Faster than Classical Quantum Algorithm for dense Formulas of Exact Satisfiability and Occupation Problems
arXiv:1512.00859 · doi:10.1088/1367-2630/18/7/073003
Abstract
We present an exact quantum algorithm for solving the Exact Satisfiability (XSAT) problem, which belongs to the important NP-complete complexity class. The algorithm is based on an intuitive approach that can be divided into two parts: First, the identification and efficient characterization of a restricted subspace that contains all the valid assignments of the XSAT; Second, a quantum search in such restricted subspace. The quantum algorithm can be used either to find a valid assignment (or to certify that no solution exists) or to count the total number of valid assignments. The query complexities for the worst-case are respectively bounded by and , where is the number of variables and the number of linearly independent clauses. Remarkably, the proposed quantum algorithm results to be faster than any known exact classical algorithm to solve dense formulas of XSAT. As a concrete application, we provide the worst-case complexity for the Hamiltonian cycle problem obtained after mapping it to a suitable XSAT. Specifically, we show that the time complexity for the proposed quantum algorithm is bounded by for 3-regular undirected graphs, where is the number of nodes. The same worst-case complexity holds for -regular bipartite graphs (the current best classical algorithm has a (worst-case) running time bounded by ). Finally, when compared to heuristic techniques for XSAT, the proposed quantum algorithm is faster than the classical WalkSAT and Adiabatic Quantum Optimization for random instances with a density of constraints close to the satisfiability threshold, the regime in which instances are typically the hardest to solve. The proposed quantum algorithm can be also extended to the generalized version of the XSAT known as Occupation problem.
Added a new section "Application to the Hamiltonian cycle problem". The paper has been published in New Journal of Physics
References in corpus (9)
- Quantum algorithm for solving linear systems of equations
- Exponential algorithmic speedup by quantum walk
- Gibbs States and the Set of Solutions of Random Constraint Satisfaction Problems
- Boson Sampling for Molecular Vibronic Spectra
- Size dependence of the minimum excitation gap in the Quantum Adiabatic Algorithm
- The Good Old Davis-Putnam Procedure Helps Counting Models
- Locked constraint satisfaction problems
- Constraint satisfaction problems with isolated solutions are hard
- Typical kernel size and number of sparse random matrices over GF(q) - a statistical physics approach
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