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CaloDVAE : Discrete Variational Autoencoders for Fast Calorimeter Shower Simulation

2022/10/14 by Abhishek Singh, Abhishek, Abhishek, E. Drechsler +5 · 1 citation
Physics and Astronomy · Computer Science · #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #Computational Physics and Python Applications

paper · pdf · doi:10.48550/arxiv.2210.07430

Abstract

Calorimeter simulation is the most computationally expensive part of Monte Carlo generation of samples necessary for analysis of experimental data at the Large Hadron Collider (LHC). The High-Luminosity upgrade of the LHC would require an even larger amount of such samples. We present a technique based on Discrete Variational Autoencoders (DVAEs) to simulate particle showers in Electromagnetic Calorimeters. We discuss how this work paves the way towards exploration of quantum annealing processors as sampling devices for generation of simulated High Energy Physics datasets.

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