Hunting for quantum-classical crossover in condensed matter problems

Author:

Yoshioka NobuyukiORCID,Okubo TsuyoshiORCID,Suzuki YasunariORCID,Koizumi Yuki,Mizukami Wataru

Abstract

AbstractThe intensive pursuit for quantum advantage in terms of computational complexity has further led to a modernized crucial question of when and how will quantum computers outperform classical computers. The next milestone is undoubtedly the realization of quantum acceleration in practical problems. Here we provide a clear evidence and arguments that the primary target is likely to be condensed matter physics. Our primary contributions are summarized as follows: 1) Proposal of systematic error/runtime analysis on state-of-the-art classical algorithm based on tensor networks; 2) Dedicated and high-resolution analysis on quantum resource performed at the level of executable logical instructions; 3) Clarification of quantum-classical crosspoint for ground-state simulation to be within runtime of hours using only a few hundreds of thousand physical qubits for 2d Heisenberg and 2d Fermi-Hubbard models, assuming that logical qubits are encoded via the surface code with the physical error rate of p = 10−3. To our knowledge, we argue that condensed matter problems offer the earliest platform for demonstration of practical quantum advantage that is order-of-magnitude more feasible than ever known candidates, in terms of both qubit counts and total runtime.

Funder

MEXT | JST | Precursory Research for Embryonic Science and Technology

MEXT | JST | Center of Innovation Program

MEXT | JST | Exploratory Research for Advanced Technology

MEXT | JST | Core Research for Evolutional Science and Technology

Publisher

Springer Science and Business Media LLC

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Handbook for Efficiently Quantifying Robustness of Magic;Quantum;2024-09-05

2. Quantum Bit Controllers: Enabling Practical Quantum Computing;The Journal of The Institute of Electrical Engineers of Japan;2024-09-01

3. Ab initio extended Hubbard model of short polyenes for efficient quantum computing;The Journal of Chemical Physics;2024-08-28

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3