A Full Quantum Generative Adversarial Network Model for High Energy Physics Simulations

Journal of Physics Conference Series, vol. 3206, pp. 012073

Abstract

Abstract The prospect of quantum computing with a potential exponential speed-up compared to classical computing identifies it as a promising method in the search for alternative future High Energy Physics (HEP) simulation approaches. HEP simulations, such as employed at the Large Hadron Collider at CERN, are extraordinarily complex and require an immense amount of computing resources in hardware and time. For some HEP simulations, classical machine learning models have already been successfully developed and tested, resulting in several orders of magnitude speed-up. In this research, we proceed to the next step and explore whether quantum computing can provide sufficient accuracy, and further improvements, suggesting it as an exciting direction of future investigations. With a small prototype model, we demonstrate a full quantum Generative Adversarial Network (GAN) model for generating downsized eight-pixel calorimeter shower images. The advantage over previous quantum models is that the model generates real individual images containing pixel energy values instead of simple probability distributions averaged over a test sample. To complete the picture, the results of the full quantum GAN model are compared to hybrid quantum-classical models using a classical discriminator neural network.

Authors 5

1. Florian Rehm Aachen

   RWTH Aachen University · European Organization for Nuclear Research

   Affiliation as printed

   CERN, 1211 Geneva 23,

   RWTH Aachen University

2. Sofia Vallecorsa

   European Organization for Nuclear Research

   Affiliation as printed

   CERN, 1211 Geneva 23,

3. Michele Grossi

   European Organization for Nuclear Research

   Affiliation as printed

   CERN, 1211 Geneva 23,

4. K. Borras Aachen

   RWTH Aachen University · Deutsches Elektronen-Synchrotron DESY

   Affiliation as printed

   Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607 Hamburg,

   RWTH Aachen University

5. Dirk Krücker

   Deutsches Elektronen-Synchrotron DESY

   Affiliation as printed

   Deutsches Elektronen-Synchrotron DESY, Notkestrasse 85, 22607 Hamburg,