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Scalable simulation of nonequilibrium quantum dynamics via classically optimized unitary circuits

Causer, Luke; Jung, Felix; Mitra, Asimpunya; Pollmann, Frank; Gammon-Smith, Adam

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Authors

Luke Causer

Felix Jung

Asimpunya Mitra

Frank Pollmann



Abstract

The advent of near-term digital quantum computers could offer us an exciting opportunity to investigate quantum many-body phenomena beyond that of classical computing. To make the best use of the hardware available, it is paramount that we have methods that accurately simulate Hamiltonian dynamics for limited circuit depths. In this paper, we propose a method to classically optimize unitary brickwall circuits to approximate quantum time evolution operators. Our method is scalable in system size through the use of tensor networks. We demonstrate that, for various three-body Hamiltonians, our approach produces quantum circuits that can outperform trotterization in both their accuracy and the quantum circuit depth needed to implement the dynamics, with the exact details being dependent on the Hamiltonian. We also explain how to choose an optimal time step that minimizes the combined errors of the quantum device and the brickwall circuit approximation.

Citation

Causer, L., Jung, F., Mitra, A., Pollmann, F., & Gammon-Smith, A. (2024). Scalable simulation of nonequilibrium quantum dynamics via classically optimized unitary circuits. Physical Review Research, 6(3), Article 033062. https://doi.org/10.1103/physrevresearch.6.033062

Journal Article Type Article
Acceptance Date Jun 18, 2024
Online Publication Date Jul 15, 2024
Publication Date 2024-07
Deposit Date Jul 22, 2024
Publicly Available Date Jul 23, 2024
Journal Physical Review Research
Electronic ISSN 2643-1564
Publisher American Physical Society
Peer Reviewed Peer Reviewed
Volume 6
Issue 3
Article Number 033062
DOI https://doi.org/10.1103/physrevresearch.6.033062
Public URL https://nottingham-repository.worktribe.com/output/37319043
Publisher URL https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.6.033062

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