Difficult instances of the counting problem for 2-quantum-SAT are very atypical

TL;DR

This paper investigates the complexity of the #2-QSAT counting problem, showing that most instances with product constraints are efficiently solvable unless they resemble classical monotone #2-SAT cases.

Contribution

It identifies conditions under which product constraint instances of #2-QSAT are efficiently solvable, bridging classical and quantum satisfiability complexities.

Findings

Most #2-QSAT instances with product constraints are easy to solve.

Entangled constraints lead to more complex, long-range correlations.

Instances resembling classical monotone #2-SAT are exceptions to efficient solvability.

Abstract

The problem 2-quantum-satisfiability (2-QSAT) is the generalisation of the 2-CNF-SAT problem to quantum bits, and is equivalent to determining whether or not a spin-1/2 Hamiltonian with two-body terms is frustration-free. Similarly to the classical problem 2-SAT, the counting problem #2-QSAT of determining the size (i.e. the dimension) of the set of satisfying states is #P-complete. However, if we consider random instances of #2-QSAT in which constraints are sampled from the Haar measure, intractible instances have measure zero. An apparent reason for this is that almost all two-qubit constraints are entangled, which more readily give rise to long-range constraints. We investigate under which conditions product constraints also give rise to efficiently solvable families of #2-QSAT instances. We consider #2-QSAT involving only discrete distributions over tensor product operators, which interpolates between classical #2-SAT and #2-QSAT involving arbitrary product constraints. We find that such instances of #2-QSAT, defined on Erdos--Renyi graphs or bond-percolated lattices, are asymptotically almost surely efficiently solvable except to the extent that they are biased to resemble monotone instances of #2-SAT.