Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network

Erdmann M, Glombitza J, Quast T (2019)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2019

Journal

Computing and Software for Big Science Springer International Publishing

Book Volume: 3

Article Number: 4

Journal Issue: 1

URI: https://link.springer.com/article/10.1007/s41781-018-0019-7

DOI: 10.1007/s41781-018-0019-7

Open Access Link: https://link.springer.com/article/10.1007/s41781-018-0019-7

Abstract

Simulations of particle showers in calorimeters are computationally time-consuming, as they have to reproduce both energy depositions and their considerable fluctuations. A new approach to ultra-fast simulations is generative models where all calorimeter energy depositions are generated simultaneously. We use GEANT4 simulations of an electron beam impinging on a multi-layer electromagnetic calorimeter for adversarial training of a generator network and a critic network guided by the Wasserstein distance. The generator is constrained during the training such that the generated showers show the expected dependency on the initial energy and the impact position. It produces realistic calorimeter energy depositions, fluctuations and correlations which we demonstrate in distributions of typical calorimeter observables. In most aspects, we observe that generated calorimeter showers reach the level of showers as simulated with the GEANT4 program.

Authors with CRIS profile

Jonas Glombitza

Involved external institutions

Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen

Germany (DE) Europäische Organisation für Kernforschung (CERN)

Switzerland (CH)

How to cite

APA:

Erdmann, M., Glombitza, J., & Quast, T. (2019). Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network. Computing and Software for Big Science, 3(1). https://doi.org/10.1007/s41781-018-0019-7

MLA:

Erdmann, Martin, Jonas Glombitza, and Thorben Quast. "Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network." Computing and Software for Big Science 3.1 (2019).

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