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2016

Quantum Annealing and the Satisfiability Problem

Pudenz, Kristen L., Tallant, Gregory S., Belote, Todd R. et al.

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The utility of satisfiability (SAT) as an application focused hard computational problem is well established.

We explore the potential of quantum annealing to enhance classical SAT solving, especially where sampling from the space of all possible solutions is of interest.
We address the formulation of SAT problems to make them suitable for commercial quantum annealers, practical concerns in their implementation, and how the performance of the resulting quantum solver compares to and complements classical SAT solvers.

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Built on

Z. Bian et. al., The Ising model: teaching an old problem new tricks, D-Wave Systems
2010
Earlier work this paper cites.
T. F. Ronnow et. al., Defining and detecting quantum speedup, Science
2010
Earlier work this paper cites.
M. W. Johnson et. al., Quantum annealing with manufactured spins, Nature
2011
Earlier work this paper cites.

Similar

S. Santa et. al., MAX 2-SAT with up to 108 qubits, New Journal of Physics
2014
Cited alongside, same era.
A. Douglass et. al., Constructing SAT Filters with a Quantum Annealer, International Conference on Theory and Applications of Satisfiability Testing
2015
Cited alongside, same era.
I. Hen et al., Probing for quantum speedup in spin-glass problems with planted solutions, Physical Review A
2015
Cited alongside, same era.
T. Toda and T. Soh, Implementing Efficient All Solutions SAT Solvers, arXiv:1510.00523
Original
Cited in the paper.

Then

A. King et. al., Performance of a quantum annealer on range-limited constraint satisfaction problems, arXiv:1502.02098 (2015)
Original
2015
Later among the works it cites.
A. Roy et al., Mapping constrained optimization problems to quantum annealing with application to fault diagnosis, Frontiers in ICT 3
2016
Closest in time.
K. L. Pudenz, Parameter Setting for Quantum Annealers, 20th IEEE High Performance Embedded Computing Workshop Proceedings
2016
Closest in time.

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