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Towards a variational Jordan-Lee-Preskill quantum algorithm

delete2022-12-28
delete6
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OA
AI
J
Junyu Liu *
Z
Zimu Li
H
Han Zheng
袁
袁骁 (Xiao Yuan)
J
Jinzhao Sun *
DOI:10.1088/2632-2153/aca06bdelete
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摘要

摘要

En 中文
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 lambda phi(4) 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.
Keyword:
quantum physics
variational quantum algorithms
high energy physics

期刊

M
Machine Learning-Science and Technology
IF:
4.6
论文数:
1.1K
被引数:
3.4K

机构

C
California Institute of Technology
学者数:
2.9W
论文数: 2.5W
被引数: 4.9W
S
Stanford University
学者数:
9.6W
论文数: 8.2W
被引数: 17.0W
U
university of chicago
学者数:
4.5W
论文数: 3.7W
被引数: 80
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