Accurate Learning of Equivariant Quantum Systems from a Single Ground State

• URL: http://arxiv.org/abs/2405.12309v1
• Date: Mon, 20 May 2024 18:13:15 GMT
• Title: Accurate Learning of Equivariant Quantum Systems from a Single Ground State
• Authors: Štěpán Šmíd, Roberto Bondesan,
• Abstract summary: We show how to learn properties of all ground states for systems with periodic boundary conditions from a single ground state sample. We prove that the prediction error tends to zero in the thermodynamic limit and numerically verify the results.
• Score: 7.980273012483663
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Predicting properties across system parameters is an important task in quantum physics, with applications ranging from molecular dynamics to variational quantum algorithms. Recently, provably efficient algorithms to solve this task for ground states within a gapped phase were developed. Here we dramatically improve the efficiency of these algorithms by showing how to learn properties of all ground states for systems with periodic boundary conditions from a single ground state sample. We prove that the prediction error tends to zero in the thermodynamic limit and numerically verify the results.

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