TY  - JOUR
AU  - Mehta, V.
AU  - Jin, F.
AU  - Michielsen, K.
AU  - De Raedt, H.
TI  - On the hardness of quadratic unconstrained binary optimization problems
JO  - Frontiers in physics
VL  - 10
SN  - 2296-424X
CY  - Lausanne
PB  - Frontiers Media
M1  - FZJ-2022-03917
SP  - 956882
PY  - 2022
AB  - 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.
LB  - PUB:(DE-HGF)16
UR  - <Go to ISI:>//WOS:000854166900001
DO  - DOI:10.3389/fphy.2022.956882
UR  - https://juser.fz-juelich.de/record/910535
ER  -