Optimizing qubit Hamiltonian parameter estimation algorithms using PSO
Quantum Physics
2012-10-17 v1
Abstract
We develop qubit Hamiltonian single parameter estimation techniques using a Bayesian approach. The algorithms considered are restricted to projective measurements in a fixed basis, and are derived under the assumption that the qubit measurement is much slower than the characteristic qubit evolution. We optimize a non-adaptive algorithm using particle swarm optimization (PSO) and compare with a previously-developed locally-optimal scheme.
Cite
@article{arxiv.1206.3830,
title = {Optimizing qubit Hamiltonian parameter estimation algorithms using PSO},
author = {Alexandr Sergeevich and Stephen D. Bartlett},
journal= {arXiv preprint arXiv:1206.3830},
year = {2012}
}
Comments
3 pages, 2 figures, presented at 2012 IEEE Congress on Evolutionary Computation, to be published in the proceedings