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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
10972018
Unsupervised phase discovery with deep anomaly detection
K Kottmann, P Huembeli, M Lewenstein, A Acín
Physical Review Letters 125 (17), 170603, 2020
912020
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
852021
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
412021
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
192021
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
172021
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
162021
Multicritical dissipative phase transitions in the anisotropic open quantum Rabi model
G Lyu, K Kottmann, MB Plenio, MJ Hwang
Phys. Rev. Research 6, 033075, 2024
62024
Reducing entanglement with physically inspired fermion-to-qubit mappings
T Parella-Dilmé, K Kottmann, L Zambrano, L Mortimer, JS Kottmann, ...
PRX Quantum 5 (3), 030333, 2024
52024
Evaluating analytic gradients of pulse programs on quantum computers
K Kottmann, N Killoran
https://arxiv.org/abs/2309.16756, 2023
32023
METHODS AND SYSTEMS FOR ESTIMATING A GRADIENT, AND METHODS AND SYSTEMS FOR CONSTRUCTING A PULSE PROGRAM
N Killoran, K Kottmann
US Patent App. 18/597,311, 2025
2025
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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