pith. sign in

arxiv: 2506.11576 · v6 · pith:LVWZWIGInew · submitted 2025-06-13 · 🪐 quant-ph · cond-mat.stat-mech· physics.chem-ph

Quantum Circuits for the Metropolis-Hastings Algorithm

classification 🪐 quant-ph cond-mat.stat-mechphysics.chem-ph
keywords quantumcomputingwalkmarkovmethodsrequirereversibleszegedy
0
0 comments X
read the original abstract

Szegedy's quantization of a reversible Markov chain provides a quantum walk whose spectral gap is quadratically larger than that of the classical walk. Quantum computers are therefore expected to provide a speedup of Metropolis-Hastings (MH) simulations. Existing generic methods to implement the quantum walk require coherently computing the transition probabilities of the underlying Markov kernel. However, reversible computing methods require a number of qubits that scales with the complexity of the computation. This overhead is undesirable in near-term fault-tolerant quantum computing, where few logical qubits are available. In this work, we present a Szegedy quantum walk construction which follows the classical proposal-acceptance logic, and does not require further reversible computing methods. We also compare this construction with an alternative to Szegedy's approach which also provides a quadratic gap amplification. Since each step of the quantum walks uses a constant number of proposal and acceptance steps, we expect the end-to-end quadratic speedup to hold for MH Markov Chain Monte-Carlo simulations.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Ancilla-Efficient QSAMPLE Preparation for Reversible Markov Chains

    quant-ph 2026-05 unverdicted novelty 7.0

    A one-ancilla framework for QSAMPLE preparation via GQSP-based selective phase compilation embedded in fixed-point amplitude amplification, improving overlap dependence to inverse square-root minimum overlap.