Comparison of D-Wave Quantum Annealing and Gibbs Monte Carlo for Sampling from a Probability Distribution of a Restricted Boltzmann Machine

arXiv:2508.10228 · cs.LG, quant-ph, stat.ML · Submitted 2025-08-13 · Read on arXiv

cs.LG, quant-ph, stat.ML

Submitted: 2025-08-13

Updated: 2026-09-08

Comments: 23 pages, 10 figures. Accepted version, published in Entropy 28(8), 925 (2026). Title changed from "Comparison of D-Wave Quantum Annealing and Markov Chain Monte Carlo for Sampling from a Probability Distribution of a Restricted Boltzmann Machine"; author list updated to match publication

Journal ref: Entropy 28(8), 925 (2026)

DOI: 10.3390/e28080925

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Monte Carlo — 4× in this paper
• Adiabatic Evolution — 2× in this paper · explained in 2 episodes
• Ground State — 2× in this paper
• Markov Chain Monte Carlo — 2× in this paper
• Alignment — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• D-Wave Quantum Processing Unit — 1× in this paper
• Generative Model — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes

Sources

• Application of Quantum Annealing to Training of Deep Neural Networks
• Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer
• Benchmarking Quantum Hardware for Training of Fully Visible Boltzmann Machines

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