Quantum computational advantage via high-dimensional Gaussian boson sampling A Deshpande, A Mehta, T Vincent, N Quesada, M Hinsche, M Ioannou, ... Science advances 8 (1), eabi7894, 2022 | 85* | 2022 |
Shallow shadows: Expectation estimation using low-depth random clifford circuits C Bertoni, J Haferkamp, M Hinsche, M Ioannou, J Eisert, H Pashayan arXiv preprint arXiv:2209.12924, 2022 | 39 | 2022 |
One Gate Makes Distribution Learning Hard M Hinsche, M Ioannou, A Nietner, J Haferkamp, Y Quek, D Hangleiter, ... Physical Review Letters 130 (24), 240602, 2023 | 24 | 2023 |
Learnability of the output distributions of local quantum circuits M Hinsche, M Ioannou, A Nietner, J Haferkamp, Y Quek, D Hangleiter, ... arXiv preprint arXiv:2110.05517, 2021 | 18 | 2021 |
On the average-case complexity of learning output distributions of quantum circuits A Nietner, M Ioannou, R Sweke, R Kueng, J Eisert, M Hinsche, ... arXiv preprint arXiv:2305.05765, 2023 | 10 | 2023 |
Classical verification of quantum learning MC Caro, M Hinsche, M Ioannou, A Nietner, R Sweke arXiv preprint arXiv:2306.04843, 2023 | 8 | 2023 |
Verifiable measurement-based quantum random sampling with trapped ions M Ringbauer, M Hinsche, T Feldker, PK Faehrmann, J Bermejo-Vega, ... arXiv preprint arXiv:2307.14424, 2023 | 3 | 2023 |