27 citations · 119 across the 12 of their papers we have counts for
4 papers · 1 filter
Machine learning phase transitions: Connections to the Fisher information
Julian Arnold, Niels Lörch, Flemming Holtorf +1
Despite the widespread use and success of machine-learning techniques for detecting phase transitions from data, their working principle and fundamental limits remain elusive. Here…
Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion
Julian Arnold, Frank Schäfer, Niels Lörch
Machine learning has been successfully used to study phase transitions. One of the most popular approaches to identifying critical points from data without prior knowledge of the u…
Mapping out phase diagrams with generative classifiers
Julian Arnold, Frank Schäfer, Alan Edelman +1
One of the central tasks in many-body physics is the determination of phase diagrams. However, mapping out a phase diagram generally requires a great deal of human intuition and un…
Performance Bounds for Quantum Feedback Control
Flemming Holtorf, Frank Schäfer, Julian Arnold +2
The limits of quantum feedback control have immediate consequences for quantum information science at large, yet remain largely unexplored. Here, we combine quantum filtering theor…