Measure for the degree of non-markovian behavior of quantum processes in open systems.

By H. Breuer, Elsi-Mari Laine, Jyrki Piilo. Physical Review Letters, 2009

1,224 citations recorded by the source corpus.

We construct a general measure for the degree of non-Markovian behavior in open quantum systems. This measure is based on the trace distance which quantifies the distinguishability of quantum states. It represents a functional of the dynamical map describing the time evolution of physical states, and can be interpreted in terms of the information flow between the open system and its environment. The measure takes on nonzero values whenever there is a flow of information from the environment back to the open system, which is the key feature of non-Markovian dynamics.

Subfields: Artificial Intelligence, Atomic and Molecular Physics, and Optics

View Paper: https://www.semanticscholar.org/paper/154fd293b4548f0a5a5e365cf1f9319862a09ec3

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In Atomic and Molecular Physics, and Optics

Citations in the corpus

Quantum speed limits: from Heisenberg’s uncertainty principle to optimal quantum control (2017, background): “It has been seen [147] that for Markovian dynamics all initial states monotonically converge towards a unique stationary state.”
Concepts of quantum non-Markovianity: A hierarchy (2017, methodology): “Decreasing system distinguishability has been broadly interpreted in terms of ‘information’ flowing from the system into its environment, but not vice versa, implying that the environment cannot store and later feed back information to the system about its earlier history [14, 20].”
Training Schrödinger’s cat: quantum optimal control (2015, background): “Reachability is expected to be larger for non-Markovian dynamics since nonMarkovianity implies information back-flow from the environment to the system [53].”
Detecting crosstalk errors in quantum information processors (2019, neutral): “[12, 8, 59, 3, 32, 60].”
Dynamics of non-Markovian open quantum systems (2015, background): “Similarly, Breuer et al. (2009) developed an alternative derivation which considers as non-Markovian those systems in which there is a back-flow of information from the environment to the system during the dynamics.”