Bayesian Estimation Achieves Precision Scaling for Non-Markovian Parameters

Researchers at Technische Universität Wien, the University of Basel, and the Universidad de La Laguna have overcome a longstanding difficulty in connecting noisy data from continuously monitored quantum systems to underlying parameters when those systems exhibit non-Markovian dynamics. This achievement addresses a significant challenge, as extending the theoretical framework for these systems is difficult because non-Markovian dynamics cannot be expressed as completely positive divisible maps. The team proposes a method based on reaction coordinate mapping to extend parameter-estimation techniques beyond the Markovian regime, focusing on linear systems undergoing Gaussian continuous measurements like homodyne detection. This work…