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Article
Report number arXiv:2203.01007 ; MIT-CTP/5400
Title Impact of quantum noise on the training of quantum Generative Adversarial Networks
Author(s) Borras, Kerstin (DESY, Zeuthen ; RWTH Aachen U.) ; Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Funcke, Lena (MIT, Cambridge, CTP ; IAIFI, Cambridge) ; Grossi, Michele (CERN) ; Hartung, Tobias (Cyprus Inst. ; Bath U.) ; Jansen, Karl (DESY, Zeuthen) ; Kruecker, Dirk (DESY, Zeuthen) ; Kühn, Stefan (Cyprus Inst.) ; Rehm, Florian (CERN ; RWTH Aachen U.) ; Tüysüz, Cenk (DESY, Zeuthen ; Humboldt U., Berlin) ; Vallecorsa, Sofia (CERN)
Publication 2023
Imprint 2022-03-02
Number of pages 6
Note 6 pages, 5 figures, Proceedings of the 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021)
In: J. Phys.: Conf. Ser. 2438, 1 (2023) pp.012093
In: 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012093
DOI 10.1088/1742-6596/2438/1/012093
Subject category hep-ex ; Particle Physics - Experiment ; quant-ph ; General Theoretical Physics
Abstract Current noisy intermediate-scale quantum devices suffer from various sources of intrinsic quantum noise. Overcoming the effects of noise is a major challenge, for which different error mitigation and error correction techniques have been proposed. In this paper, we conduct a first study of the performance of quantum Generative Adversarial Networks (qGANs) in the presence of different types of quantum noise, focusing on a simplified use case in high-energy physics. In particular, we explore the effects of readout and two-qubit gate errors on the qGAN training process. Simulating a noisy quantum device classically with IBM's Qiskit framework, we examine the threshold of error rates up to which a reliable training is possible. In addition, we investigate the importance of various hyperparameters for the training process in the presence of different error rates, and we explore the impact of readout error mitigation on the results.
Copyright/License preprint: (License: CC BY 4.0)



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 記錄創建於2022-03-04,最後更新在2024-02-20


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