Adaptive Hamiltonian Estimation Using Bayesian Experimental Design

Details Adaptive Hamiltonian Estimation Using Bayesian Experimental Design Adaptive Hamiltonian Estimation Using Bayesian Experimental Design

2011-11-03

arxiv.org/abs/1111.0935v1

Physics

Quantum Physics

8 pages, 3 figures. To appear in Bayesian Inference And Maximum Entropy Methods In Science And Engineering: Proceedings of the

Scientific paper

Using Bayesian experimental design techniques, we have shown that for a single two-level quantum mechanical system under strong (projective) measurement, the dynamical parameters of a model Hamiltonian can be estimated with exponentially improved accuracy over offline estimation strategies. To achieve this, we derive an adaptive protocol which finds the optimal experiments based on previous observations. We show that the risk associated with this algorithm is close to the global optimum, given a uniform prior. Additionally, we show that sampling at the Nyquist rate is not optimal.

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