Simulated versus reduced noise quantum annealing in maximum independent set solution to wireless network scheduling

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With the introduction of adiabatic quantum computation (AQC) and its implementation on D-Wave annealers, there has been a constant quest for benchmark problems that would allow for a fair comparison between such classical combinatorial optimization techniques as simulated annealing (SA) and AQC-based optimization. Such a benchmark case study has been the scheduling problem to avoid interference in the very specific Dirichlet protocol in wireless networking, where it was shown that the gap expansion to retain noninterference solutions benefits AQC better than SA. Here, we show that the same gap expansion allows for significant improvement in the D-Wave 2X solution compared with that of its predecessor, the D-Wave II.

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Correspondence to Edmond Jonckheere.

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This research was supported by NSF Grant CCF-1423624.

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Wang, C., Jonckheere, E. Simulated versus reduced noise quantum annealing in maximum independent set solution to wireless network scheduling. Quantum Inf Process 18, 6 (2019).

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  • Quantum computing
  • Graph theory
  • Machine learning algorithms
  • Optimal scheduling
  • Simulated annealing
  • Wireless application protocol