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
87 * 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
41 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
25 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 Efficient distributed inner product estimation via Pauli sampling M Hinsche, M Ioannou, S Jerbi, L Leone, J Eisert, J Carrasco
arXiv preprint arXiv:2405.06544, 2024
1 2024