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This research presents a novel algorithmic approach to reduce the sampling cost of estimating thermal expectation values in quantum systems by utilizing single Gibbs-sampling trajectories. By interleaving coherent measurements that satisfy detailed balance, the method leverages shorter autocorrelation times compared to traditional mixing time requirements, offering significant efficiency gains for energy estimation and general observables. The work introduces specific techniques like Gaussian-filtered quantum phase estimation and weighted operator Fourier transforms to minimize measurement overhead and disturbance.
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Predicting properties of quantum thermal states from a single trajectory

arXiv2 min read

arXiv:2602.12539v2 Announce Type: replace Abstract: Estimating thermal expectation values of observables is a fundamental task in quantum physics, quantum chemistry, and materials science. While recent quantum algorithms have enabled efficient quantum preparation of thermal states, observable estimation via sampling remains costly: a straightforward implementation separates successive measurements by a full mixing time in order to ensure samples are approximately independent. In this work, we show that the sampling cost can be substantially reduced by using a single Gibbs-sampling trajectory. After a single burn-in period, we interleave coherent measurements that satisfy detailed balance with respect to the target Gibbs state. The efficiency of this approach rests on the fact that, in many settings, the autocorrelation time can be significantly shorter than the mixing time. For energy estimation (and more generally for observables commuting with the Hamiltonian), we implement the required measurements using Gaussian-filtered quantum phase estimation with only logarithmic overhead. We also introduce a weighted operator Fourier transform technique to mitigate measurement-induced disturbance for general observables.

Abstract:Estimating thermal expectation values of observables is a fundamental task in quantum physics, quantum chemistry, and materials science. While recent quantum algorithms have enabled efficient quantum preparation of thermal states, observable estimation via sampling remains costly: a straightforward implementation separates successive measurements by a full mixing time in order to ensure samples are approximately independent. In this work, we show that the sampling cost can be substantially reduced by using a single Gibbs-sampling trajectory. After a single burn-in period, we interleave coherent measurements that satisfy detailed balance with respect to the target Gibbs state. The efficiency of this approach rests on the fact that, in many settings, the autocorrelation time can be significantly shorter than the mixing time. For energy estimation (and more generally for observables commuting with the Hamiltonian), we implement the required measurements using Gaussian-filtered quantum phase estimation with only logarithmic overhead. We also introduce a weighted operator Fourier transform technique to mitigate measurement-induced disturbance for general observables.

arXiv:2602.12539 [quant-ph]

(or arXiv:2602.12539v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2602.12539 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 249 words

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