# Robust online Hamiltonian learning

@article{Granade2013RobustOH, title={Robust online Hamiltonian learning}, author={Christopher E. Granade and Christopher Ferrie and Nathan Wiebe and David G. Cory}, journal={New Journal of Physics}, year={2013}, volume={14} }

In this work we combine two distinct machine learning methodologies, sequential Monte Carlo and Bayesian experimental design, and apply them to the problem of inferring the dynamical parameters of a quantum system. We design the algorithm with practicality in mind by including parameters that control trade-offs between the requirements on computational and experimental resources. The algorithm can be implemented online (during experimental data collection), avoiding the need for storage and…

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