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Pythia-Contrib: a modular contribution framework for the Pythia 8 event generator
Benoit Assi, Christian Bierlich, Rikab Gambhir +6
Pythia is a general-purpose Monte Carlo event generator used in particle, astroparticle, and nuclear physics, by theorists and experimentalists, to simulate particle collisions. Be…
HEPTABench: A framework for portable and controlled agentic evaluations in high energy physics
Tony Menzo, Alexander Roman, George T. Fleming +3
Quantifying the capability and reliability of agentic systems in high-energy physics (HEP) requires repeated evaluations under controlled configurations. Establishing whether chang…
Reining in an Agentic Harness for High Energy Physics
Tony Menzo, George T. Fleming, Konstantin T. Matchev +2
Agentic systems now address tasks across theoretical, phenomenological, and experimental high energy physics (HEP), but their scientific capabilities remain difficult to reuse acro…
Confinement, String Breaking, and Hadronization in the Compact Abelian Higgs Model
Blake Senseman, Zane Ozzello, Yannick Meurice +1
While real-time simulation of Quantum Chromodynamics remains technologically out of reach, many simplified models for studying elements of QCD phenomenology are being investigated.…
Vistas: A Visualization Interface for Particle Collision Simulations
Benoit Assi, Christan Bierlich, Rikab Gambhir +7
We introduce Vistas, a tool for visualizing high-energy particle physics collisions simulated by the Pythia Monte-Carlo event generator. Vistas utilizes the browser-based event dis…
Agentic Diagrammatica: Towards Autonomous Symbolic Computation in High Energy Physics
Tony Menzo, Alexander Roman, George T. Fleming +3
We present Diagrammatica, a symbolic computation extension to the HEPTAPOD agentic framework, which enables LLM agents to plan and execute multi-step theoretical calculations. Symb…
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
HDSense: An efficient method for ranking observable sensitivity
Benoît Assi, Christian Bierlich, Rikab Gambhir +6
Identifying which observables most effectively constrain model parameters can be computationally prohibitive when considering full likelihoods of many correlated observables. This…