Experimental characterisation of a non-Markovian quantum process
Abstract
Every quantum system is coupled to an environment. Such system-environment interaction leads to temporal correlation between quantum operations at different times, resulting in non-Markovian noise. In principle, a full characterisation of non-Markovian noise requires tomography of a multi-time processes matrix, which is both computationally and experimentally demanding. In this paper, we propose a more efficient solution. We employ machine learning models to estimate the amount of non-Markovianity, as quantified by an information-theoretic measure, with tomographically incomplete measurement. We test our model on a quantum optical experiment, and we are able to predict the non-Markovianity measure with accuracy. Our experiment paves the way for efficient detection of non-Markovian noise appearing in large scale quantum computers.
Cite
@article{arxiv.2102.01327,
title = {Experimental characterisation of a non-Markovian quantum process},
author = {K. Goswami and C. Giarmatzi and C. Monterola and S. Shrapnel and J. Romero and F. Costa},
journal= {arXiv preprint arXiv:2102.01327},
year = {2021}
}