Differential Evolution for Many-Particle Adaptive Quantum Metrology
Quantum Physics
2013-06-04 v2
Abstract
We devise powerful algorithms based on differential evolution for adaptive many-particle quantum metrology. Our new approach delivers adaptive quantum metrology policies for feedback control that are orders-of-magnitude more efficient and surpass the few-dozen-particle limitation arising in methods based on particle-swarm optimization. We apply our method to the binary-decision-tree model for quantum-enhanced phase estimation as well as to a new problem: a decision tree for adaptive estimation of the unknown bias of a quantum coin in a quantum walk and show how this latter case can be realized experimentally.
Cite
@article{arxiv.1304.2246,
title = {Differential Evolution for Many-Particle Adaptive Quantum Metrology},
author = {Neil B. Lovett and Cécile Crosnier and Martí Perarnau-Llobet and Barry C. Sanders},
journal= {arXiv preprint arXiv:1304.2246},
year = {2013}
}
Comments
Fig. 2(a) is the cover of Physical Review Letters Vol. 110 Issue 22