CaloFlow for CaloChallenge Dataset 1

• URL: http://arxiv.org/abs/2210.14245v3
• Date: Wed, 15 May 2024 20:56:03 GMT
• Title: CaloFlow for CaloChallenge Dataset 1
• Authors: Claudius Krause, Ian Pang, David Shih,
• Abstract summary: CaloFlow is a new and promising approach to fast calorimeter simulation based on normalizing flows. We show how it can produce high-fidelity samples with a sampling time that is several orders of magnitude faster than Geant4.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: CaloFlow is a new and promising approach to fast calorimeter simulation based on normalizing flows. Applying CaloFlow to the photon and charged pion Geant4 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 Geant4. 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 Geant4 samples.

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