| Parameterized quantum circuits as machine learning models M Benedetti, E Lloyd, S Sack, M Fiorentini Quantum Science and Technology 4 (4), 043001, 2019 | 820 | 2019 |
| Avoiding barren plateaus using classical shadows SH Sack, RA Medina, AA Michailidis, R Kueng, M Serbyn PRX Quantum 3 (020365), 2022 | 100 | 2022 |
| Quantum annealing initialization of the quantum approximate optimization algorithm SH Sack, M Serbyn Quantum 5, 491, 2021 | 97 | 2021 |
| Recursive greedy initialization of the quantum approximate optimization algorithm with guaranteed improvement SH Sack, RA Medina, R Kueng, M Serbyn Physical Review A 107 (6), 062404, 2023 | 15* | 2023 |
| Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation SH Sack, DJ Egger Physical Review Research 6 (1), 013223, 2024 | 13 | 2024 |
| Entanglement-based observables for quantum impurities L Stocker, SH Sack, MS Ferguson, O Zilberberg Physical Review Research 4 (4), 043177, 2022 | 5 | 2022 |
| Elastic propagation of fast electron vortices through amorphous materials S Löffler, S Sack, T Schachinger Acta Crystallographica Section A: Foundations and Advances 75 (6), 902-910, 2019 | 5 | 2019 |
| Solving non-native combinatorial optimization problems using hybrid quantum-classical algorithms J Wurtz, S Sack, ST Wang arXiv preprint arXiv:2403.03153, 2024 | 2 | 2024 |
| Electron vortices in solids-from crystalline to amorphous materials S Löffler, S Sack, T Schachinger MC 2017 Lausanne-Microscopy Conference, 760-761, 2017 | | 2017 |
Mattia FiorentiniRigetti ComputingBestätigte E-Mail-Adresse bei rigetti.com
