Quantum Gaussian process state: A kernel-inspired state with quantum support data

Yannic Rath; George H. Booth

doi:10.1103/PhysRevResearch.4.023126

Quantum Gaussian process state: A kernel-inspired state with quantum support data

Yannic Rath, George H. Booth

King's College London

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

Abstract

We introduce the quantum Gaussian process state, motivated via a statistical inference for the wave function supported by a data set of unentangled product states. We show that this condenses down to a compact and expressive parametric form, with a variational flexibility shown to be competitive or surpassing established alternatives. The connections of the state to its roots as a Bayesian inference machine as well as matrix product states, also allow for efficient deterministic training of global states from small training data with enhanced generalization, including on application to frustrated spin physics.

Original language	English
Article number	023126
Journal	Physical Review Research
Volume	4
Issue number	2
DOIs	https://doi.org/10.1103/PhysRevResearch.4.023126
Publication status	Published - Jun 2022

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abstract = "We introduce the quantum Gaussian process state, motivated via a statistical inference for the wave function supported by a data set of unentangled product states. We show that this condenses down to a compact and expressive parametric form, with a variational flexibility shown to be competitive or surpassing established alternatives. The connections of the state to its roots as a Bayesian inference machine as well as matrix product states, also allow for efficient deterministic training of global states from small training data with enhanced generalization, including on application to frustrated spin physics.",

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note = "Funding Information: The authors are thankful for valuable discussions with Aldo Glielmo, Andrew Green and G{\'a}bor Cs{\'a}nyi relating to this work. G.H.B. gratefully acknowledges support from the Royal Society via a University Research Fellowship, and funding from the Air Force Office of Scientific Research via Grant No. FA9550-18-1-0515. The project has also received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 759063. We are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by EPSRC (Grants No. EP/P020194/1 and No. EP/T022213/1). Publisher Copyright: {\textcopyright} 2022 authors. Published by the American Physical Society.",

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Quantum Gaussian process state: A kernel-inspired state with quantum support data

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