In an earlier work, we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of a quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. This paper explores the dual- PQC GAN for a more practical usage by testing its performance in the presence of different types of quantum noise, which are the major obstacles to overcome for successful deployment using near-term quantum devices. The results propose the possibility of running the model on current real hardware, but improvements are still required in some areas.
@article{arxiv.2205.15003,
title = {Running the Dual-PQC GAN on noisy simulators and real quantum hardware},
author = {Su Yeon Chang and Edwin Agnew and Elías F. Combarro and Michele Grossi and Steven Herbert and Sofia Vallecorsa},
journal= {arXiv preprint arXiv:2205.15003},
year = {2023}
}
Comments
6 pages, 5 figures, Proceedings of the 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)