2022
DOI: 10.48550/arxiv.2201.06533
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Efficient Algorithms for Approximating Quantum Partition Functions at Low Temperature

Abstract: We establish an efficient approximation algorithm for the partition functions of a class of quantum spin systems at low temperature, which can be viewed as stable quantum perturbations of classical spin systems. Our algorithm is based on combining the contour representation of quantum spin systems of this type due to Borgs, Kotecký, and Ueltschi with the algorithmic framework developed by Helmuth, Perkins, and Regts, and Borgs et al.

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Cited by 1 publication
(2 citation statements)
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“…Other results on particular classes of models recently studied are e.g. those of [100] a class of dense Hamiltionians was shown to have an efficient algorithm, while in [29] a class of quantum models close to classical ones was shown to have a convergent cluster expansion even at low temperatures. There also exists quantum algorithms for approximating general partition functions [100,105] in the sense of Eq.…”
Section: B Hardness Of Approximating Partition Functionsmentioning
confidence: 99%
See 1 more Smart Citation
“…Other results on particular classes of models recently studied are e.g. those of [100] a class of dense Hamiltionians was shown to have an efficient algorithm, while in [29] a class of quantum models close to classical ones was shown to have a convergent cluster expansion even at low temperatures. There also exists quantum algorithms for approximating general partition functions [100,105] in the sense of Eq.…”
Section: B Hardness Of Approximating Partition Functionsmentioning
confidence: 99%
“…Let us note, however, that there are specific models in the literature for which the convergence can be guaranteed for larger ranges of temperatures (see e.g. [29] and references therein). See Sec.…”
Section: A Connected Cluster Expansionmentioning
confidence: 99%