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@ARTICLE{Mehta:910535,
      author       = {Mehta, V. and Jin, F. and Michielsen, K. and De Raedt, H.},
      title        = {{O}n the hardness of quadratic unconstrained binary
                      optimization problems},
      journal      = {Frontiers in physics},
      volume       = {10},
      issn         = {2296-424X},
      address      = {Lausanne},
      publisher    = {Frontiers Media},
      reportid     = {FZJ-2022-03917},
      pages        = {956882},
      year         = {2022},
      abstract     = {We use exact enumeration to characterize the solutions of
                      quadratic unconstrained binary optimization problems of less
                      than 21 variables in terms of their distributions of Hamming
                      distances to close-by solutions. We also perform experiments
                      with the D-Wave Advantage 5.1 quantum annealer, solving many
                      instances of up to 170-variable, quadratic unconstrained
                      binary optimization problems. Our results demonstrate that
                      the exponents characterizing the success probability of a
                      D-Wave annealer to solve a quadratic unconstrained binary
                      optimization correlate very well with the predictions based
                      on the Hamming distance distributions computed for small
                      problem instances.},
      cin          = {JSC},
      ddc          = {530},
      cid          = {I:(DE-Juel1)JSC-20090406},
      pnm          = {5111 - Domain-Specific Simulation $\&$ Data Life Cycle Labs
                      (SDLs) and Research Groups (POF4-511)},
      pid          = {G:(DE-HGF)POF4-5111},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:000854166900001},
      doi          = {10.3389/fphy.2022.956882},
      url          = {https://juser.fz-juelich.de/record/910535},
}