collaborators

7 papers

nucl-ex2026

ePIC Early Science Report

D. Abbott, N. Abdelrahman, S. Abhijit +781

This Early Science Report from the ePIC Collaboration outlines the compelling physics program achievable during the first years of operation of the Electron-Ion Collider (EIC), pri…

physics.ins-det2026

GPT-Based Fast Simulation of CLAS12 Detector Hits via Conditional Autoregressive Generation

Cole Granger, James Giroux, Richard Tyson +2

Modern particles physics experiments have demonstrated an increasing need for fast, high-fidelity detector simulation as detector components have improved and subsequent computatio…

physics.data-an2026

Application of a Mixture of Experts-based Foundation Model to the GlueX DIRC Detector

Cristiano Fanelli, James Giroux, Cole Granger +1

We present a Mixture-of-Experts-based foundation model applied to the GlueX DIRC detector at Jefferson Lab, demonstrating its utility as a unified framework for fast simulation, pa…

physics.ins-det2026

Generalizable Foundation Models for Calorimetry via Mixtures-of-Experts and Parameter Efficient Fine Tuning

Carlos Cardona-Giraldo, Cristiano Fanelli, James Giroux +3

Modern particle physics experiments face an increasing demand for high-fidelity detector simulation as luminosities rise and computational requirements approach the limits of avail…

cs.LG2025

Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data

James Giroux, Cristiano Fanelli

We present a (proto) Foundation Model for Nuclear Physics, capable of operating on low-level detector inputs from Imaging Cherenkov Detectors at the future Electron Ion Collider. B…

physics.ins-det2025

Generative Models for Fast Simulation of Cherenkov Detectors at the Electron-Ion Collider

James Giroux, Michael Martinez, Cristiano Fanelli

The integration of Deep Learning (DL) into experimental nuclear and particle physics has driven significant progress in simulation and reconstruction workflows. However, traditiona…