基于Google云平台的2规范理论量子电路的大规模多节点模拟

Erik J. Gustafson, B. Holzman, J. Kowalkowski, Henry Lamm, A. Li, G. Perdue, S. Isakov, O. Martin, R. Thomson, J. Beall, M. Ganahl, G. Vidal, E. Peters
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引用次数: 18

摘要

在量子计算机上模拟量子场论是量子信息科学最令人兴奋的基础物理应用之一。量子场的动态时间演化是一个超越经典计算能力的挑战,但它可以教给我们关于空间和时间基本结构的重要课程。我们是否可以使用近期量子计算硬件来回答感兴趣的科学问题是一个悬而未决的问题,需要对量子噪声进行详细的模拟研究。在这里,我们提出了一个大规模的模拟研究,该研究由使用Google云平台的多节点qsim实现提供支持。我们还在qsim中使用了新开发的GPU功能,并展示了如何使用张量处理单元——专门用于机器学习的专用集成电路(asic)——来显著加快大型量子电路的模拟。我们演示了使用高性能云计算来模拟系统大小为36量子位的2量子场理论。我们发现这种晶格大小无法以足够的精度模拟我们的问题和可观察的组合,这意味着对该理论感兴趣的更具挑战性的可观察对象可能超出了使用精确电路模拟的经典计算范围。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Large scale multi-node simulations of ℤ2 gauge theory quantum circuits using Google Cloud Platform
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 near-term 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 multi-node implementation of qsim using the Google Cloud Platform. We additionally employ newly-developed GPU capabilities in qsim and show how Tensor Processing Units — Application-specific 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 ℤ2 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.
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