Differential Evolution for Many-Particle Adaptive Quantum Metrology
Neil B. Lovett, Cécile Crosnier, Martí Perarnau-Llobet, Barry Cyril Sanders · Physical Review Letters · 2013
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.