Towards provably efficient quantum algorithms for large-scale machine-learning models J Liu, M Liu, JP Liu, Z Ye, Y Alexeev, J Eisert, L Jiang Nature Communications 15, 434, 2023 | 26 | 2023 |
Classical algorithm for simulating experimental Gaussian boson sampling C Oh, M Liu, Y Alexeev, B Fefferman, L Jiang Nature Physics, 2024 | 23* | 2024 |
Simulating lossy Gaussian boson sampling with matrix-product operators M Liu, C Oh, J Liu, L Jiang, Y Alexeev Phys Rev A 108 (5), 052604, 2023 | 16* | 2023 |
Estimating the randomness of quantum circuit ensembles up to 50 qubits M Liu, J Liu, Y Alexeev, L Jiang npj Quantum Information 8, 137, 2022 | 12 | 2022 |
Embedding learning in hybrid quantum-classical neural networks M Liu, J Liu, R Liu, H Makhanov, D Lykov, A Apte, Y Alexeev 2022 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2022 | 9 | 2022 |
Experimental implementation of wavefront sensorless real-time adaptive optics aberration correction control loop with a neural network M Liu, DN Lopez, GC Spalding Emerging Topics in Artificial Intelligence 2020 11469, 59-67, 2020 | 3 | 2020 |
The computational power of random quantum circuits in arbitrary geometries M DeCross, R Haghshenas, M Liu, Y Alexeev, CH Baldwin, JP Bartolotta, ... arXiv preprint arXiv:2406.02501, 2024 | 1 | 2024 |
Stochastic Approach for Simulating Quantum Noise Using Tensor Networks W Berquist, D Lykov, M Liu, Y Alexeev 2022 IEEE/ACM Third International Workshop on Quantum Computing Software …, 2022 | 1 | 2022 |
Exploration of quantum machine learning and ai accelerators for fusion science M Liu, G Dong, KG Felker, M Otten, P Balaprakash, W Tang, Y Alexeev Argonne National Lab.(ANL), Argonne, IL (United States), 2022 | 1 | 2022 |