| Machine learning quantum phases of matter beyond the fermion sign problem P Broecker, J Carrasquilla, RG Melko, S Trebst Scientific reports 7 (1), 8823, 2017 | 367 | 2017 |
| Quantum phase recognition via unsupervised machine learning P Broecker, FF Assaad, S Trebst arXiv preprint arXiv:1707.00663, 2017 | 66 | 2017 |
| Rényi entropies of interacting fermions from determinantal quantum Monte Carlo simulations P Broecker, S Trebst Journal of Statistical Mechanics: Theory and Experiment 2014 (8), P08015, 2014 | 42 | 2014 |
| Numerical stabilization of entanglement computation in auxiliary-field quantum Monte Carlo simulations of interacting many-fermion systems P Broecker, S Trebst Physical Review E 94 (6), 063306, 2016 | 22 | 2016 |
| Entanglement and the fermion sign problem in auxiliary field quantum Monte Carlo simulations P Broecker, S Trebst Physical Review B 94 (7), 075144, 2016 | 16 | 2016 |
| Probing transport in quantum many-fermion simulations via quantum loop topography Y Zhang, C Bauer, P Broecker, S Trebst, EA Kim Physical Review B 99 (16), 161120, 2019 | 5 | 2019 |
| Disentangling and machine learning the many-fermion problem P Bröcker Universität zu Köln, 2018 | 1 | 2018 |
| Quantum Loop Topography for Machine Learning Transport Y Zhang, C Bauer, P Broecker, P Ginsparg, S Trebst, EA Kim Bulletin of the American Physical Society 64, 2019 | | 2019 |
