Generative neural networks for fast ZDC simulations
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Updated
Jan 30, 2025 - Python
Generative neural networks for fast ZDC simulations
fast simulation tool originally developed by the BNL EIC task force
Even Faster Simulation of the Zero Degree Calorimeter Responses with Flow Matching
Tracking papers that use or relate to the LEMURS multi-detector calorimeter shower dataset (arXiv:2509.05108)
▎ Physics-constrained WGAN-GP that acts as a fast surrogate for Monte Carlo simulation of particles crossing the COMET Phase-I monitor plane. Includes ROOT-to-parquet ingestion, per-species training, multi-metric evaluation (C2ST, MMD, tail tests) and HTCondor submit files.
Production code for the SimpleBox and LEMURS point cloud calorimeter shower datasets: Geant4/DD4hep simulation to training-ready HDF5
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