Statistical Mechanics Calculations Using Variational Autoregressive Networks and Quantum Annealing

• URL: http://arxiv.org/abs/2404.19274v2
• Date: Mon, 20 May 2024 05:34:04 GMT
• Title: Statistical Mechanics Calculations Using Variational Autoregressive Networks and Quantum Annealing
• Authors: Yuta Tamura, Masayuki Ohzeki,
• Abstract summary: An approximation method using a variational autoregressive network (VAN) has been proposed recently. The present study introduces a novel approximation method that employs samples derived from quantum annealing machines in conjunction with VAN. When applied to the finite-size Sherrington-Kirkpatrick model, the proposed method demonstrates enhanced accuracy compared to the traditional VAN approach.
• Score: 0.552480439325792
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In statistical mechanics, computing the partition function is generally difficult. An approximation method using a variational autoregressive network (VAN) has been proposed recently. This approach offers the advantage of directly calculating the generation probabilities while obtaining a significantly large number of samples. The present study introduces a novel approximation method that employs samples derived from quantum annealing machines in conjunction with VAN, which are empirically assumed to adhere to the Gibbs-Boltzmann distribution. When applied to the finite-size Sherrington-Kirkpatrick model, the proposed method demonstrates enhanced accuracy compared to the traditional VAN approach and other approximate methods, such as the widely utilized naive mean field.

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