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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.