Large scale multinode simulations of $\mathbb{Z}_2$ gauge theory quantum circuits using Google Cloud Platform
Abstract
Simulating quantum field theories on a quantum computer is one of the most exciting fundamental physics applications of quantum information science. Dynamical time evolution of quantum fields is a challenge that is beyond the capabilities of classical computing, but it can teach us important lessons about the fundamental fabric of space and time. Whether we may answer scientific questions of interest using nearterm quantum computing hardware is an open question that requires a detailed simulation study of quantum noise. Here we present a large scale simulation study powered by a multinode implementation of qsim using the Google Cloud Platform. We additionally employ newlydeveloped GPU capabilities in qsim and show how Tensor Processing Units  Applicationspecific Integrated Circuits (ASICs) specialized for Machine Learning  may be used to dramatically speed up the simulation of large quantum circuits. We demonstrate the use of high performance cloud computing for simulating $\mathbb{Z}_2$ quantum field theories on system sizes up to 36 qubits. We find this lattice size is not able to simulate our problem and observable combination with sufficient accuracy, implying more challenging observables of interest for this theory are likely beyond the reach of classical computation using exact circuit simulation.
 Publication:

arXiv eprints
 Pub Date:
 October 2021
 arXiv:
 arXiv:2110.07482
 Bibcode:
 2021arXiv211007482G
 Keywords:

 Quantum Physics;
 High Energy Physics  Lattice
 EPrint:
 8 pages, 6 figures, 3 tables