| Parameterized quantum circuits as machine learning models M Benedetti, E Lloyd, S Sack, M Fiorentini Quantum science and technology 4 (4), 043001, 2019 | 1073 | 2019 |
| Avoiding barren plateaus using classical shadows SH Sack, RA Medina, AA Michailidis, R Kueng, M Serbyn PRX Quantum 3 (020365), 2022 | 150 | 2022 |
| Quantum annealing initialization of the quantum approximate optimization algorithm SH Sack, M Serbyn Quantum 5, 491, 2021 | 144 | 2021 |
| Large-scale quantum approximate optimization on nonplanar graphs with machine learning noise mitigation SH Sack, DJ Egger Physical Review Research 6 (1), 013223, 2024 | 35 | 2024 |
| 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 | 25 | 2023 |
| Entanglement-based observables for quantum impurities L Stocker, SH Sack, MS Ferguson, O Zilberberg Physical Review Research 4 (4), 043177, 2022 | 11 | 2022 |
| Solving non-native combinatorial optimization problems using hybrid quantum-classical algorithms J Wurtz, SH Sack, ST Wang IEEE Transactions on Quantum Engineering, 2024 | 6 | 2024 |
| Elastic propagation of fast electron vortices through amorphous materials S Löffler, S Sack, T Schachinger Foundations of Crystallography 75 (6), 902-910, 2019 | 5 | 2019 |
| Electron Vortices in Solids: From Crystalline to Amorphous Materials S Löffler, S Sack, T Schachinger 13th Multinational Congress on Microscopy, 58-59, 2017 | | 2017 |
Mattia FiorentiniRigetti ComputingE-mailová adresa ověřena na: rigetti.com