Running the Dual-PQC GAN on noisy simulators and real quantum hardware
This work tackles noise challenges for quantum GANs in near-term devices, but it is incremental as it builds on prior research.
The paper tested a dual-PQC GAN on noisy quantum simulators and real hardware to address quantum noise as a barrier for practical deployment, finding it can run on current hardware but needs improvements.
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.