| Tensorflow quantum: A software framework for quantum machine learning M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2020 | 401 | 2020 |
| Graph neural networks for particle reconstruction in high energy physics detectors X Ju, S Farrell, P Calafiura, D Murnane, L Gray, T Klijnsma, K Pedro, ... arXiv preprint arXiv:2003.11603, 2020 | 128 | 2020 |
| Traversable wormhole dynamics on a quantum processor D Jafferis, A Zlokapa, JD Lykken, DK Kolchmeyer, SI Davis, N Lauk, ... Nature 612 (7938), 51-55, 2022 | 125 | 2022 |
| Entangling quantum generative adversarial networks MY Niu, A Zlokapa, M Broughton, S Boixo, M Mohseni, V Smelyanskyi, ... Physical review letters 128 (22), 220505, 2022 | 87 | 2022 |
| Charged particle tracking with quantum annealing optimization A Zlokapa, A Anand, JR Vlimant, JM Duarte, J Job, D Lidar, M Spiropulu Quantum Machine Intelligence 3, 1-11, 2021 | 46 | 2021 |
| Tensorflow quantum: a software framework for quantum machine learning. 2020 M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2003 | 43 | 2003 |
| A deep learning model for noise prediction on near-term quantum devices A Zlokapa, A Gheorghiu arXiv preprint arXiv:2005.10811, 2020 | 40 | 2020 |
| Boundaries of quantum supremacy via random circuit sampling A Zlokapa, B Villalonga, S Boixo, DA Lidar npj Quantum Information 9 (1), 36, 2023 | 37 | 2023 |
| Quantum adiabatic machine learning by zooming into a region of the energy surface A Zlokapa, A Mott, J Job, JR Vlimant, D Lidar, M Spiropulu Physical Review A 102 (6), 062405, 2020 | 27 | 2020 |
| Tensorflow quantum: A software framework for quantum machine learning. arXiv 2020 M Broughton, G Verdon, T McCourt, AJ Martinez, JH Yoo, SV Isakov, ... arXiv preprint arXiv:2003.02989, 2003 | 25 | 2003 |
| In-Situ Observation of Phase Separation During Growth of Cs2LiLaBr6:Ce Crystals Using Energy-Resolved Neutron Imaging AS Tremsin, D Perrodin, AS Losko, SC Vogel, T Shinohara, K Oikawa, ... Crystal Growth & Design 17 (12), 6372-6381, 2017 | 23 | 2017 |
| Bayesian interpolation with deep linear networks B Hanin, A Zlokapa Proceedings of the National Academy of Sciences 120 (23), e2301345120, 2023 | 20 | 2023 |
| A quantum algorithm for training wide and deep classical neural networks A Zlokapa, H Neven, S Lloyd arXiv preprint arXiv:2107.09200, 2021 | 16 | 2021 |
| Large-scale distributed training applied to generative adversarial networks for calorimeter simulation JR Vlimant, F Pantaleo, M Pierini, V Loncar, S Vallecorsa, D Anderson, ... EPJ Web of Conferences 214, 06025, 2019 | 8 | 2019 |
| Graph neural networks for particle reconstruction in high energy physics detectors (2020) X Ju, S Farrell, P Calafiura, D Murnane, LG Prabhat, T Klijnsma, K Pedro, ... arXiv preprint arXiv:2003.11603, 0 | 5 | |
| Comment on" Comment on" Traversable wormhole dynamics on a quantum processor"" D Jafferis, A Zlokapa, JD Lykken, DK Kolchmeyer, SI Davis, N Lauk, ... arXiv preprint arXiv:2303.15423, 2023 | 4 | 2023 |
| Hamiltonian simulation for low-energy states with optimal time dependence A Zlokapa, RD Somma arXiv preprint arXiv:2404.03644, 2024 | 3 | 2024 |
| Biological error correction codes generate fault-tolerant neural networks. A Zlokapa, AK Tan, JM Martyn, M Tegmark, IL Chuang arXiv preprint arXiv:2202.12887, 2022 | 3 | 2022 |
| Quantum adiabatic machine learning with zooming A Zlokapa, A Mott, J Job, JR Vlimant, D Lidar, M Spiropulu Bulletin of the American Physical Society 66, 2021 | 2 | 2021 |
| Quantum Computing for Machine Learning and Physics Simulation A Zlokapa California Institute of Technology, 2021 | 2 | 2021 |
