Machine Learning for Understanding Quantum Systems
We are interested in deploying machine learning methods to improve the understanding of quantum systems. Given a physical system in which a subsystem is embedded in a larger system, i.e. a bath, we used neural networks to learn the generator of the subsystem’s dynamics. The network was trained with pre-simulated trajectories of Bloch vectors arising from different initial states.
Publications
Machine learning time-local generators of open quantum dynamics
Phys. Rev. Research
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2021