Fast counting with tensor networks

Kourtis, Stefanos; Chamon, Claudio; Mucciolo, Eduardo; Ruckenstein, Andrei

doi:10.21468/SciPostPhys.7.5.060

Fast counting with tensor networks

Journal Article · Tue Nov 12 04:00:00 EST 2019 · SciPost Physics

DOI:https://doi.org/10.21468/SciPostPhys.7.5.060· OSTI ID:1574034

Kourtis, Stefanos ^[1]; Chamon, Claudio ^[1]; Mucciolo, Eduardo ^[2]; Ruckenstein, Andrei ^[1]

Boston University
University of Central Florida

We introduce tensor network contraction algorithms for counting satisfying assignments of constraint satisfaction problems (#CSPs). We represent each arbitrary #CSP formula as a tensor network, whose full contraction yields the number of satisfying assignments of that formula, and use graph theoretical methods to determine favorable orders of contraction. We employ our heuristics for the solution of #P-hard counting boolean satisfiability (#SAT) problems, namely monotone #1-in-3SAT and #Cubic-Vertex-Cover, and find that they outperform state-of-the-art solvers by a significant margin.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: FG02-06ER46316

OSTI ID:: 1574034

Alternate ID(s):: OSTI ID: 1800383

Journal Information:: SciPost Physics, Journal Name: SciPost Physics Journal Issue: 5 Vol. 7; ISSN 2542-4653

Publisher:: Stichting SciPostCopyright Statement

Country of Publication:: Netherlands

Language:: English

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