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Area of Science:

  • Computational physics
  • Optimization algorithms
  • Quantum computing

Background:

  • Quantum annealing has inspired specialized solvers for unconstrained binary quadratic programming (UBQP).
  • Understanding solver performance across diverse problem types is crucial for their advancement and application.
  • Benchmarking is essential to identify strengths and weaknesses of different UBQP solvers.

Purpose of the Study:

  • To benchmark and compare the performance of four UBQP solvers.
  • To identify which solver performs best on specific types of UBQP instances.
  • To provide insights into the practical applicability of different quantum-inspired optimization techniques.

Main Methods:

  • Performance evaluation of D-Wave Hybrid Solver Service (HSS), Toshiba Simulated Bifurcation Machine (SBM), Fujitsu Digital Annealer (DA), and personal computer simulated annealing.
  • Benchmarking utilized MQLib instances, random not-all-equal 3-SAT (NAE 3-SAT) at the SAT-UNSAT phase transition, and the Ising spin glass Sherrington-Kirkpatrick (SK) model.
  • Comparative analysis of solution quality and/or speed across different problem classes.

Main Results:

  • D-Wave HSS demonstrated superior performance on MQLib instances.
  • Fujitsu DA achieved the best performance on NAE 3-SAT problems.
  • Toshiba SBM ranked first for the SK model instances.

Conclusions:

  • The performance of UBQP solvers varies significantly depending on the problem structure.
  • Each solver exhibits distinct strengths, with HSS, DA, and SBM excelling in different domains.
  • These findings aid in selecting the appropriate solver for specific optimization challenges.