Towards a variational Jordan-Lee-Preskill quantum algorithm
- Creators
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Liu, Junyu
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Li, Zimu
- Zheng, Han
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Yuan, Xiao
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Sun, Jinzhao
Abstract
Rapid developments of quantum information technology show promising opportunities for simulating quantum field theory in near-term quantum devices. In this work, we formulate the theory of (time-dependent) variational quantum simulation of the 1 + 1 dimensional λφ⁴ quantum field theory including encoding, state preparation, and time evolution, with several numerical simulation results. These algorithms could be understood as near-term variational quantum circuit (quantum neural network) analogs of the Jordan-Lee-Preskill algorithm, the basic algorithm for simulating quantum field theory using universal quantum devices. Besides, we highlight the advantages of encoding with harmonic oscillator basis based on the Lehmann-Symanzik-Zimmermann reduction formula and several computational efficiency such as when implementing a bosonic version of the unitary coupled cluster ansatz to prepare initial states. We also discuss how to circumvent the 'spectral crowding' problem in the quantum field theory simulation and appraise our algorithm by both state and subspace fidelities.
Additional Information
© 2022 The Author(s). Published by IOP Publishing Ltd. Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. This paper is mostly finished when J L is a graduate student in Caltech. We thank Alex J Buser, Liang Jiang, Natalie Klco, Peter Love, Ash Milsted, John Preskill, Burak Sahinoglu, Guifre Vidal, and Xiaoyang Wang for related discussions. J L is supported in part by the Institute for Quantum Information and Matter (IQIM), an NSF Physics Frontiers Center (NSF Grant PHY-1125565) with support from the Gordon and Betty Moore Foundation (GBMF-2644), the Walter Burke Institute for Theoretical Physics. J L is also supported in part by International Business Machines (IBM) Quantum through the Chicago Quantum Exchange. X Y acknowledges support from the Simons Foundation.Attached Files
Published - Liu_2022_Mach._Learn.__Sci._Technol._3_045030.pdf
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Additional details
- Eprint ID
- 119275
- Resolver ID
- CaltechAUTHORS:20230214-86673200.4
- PHY-1125565
- NSF
- GBMF-2644
- Gordon and Betty Moore Foundation
- Walter Burke Institute for Theoretical Physics, Caltech
- IBM Quantum
- Alfred P. Sloan Foundation
- Created
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2023-03-29Created from EPrint's datestamp field
- Updated
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2023-03-29Created from EPrint's last_modified field
- Caltech groups
- Institute for Quantum Information and Matter, Walter Burke Institute for Theoretical Physics