CaloFlow for CaloChallenge dataset 1

Author:

Krause Claudius12ORCID,Pang Ian2,Shih David2

Affiliation:

1. Heidelberg University

2. Rutgers University

Abstract

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.

Funder

Baden-Württemberg Stiftung

United States Department of Energy

Publisher

Stichting SciPost

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