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Korbinian Kottmann
Korbinian Kottmann
Xanadu
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Title
Cited by
Cited by
Year
Pennylane: Automatic differentiation of hybrid quantum-classical computations
arXiv preprint arXiv:1811.04968, 2018
7692018
Unsupervised phase discovery with deep anomaly detection
K Kottmann, P Huembeli, M Lewenstein, A Acín
Physical Review Letters 125 (17), 170603, 2020
752020
Unsupervised machine learning of topological phase transitions from experimental data
N Käming, A Dawid, K Kottmann, M Lewenstein, K Sengstock, A Dauphin, ...
Machine Learning: Science and Technology 2 (3), 035037, 2021
612021
Variational quantum anomaly detection: Unsupervised mapping of phase diagrams on a physical quantum computer
K Kottmann, F Metz, J Fraxanet, N Baldelli
Physical Review Research 3 (4), 043184, 2021
332021
Sukin Sim, Arshpreet Singh, Ingrid Strandberg, Jay Soni, Antal Száva, Slimane Thabet, Rodrigo A
V Bergholm, J Izaac, M Schuld, C Gogolin, S Ahmed, V Ajith, MS Alam, ...
Vargas-Hernández, Trevor Vincent, Nicola Vitucci, Maurice Weber, David …, 2022
282022
Supersolid-superfluid phase separation in the extended Bose-Hubbard model
K Kottmann, A Haller, A Acín, GE Astrakharchik, M Lewenstein
Physical Review B 104 (17), 174514, 2021
142021
Detecting ergodic bubbles at the crossover to many-body localization using neural networks
T Szołdra, P Sierant, K Kottmann, M Lewenstein, J Zakrzewski
Physical Review B 104 (14), L140202, 2021
132021
Unsupervised mapping of phase diagrams of 2D systems from infinite projected entangled-pair states via deep anomaly detection
K Kottmann, P Corboz, M Lewenstein, A Acín
SciPost Physics 11 (2), 025, 2021
112021
Multicritical dissipative phase transitions in the anisotropic open quantum Rabi model
G Lyu, K Kottmann, MB Plenio, MJ Hwang
arXiv preprint arXiv:2311.11346, 2023
12023
Reducing Entanglement With Physically-Inspired Fermion-To-Qubit Mappings
T Parella-Dilmé, K Kottmann, L Zambrano, L Mortimer, JS Kottmann, ...
arXiv preprint arXiv:2311.07409, 2023
12023
Evaluating analytic gradients of pulse programs on quantum computers
K Kottmann, N Killoran
https://arxiv.org/abs/2309.16756, 2023
12023
Investigating quantum many-body systems with tensor networks, machine learning and quantum computers
K Kottmann
arXiv preprint arXiv:2210.11130, 2022
2022
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