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At CERN, the ALICE collaboration uses open source code on GitHub to analyze massive amounts of physics data, demonstrating how shared code and peer review enable global teamwork in scientific breakthroughs.
Physicists have reached the neutrino fog in dark matter detection, forcing a shift from WIMP searches to broader approaches like quantum sensors and atmospheric searches.
This paper presents a quantized, integer-only transformer implementation for jet tagging on AMD Versal AI Engines, including a reusable open-source framework that maps transformer layers to AIE tiles for low-latency trigger systems at CERN LHC.
Lex Fridman's podcast conversation with particle physicist Don Lincoln about major open questions in physics, including dark energy, dark matter, and the unification of laws.
Collider-Bench is a new benchmark that evaluates LLM agents on reproducing particle physics analyses from the Large Hadron Collider using only public papers and open software, requiring physical reasoning to fill missing implementation details.
The article explores the historical and technical challenges involved in the detection of neutrinos, specifically highlighting the contributions and long journey at Los Alamos.
GPT-5.2 assisted in deriving a new theoretical physics result showing that single-minus gluon tree amplitudes can be nonzero under specific half-collinear momentum conditions, challenging decades of assumptions in particle physics. The AI model identified patterns in complex Feynman diagram expressions and conjectured a general formula that was subsequently verified through formal proofs.