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.
翻译:在早期工作中,我们引入了量子GAN的先进原型,即二元分量子反转网络(PQC),这是量子GAN的先进原型。我们应用了这个模型用于一个现实的高能物理(HEP)使用案例:精确的理论模拟卡罗里米反应,其问题小一些。本文探讨了双元分量子电路(PQC),以便在有不同种类量子噪音的情况下测试其性能,以便更实际地使用,这些量子噪音是使用近期量子装置成功部署的主要障碍。结果提出了运行当前实际硬件模型的可能性,但有些领域仍然需要改进。