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

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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 languageEnglish
Article number023126
JournalPhysical Review Research
Volume4
Issue number2
DOIs
Publication statusPublished - Jun 2022

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