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| Hauptseite > Publikationsdatenbank > Garden optimization problems for benchmarking quantum annealers > print |
| Hauptseite > Publikationsdatenbank > Garden optimization problems for benchmarking quantum annealers > print |
| 001 | 902992 | ||
| 005 | 20230303093941.0 | ||
| 024 | 7 | _ | |a 10.1007/s11128-021-03226-6 |2 doi |
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| 037 | _ | _ | |a FZJ-2021-04738 |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Gonzalez Calaza, Carlos D. |0 P:(DE-Juel1)171436 |b 0 |e Corresponding author |
| 245 | _ | _ | |a Garden optimization problems for benchmarking quantum annealers |
| 260 | _ | _ | |a Dordrecht |c 2021 |b Springer Science + Business Media B.V. |
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| 520 | _ | _ | |a We benchmark the 5000+ qubit system coupled with the Hybrid Solver Service 2 released by D-Wave Systems Inc. in September 2020 by using a new class of optimization problems called garden optimization problems known in companion planting. These problems are scalable to an arbitrarily large number of variables and intuitively find application in real-world scenarios. We derive their QUBO formulation and illustrate their relation to the quadratic assignment problem. We demonstrate that the system and the new hybrid solver can solve larger problems in less time than their predecessors. However, we also show that the solvers based on the 2000+ qubit system sometimes produce more favourable results if they can solve the problems. |
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| 700 | 1 | _ | |a Willsch, Dennis |0 P:(DE-Juel1)167542 |b 1 |
| 700 | 1 | _ | |a Michielsen, Kristel |0 P:(DE-Juel1)138295 |b 2 |
| 773 | _ | _ | |a 10.1007/s11128-021-03226-6 |g Vol. 20, no. 9, p. 305 |0 PERI:(DE-600)2088114-9 |n 9 |p 305 |t Quantum information processing |v 20 |y 2021 |x 1570-0755 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/902992/files/GonzalezCalaza2021_Article_GardenOptimizationProblemsForB.pdf |y OpenAccess |
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