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arXiv 2602.07151quant-ph
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在数字量子计算机上放置费米子

Putting fermions onto a digital quantum computer

Sandia National Laboratories(桑迪亚国家实验室);DAMTP, Centre for Mathematical Sciences, University of Cambridge(剑桥大学数学科学中心 DAMTP);Department of Physics and Astronomy, Dartmouth College(达特茅斯学院物理与天文学系);Joint Center for Quantum Information and Computer Science, University of Maryland(马里兰大学量子信息与计算科学联合中心);School of Physics, University of Sydney(悉尼大学物理学院);Department of Chemistry, Rice University(莱斯大学化学系);Department of Physics and Astronomy, Rice University(莱斯大学物理与天文学系);Department of Computer Science, University of Oxford(牛津大学计算机科学系)
Riley W. Chien, Mitchell L. Chiew, Brent Harrison, Jason Necaise, Weishi Wang, Maryam Mudassar, Campbell McLauchlan, Thomas M. Henderson, Gustavo E. Scuseria, S… 展开作者

Riley W. Chien, Mitchell L. Chiew, Brent Harrison, Jason Necaise, Weishi Wang, Maryam Mudassar, Campbell McLauchlan, Thomas M. Henderson, Gustavo E. Scuseria, Sergii Strelchuk, James D. Whitfield

AI总结:

本文探讨了在数字量子计算机上模拟费米子系统的方法,挑战了多维费米子系统更难处理的观念。

摘要:

量子计算机预计将成为研究物理量子系统的一种强大工具。因此,已开发出多种用于研究此类系统物理性质的量子算法。尽管基于量子位的量子计算机天然适合研究自旋-1/2系统,但包含其他自由度的系统必须首先被编码为量子位。转换到和从费米子自由度的变换长期以来一直是物理学的重要工具,现在在基于量子位的量子计算机上模拟费米子系统又提供了另一个应用。在本文中,我们回顾了将费米子自由度编码为量子位的方法,并试图消除一个持久的观点,即多维以上的费米子系统本质上更难处理。

英文摘要:

Quantum computers are expected to become a powerful tool for studying physical quantum systems. Consequently, a number of quantum algorithms for studying the physical properties of such systems have been developed. While qubit-based quantum computers are naturally suited to the study of spin-1/2 systems, systems containing other degrees of freedom must first be encoded into qubits. Transformations to and from fermionic degrees of freedom have long been an important tool in physics and, now the simulation of fermionic systems on quantum computers based on qubits provides yet another application. In this perspective, we review methods for encoding fermionic degrees of freedom into qubits and attempt to dispel the persistent notion that fermionic systems beyond one dimension are fundamentally more difficult to deal with.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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