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Title: Simulation-assisted learning of open quantum systems
Models for open quantum systems, which play important roles in electron transport problems and quantum computing, must take into account the interaction of the quantum system with the surrounding environment. Although such models can be derived in some special cases, in most practical situations, the exact models are unknown and have to be calibrated. This paper presents a learning method to infer parameters in Markovian open quantum systems from measurement data. One important ingredient in the method is a direct simulation technique of the quantum master equation, which is designed to preserve the completely-positive property with guaranteed accuracy. The method is particularly helpful in the situation where the time intervals between measurements are large. The approach is validated with error estimates and numerical experiments.  more » « less
Award ID(s):
2111221
PAR ID:
10533580
Author(s) / Creator(s):
;
Publisher / Repository:
Quantum Journal
Date Published:
Journal Name:
Quantum
Volume:
8
ISSN:
2521-327X
Page Range / eLocation ID:
1407
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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