roughly forty million proton collisions per second at the Large Hadron Collider are worth recording. With far more collisions occurring than can be stored, automated filtering is essential to the collider's physics programme, and the project is drawing attention for the scale of the challenge involved.

Physicists have collided oxygen nuclei in high-energy experiments designed to recreate conditions from the first moments after the Big Bang. By smashing the nuclei apart at near-light speeds, researchers can study the primordial plasma of quarks and gluons thought to have filled the early universe. The work extends heavy-ion collision research to lighter elements and offers a new window on how matter first formed.

Phys.org reports on a mathematical technique drawing on tropical geometry that could simplify calculations used in particle collider experiments. The approach offers a potential shortcut for handling the complex computations physicists rely on to predict collision outcomes at facilities like the Large Hadron Collider, though details of its practical impact remain limited in the coverage so far.

Researchers report a foundation model pretrained on 500 million simulated particle collisions that can transfer across different collider analyses. The work suggests a single pretrained model could support multiple high-energy physics tasks without retraining from scratch, potentially reducing the computing and simulation costs of experiments like those at large colliders. The announcement is drawing attention within the artificial intelligence community as an example of foundation-model methods moving into fundamental physics research.