QAGAs employ reverse quantum annealing for mutations and classical crossovers, outperforming standard quantum annealing at locating global optima on spin-glass instances using the D-Wave 2000Q.
Optimized simulated annealing for Ising spin glasses
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abstract
We present several efficient implementations of the simulated annealing algorithm for Ising spin glasses on sparse graphs. In particular, we provide a generic code for any choice of couplings, an optimized code for bipartite graphs, and highly optimized implementations using multi-spin coding for graphs with small maximum degree and discrete couplings with a finite range. The latter codes achieve up to 50 spin flips per nanosecond on modern Intel CPUs. We also compare the performance of the codes to that of the special purpose D-Wave devices built for solving such Ising spin glass problems.
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Quantum-Assisted Genetic Algorithm
QAGAs employ reverse quantum annealing for mutations and classical crossovers, outperforming standard quantum annealing at locating global optima on spin-glass instances using the D-Wave 2000Q.