Generative Adversarial Networks for the fast simulation of the Time Projection Chamber responses at the MPD detector

• URL: http://arxiv.org/abs/2203.16355v1
• Date: Wed, 30 Mar 2022 14:31:50 GMT
• Title: Generative Adversarial Networks for the fast simulation of the Time Projection Chamber responses at the MPD detector
• Authors: A. Maevskiy, F. Ratnikov, A. Zinchenko, V. Riabov, A. Sukhorosov and D. Evdokimov
• Abstract summary: We demonstrate the applicability of Generative Adversarial Networks (GAN) as the basis for such fast-simulation models. Our prototype GAN-based model of TPC works more than an order of magnitude faster compared to the detailed simulation.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The detailed detector simulation models are vital for the successful operation of modern high-energy physics experiments. In most cases, such detailed models require a significant amount of computing resources to run. Often this may not be afforded and less resource-intensive approaches are desired. In this work, we demonstrate the applicability of Generative Adversarial Networks (GAN) as the basis for such fast-simulation models for the case of the Time Projection Chamber (TPC) at the MPD detector at the NICA accelerator complex. Our prototype GAN-based model of TPC works more than an order of magnitude faster compared to the detailed simulation without any noticeable drop in the quality of the high-level reconstruction characteristics for the generated data. Approaches with direct and indirect quality metrics optimization are compared.

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