MAX 2-SAT with up to 108 qubits
arXiv:1307.3931 · doi:10.1088/1367-2630/16/4/045006
Abstract
We experimentally study the performance of a programmable quantum annealing processor, the D-Wave One (DW1) with up to 108 qubits, on maximum satisfiability problem with 2 variables per clause (MAX 2-SAT) problems. We consider ensembles of random problems characterized by a fixed clause density, an order parameter which we tune through its critical value in our experiments. We demonstrate that the DW1 is sensitive to the critical value of the clause density. The DW1 results are verified and compared with akmaxsat, an exact, state-of-the-art algorithm. We study the relative performance of the two solvers and how they correlate in terms of problem hardness. We find that the DW1 performance scales more favorably with problem size and that problem hardness correlation is essentially non-existent. We discuss the relevance and limitations of such a comparison.
18 pages, 23 figures
References in corpus (8)
- Mathematical Foundation of Quantum Annealing
- Minor-embedding in adiabatic quantum computation: II. Minor-universal graph design
- Simple proof of equivalence between adiabatic quantum computation and the circuit model
- Towards Fault Tolerant Adiabatic Quantum Computation
- Size dependence of the minimum excitation gap in the Quantum Adiabatic Algorithm
- The performance of the quantum adiabatic algorithm on random instances of two optimization problems on regular hypergraphs
- Noise resistance of adiabatic quantum computation using random matrix theory
- High Fidelity Adiabatic Quantum Computation via Dynamical Decoupling
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