Uncertain fate of fair sampling in quantum annealing
| Autor: | Helmut G. Katzgraber, Andrew J. Ochoa, Mario S. Könz, Matthias Troyer, Guglielmo Mazzola |
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| Rok vydání: | 2019 |
| Předmět: |
Physics
Quantum Physics Quantum Monte Carlo Quantum annealing FOS: Physical sciences Sampling (statistics) Disordered Systems and Neural Networks (cond-mat.dis-nn) Condensed Matter - Disordered Systems and Neural Networks 01 natural sciences 010305 fluids & plasmas Quadratic equation 0103 physical sciences Statistical physics Perturbation theory (quantum mechanics) Quantum Physics (quant-ph) 010306 general physics Degeneracy (mathematics) Quantum Sampling bias |
| Zdroj: | Physical Review A. 100 |
| ISSN: | 2469-9934 2469-9926 |
| DOI: | 10.1103/physreva.100.030303 |
| Popis: | Recently, it was demonstrated both theoretically and experimentally on the D-Wave quantum annealer that transverse-field quantum annealing does not find all ground states with equal probability. In particular, it was proposed that more complex driver Hamiltonians beyond transverse fields might mitigate this shortcoming. Here, we investigate the mechanisms of (un)fair sampling in quantum annealing. While higher-order terms can improve the sampling for selected small problems, we present multiple counterexamples where driver Hamiltonians that go beyond transverse fields do not remove the sampling bias. Using perturbation theory we explain why this is the case. In addition, we present large-scale quantum Monte Carlo simulations for spin glasses with known degeneracy in two space dimensions and demonstrate that the fair-sampling performance of quadratic driver terms is comparable to standard transverse-field drivers. Our results suggest that quantum annealing machines are not well suited for sampling applications, unless post-processing techniques to improve the sampling are applied. Comment: 6 pages, 5 figures |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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