370 citations · 1.2k across the 31 of their papers we have counts for
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Reinforcement learning of quantum circuit architectures for molecular potential energy curves
Maureen Krumtünger, Alissa Wilms, Paul K. Faehrmann +4
Quantum chemistry and optimization are two of the most prominent applications of quantum computers. Variational quantum algorithms have been proposed for solving problems in these…
Maximum channel entropy principle and microcanonical channels
Philippe Faist, Sumeet Khatri
The thermal state plays a number of significant roles throughout physics, information theory, quantum computing, and machine learning. It arises from Jaynes' maximum-entropy princi…
Thermalization with partial information
Philippe Faist, Sumeet Khatri
A many-body system, whether in contact with a large environment or evolving under complex dynamics, can typically be modeled as occupying the thermal state singled out by Jaynes' m…
-Positive Maps: New Characterizations and a Generation Method
Frederik vom Ende, Sumeet Khatri, Sergey Denisov
We study -positive linear maps on matrix algebras and address two problems, (i) characterizations of -positivity and (ii) generation of non-decomposable -positive maps. On…
Quantum reinforcement learning of classical rare dynamics: Enhancement by intrinsic Fourier features
Alissa Wilms, Laura Ohff, Andrea Skolik +3
Rare events are essential for understanding the behavior of non-equilibrium and industrial systems. It is of ongoing interest to develop methods for effectively searching for rare…
Constant Overhead Entanglement Distillation via Scrambling
Andi Gu, Lorenzo Leone, Kenneth Goodenough +1
High-fidelity quantum entanglement enables key quantum networking capabilities such as secure communication and distributed quantum computing, but long-distance entanglement distri…