Generative neural networks for fast ZDC simulations
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Updated
Jan 30, 2025 - Python
Generative neural networks for fast ZDC simulations
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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