| Critical behavior of the quantum contact process in one dimension F Carollo, E Gillman, H Weimer, I Lesanovsky Physical review letters 123 (10), 100604, 2019 | 50 | 2019 |
| Quantum backflow states from eigenstates of the regularized current operator JJ Halliwell, E Gillman, O Lennon, M Patel, I Ramirez Journal of Physics A: Mathematical and Theoretical 46 (47), 475303, 2013 | 29 | 2013 |
| Numerical simulation of critical dissipative non-equilibrium quantum systems with an absorbing state E Gillman, F Carollo, I Lesanovsky New Journal of Physics 21 (9), 093064, 2019 | 28 | 2019 |
| Nonequilibrium Phase Transitions in ()-Dimensional Quantum Cellular Automata with Controllable Quantum Correlations E Gillman, F Carollo, I Lesanovsky Physical Review Letters 125 (10), 100403, 2020 | 23 | 2020 |
| Numerical simulation of quantum nonequilibrium phase transitions without finite-size effects E Gillman, F Carollo, I Lesanovsky Physical Review A 103 (4), L040201, 2021 | 12 | 2021 |
| Quantum and Classical Temporal Correlations in Quantum Cellular Automata E Gillman, F Carollo, I Lesanovsky Physical Review Letters 127 (23), 230502, 2021 | 11 | 2021 |
| Topological defects in quantum field theory with matrix product states E Gillman, A Rajantie Physical Review D 96 (9), 094509, 2017 | 9 | 2017 |
| Kibble Zurek mechanism of topological defect formation in quantum field theory with matrix product states E Gillman, A Rajantie Physical Review D 97 (9), 094505, 2018 | 7 | 2018 |
| Asynchronism and nonequilibrium phase transitions in -dimensional quantum cellular automata E Gillman, F Carollo, I Lesanovsky Physical Review E 106 (3), L032103, 2022 | 5 | 2022 |
| Using quantum cellular automata for exploring collective effects in large-scale quantum neural networks E Gillman, F Carollo, I Lesanovsky Physical Review E 107 (2), L022102, 2023 | 4 | 2023 |
| A tensor network approach to finite markov decision processes E Gillman, DC Rose, JP Garrahan arXiv preprint arXiv:2002.05185, 2020 | 4 | 2020 |
| Modelling nature: An introduction to mathematical modelling of natural systems E Gillman, M Gillman CABI, 2019 | 2 | 2019 |
| Combining Reinforcement Learning and Tensor Networks, with an Application to Dynamical Large Deviations E Gillman, DC Rose, JP Garrahan Physical Review Letters 132 (19), 197301, 2024 | | 2024 |
| Reinforcement Learning with Tensor Networks: Application to Dynamical Large Deviations E Gillman, DC Rose, JP Garrahan arXiv preprint arXiv:2209.14089, 2022 | | 2022 |
| Topological Defect Formation in Quantum Phase Transitions E Gillman Imperial College London, 2018 | | 2018 |
Igor LesanovskyUniversität Tübingen在 uni-tuebingen.de 的电子邮件经过验证
