SciPost Physics · 2024 · 24 citations · 39 references
Natural SciencesComputer SciencePhysicsComputational PhysicsMachine LearningParticle PhysicsCalorimetryDeep LearningImage Feature EngineeringMonte Carlo SimulationSampling Time Design
CALOFLOW is a new and promising approach to fast calorimeter simulation based on normalizing flows. Applying CALOFLOW to the photon and charged pion ≥ant showers of Dataset 1 of the Fast Calorimeter Simulation Challenge 2022, we show how it can produce high-fidelity samples with a sampling time that is several orders of magnitude faster than ≥ant. We demonstrate the fidelity of the samples using calorimeter shower images, histograms of high level features, and aggregate metrics such as a classifier trained to distinguish CALOFLOW from ≥ant samples.
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Matplotlib: A 2D Graphics Environment
John D. Hunter · Computing in Science & Engineering · 2007 · 39.6K citations
Geant4 developments and applications
John E. Allison, K. Amako, J. Apostolakis et al. · IEEE Transactions on Nuclear Science · 2006 · 6.9K citations · Full text