Kavli Affiliate: Ke Wang
| First 5 Authors: Ke Wang, Xiantao Li, , ,
| Summary:
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.
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