Abstract
Satisfiability filters are a new and promising type of filters for set membership testing. In order to construct satisfiability filters, it is necessary to find disparate solutions to hard random kk-SAT problems. This paper compares simulated annealing, simulated quantum annealing and WalkSAT, an open-source SAT solver, in terms of their ability to find such solutions. The results indicate that solutions found by simulated quantum annealing are generally less disparate than solutions found by the other solvers and therefore less useful for the construction of satisfiability filters.
Highlights
At the beginning of the annealing schedule Γ (0) > |J...|, |hij |, so that HQA is dominated by HD and the system will be in the attainable ground state of HD with all spins pointing along x-direction, that is each variable is in a superposition between true and false
Since this paper mainly investigates what kind of solutions are found by each solver, the runtime is not considered here
The results show that the solutions found by simulated quantum annealing (SQA) lead to a higher false positive rate (FPR) than the solutions found by simulated annealing (SA) and WS
Summary
I.e. determining whether a specific element is a member of a given set in a fast and memory efficient way, is important for many applications, such as database searches. Weaver and collaborators introduced a new type of filter, called satisfiability filter [2]. The creation of a satisfiability filter relies on finding solutions to SAT problems. Our simulations use an efficient implementation of simulated quantum annealing (SQA), which has been shown to be indicative of the performance of stoquastic Quantum Annealing devices [6,7,8]. Our results indicate that the solutions found by SQA are generally less disparate than the solutions found by the other solvers, resulting in a lower efficiency of filters constructed from them. Our simulations indicate that QA shows no improvement for the construction of SAT filters.
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