2022/08/19 by Garrett T. Floyd, Floyd, Garrett T., D. P. Landau +3
Computer Science · Mathematics · Physics and Astronomy · #Algorithm #Artificial intelligence #Computer science #Computer vision #FOS: Physical sciences #Histogram #Image (mathematics) #Importance sampling #Markov chain Monte Carlo #Mathematics #Metropolis–Hastings algorithm #Monte Carlo method #Physics #Quantum #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #Quantum algorithm #Quantum computer #Quantum many-body systems #Quantum mechanics #Sampling (signal processing) #Statistics #Theoretical computer science
paper · pdf · doi:10.48550/arxiv.2208.09543
openalex publication_date 2022/08/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It has been shown that the Metropolis algorithm can be implemented on quantum computers in a way that avoids the sign problem. However, flat histogram techniques are often preferred as they don't suffer from the same limitations that afflict Metropolis for problems of real-world interest and provide a host of other benefits. In particular, the Wang-Landau method is known for its efficiency and accuracy. In this work we design, implement, and validate a quantum algorithm for Wang-Landau sampling, greatly expanding the range of quantum many body problems solvable by Monte Carlo simulation.