| Support vector machines on the D-Wave quantum annealer D Willsch, M Willsch, H De Raedt, K Michielsen Computer physics communications 248, 107006, 2020 | 183 | 2020 |
| Benchmarking the quantum approximate optimization algorithm M Willsch, D Willsch, F Jin, H De Raedt, K Michielsen Quantum Information Processing 19, 1-24, 2020 | 182 | 2020 |
| Massively parallel quantum computer simulator, eleven years later H De Raedt, F Jin, D Willsch, M Willsch, N Yoshioka, N Ito, S Yuan, ... Computer Physics Communications 237, 47-61, 2019 | 142 | 2019 |
| Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems D Willsch, M Willsch, CD Gonzalez Calaza, F Jin, H De Raedt, ... Quantum Information Processing 21 (4), 141, 2022 | 109 | 2022 |
| Benchmarking gate-based quantum computers K Michielsen, M Nocon, D Willsch, F Jin, T Lippert, H De Raedt Computer Physics Communications 220, 44-55, 2017 | 100 | 2017 |
| Gate-error analysis in simulations of quantum computers with transmon qubits D Willsch, M Nocon, F Jin, H De Raedt, K Michielsen Physical Review A 96 (6), 062302, 2017 | 67 | 2017 |
| Random state technology F Jin, D Willsch, M Willsch, H Lagemann, K Michielsen, H De Raedt Journal of the Physical Society of Japan 90 (1), 012001, 2021 | 51 | 2021 |
| Approaching remote sensing image classification with ensembles of support vector machines on the d-wave quantum annealer G Cavallaro, D Willsch, M Willsch, K Michielsen, M Riedel IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 46 | 2020 |
| GPU-accelerated simulations of quantum annealing and the quantum approximate optimization algorithm D Willsch, M Willsch, F Jin, K Michielsen, H De Raedt Computer physics communications 278, 108411, 2022 | 42 | 2022 |
| Quantum nondemolition dispersive readout of a superconducting artificial atom using large photon numbers D Gusenkova, M Spiecker, R Gebauer, M Willsch, D Willsch, F Valenti, ... Physical Review Applied 15 (6), 064030, 2021 | 41 | 2021 |
| Observation of Josephson harmonics in tunnel junctions D Willsch, D Rieger, P Winkel, M Willsch, C Dickel, J Krause, Y Ando, ... Nature Physics 20 (5), 815-821, 2024 | 40 | 2024 |
| Testing quantum fault tolerance on small systems D Willsch, M Willsch, F Jin, H De Raedt, K Michielsen Physical Review A 98 (5), 052348, 2018 | 38 | 2018 |
| Unbalanced penalization: A new approach to encode inequality constraints of combinatorial problems for quantum optimization algorithms JA Montañez-Barrera, D Willsch, A Maldonado-Romo, K Michielsen Quantum Science and Technology 9 (2), 025022, 2024 | 30 | 2024 |
| Garden optimization problems for benchmarking quantum annealers CD Gonzalez Calaza, D Willsch, K Michielsen Quantum information processing 20 (9), 305, 2021 | 30 | 2021 |
| Large-scale simulation of Shor’s quantum factoring algorithm D Willsch, M Willsch, F Jin, H De Raedt, K Michielsen Mathematics 11 (19), 4222, 2023 | 23 | 2023 |
| Supercomputer simulations of transmon quantum computers D Willsch arXiv preprint arXiv:2008.13490, 2020 | 15 | 2020 |
| Discrete-event simulation of an extended Einstein-Podolsky-Rosen-Bohm experiment H De Raedt, MS Jattana, D Willsch, M Willsch, F Jin, K Michielsen Frontiers in physics 8, 160, 2020 | 13 | 2020 |
| Einstein–Podolsky–Rosen–Bohm experiments: A discrete data driven approach H De Raedt, MI Katsnelson, MS Jattana, V Mehta, M Willsch, D Willsch, ... Annals of Physics 453, 169314, 2023 | 11 | 2023 |
| Real-time simulation of flux qubits used for quantum annealing M Willsch, D Willsch, F Jin, H De Raedt, K Michielsen Physical Review A 101 (1), 012327, 2020 | 11 | 2020 |
| Transfer learning of optimal qaoa parameters in combinatorial optimization JA Montanez-Barrera, D Willsch, K Michielsen arXiv preprint arXiv:2402.05549, 2024 | 10 | 2024 |
