Speaker
Noah Pinkney
Description
We investigate and compare a number of different strategies for rapidly estimating the values of unknown Hamiltonian parameters of a quantum system. Rapid and accurate Hamiltonian parameter estimation has applications in quantum sensing, quantum control, and quantum computing. We show that an adaptive Bayesian method based on minimizing the Shannon entropy in each shot of a measurement sequence can successfully predict multiple unknown parameters more efficiently than a simple non-adaptive protocol. The adaptive protocol can be directly applied to ongoing experiments on spin qubits in double quantum dots, where multiple parameters (e.g.: exchange and magnetic fields) must be continuously estimated for good performance.
| Keyword-1 | Parameter estimation |
|---|---|
| Keyword-2 | Bayesian inference |
| Keyword-3 | Spin qubits |
Author
Noah Pinkney
Co-author
William Coish
(McGill University)
