In this extended abstract, we have introduced a highly memory-efficient state vector simulation of quantum circuits premised on data compression, harnessing the capabilities of both CPUs and GPUs. We have elucidated the inherent challenges in architecting this system, while concurrently proposing our tailored solutions. Moreover, we have delineated our preliminary implementation and deliberated upon the potential for integration with other GPU-oriented simulators. In forthcoming research, we aim to present a more comprehensive set of results, bolstering the assertion of the efficacy and performance of our approach.
@article{arxiv.2309.16979,
title = {MEMQSim: Highly Memory-Efficient and Modularized Quantum State-Vector Simulation},
author = {Boyuan Zhang and Bo Fang and Qiang Guan and Ang Li and Dingwen Tao},
journal= {arXiv preprint arXiv:2309.16979},
year = {2023}
}