Experimental characterization of a non-Markovian quantum process
Kaumudibikash Goswami, Christina Giarmatzi, Christopher Monterola, Sally Shrapnel, Jacquiline Romero, Fabio Costa
Abstract
Most noise-characterization methods for quantum technologies assume Markovianity, meaning that the environment and the system have no memory of their interactions with each other, because it is inefficient and computationally demanding to take temporal correlations into account. Here, the authors propose a more efficient machine learning method for estimating non-Markovian noise and implement it in a proof-of-principle quantum optics experiment.
Topics & Concepts
Characterization (materials science)Markov processNoise (video)Computer scienceMeaning (existential)Process (computing)QuantumStatistical physicsQuantum technologyQuantum processTheoretical computer scienceOpen quantum systemArtificial intelligenceQuantum mechanicsMathematicsPhysicsQuantum dynamicsOpticsEpistemologyPhilosophyImage (mathematics)Operating systemStatisticsQuantum Information and CryptographyQuantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications