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Efficient quantum Gibbs samplers with Kubo--Martin--Schwinger detailed balance condition

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arxiv 2404.05998 v5 pith:I544FLYO submitted 2024-04-09 quant-ph

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keywords gibbsdynamicsquantumdetailedefficientjumpsamplersakin
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Lindblad dynamics and other open-system dynamics provide a promising path towards efficient Gibbs sampling on quantum computers. In these proposals, the Lindbladian is obtained via an algorithmic construction akin to designing an artificial thermostat in classical Monte Carlo or molecular dynamics methods, rather than treated as an approximation to weakly coupled system-bath unitary dynamics. Recently, Chen, Kastoryano, and Gily\'en (arXiv:2311.09207) introduced the first efficiently implementable Lindbladian satisfying the Kubo--Martin--Schwinger (KMS) detailed balance condition, which ensures that the Gibbs state is a fixed point of the dynamics and is applicable to non-commuting Hamiltonians. This Gibbs sampler uses a continuously parameterized set of jump operators, and the energy resolution required for implementing each jump operator depends only logarithmically on the precision and the mixing time. In this work, we build upon the structural characterization of KMS detailed balanced Lindbladians by Fagnola and Umanit\`a, and develop a family of efficient quantum Gibbs samplers using a finite set of jump operators (the number can be as few as one), \re{akin to the classical Markov chain-based sampling algorithm. Compared to the existing works, our quantum Gibbs samplers have a comparable quantum simulation cost but with greater design flexibility and a much simpler implementation and error analysis.} Moreover, it encompasses the construction of Chen, Kastoryano, and Gily\'en as a special instance.

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  1. Symmetry-initialized quantum Gibbs sampling: a non-Abelian asymmetry cascade

    quant-ph 2026-07 conditional novelty 6.0 of 10

    For a reversible quantum Gibbs sampler with a weakly broken symmetry, initializing in the symmetry-averaged state removes the slow modes and provably upgrades a prefactor saving into an asymptotic rate jump.

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