# Non-Markovianity, information backflow and system-environment correlation for open-quantum-system processes

## TL;DR

This paper investigates quantum non-Markovian processes, defining conditions for Markovianity based on information backflow and system-environment correlations, and provides measures and algorithms for quantification.

## Contribution

It introduces a new quantum non-Markovianity measure aligned with classical definitions and characterizes Markovianity through IBTRES and SECE conditions.

## Key findings

- Markovian process iff no IBTRES and no SECE
- Necessary and sufficient conditions for IBTRES and SECE
- Explicit measures and algorithms for non-Markovianity

## Abstract

A Markovian process of a system is defined classically as a process in which the future state of the system is fully determined by only its present state, not by its previous history. There have been several measures of non-Markovianity to quantify the degrees of non-Markovian effect in a process of an open quantum system based on information backflow from the environment to the system. However, the condition for the witness of the system information backflow does not coincide with the classical definition of a Markovian process. Recently, a new measure with a condition that coincides with the classical definition in the relevant limit has been proposed. Here, we focus on the new definition (measure) for quantum non-Markovian processes, and characterize the Markovian condition as a quantum process that has no information backflow through the reduced environment state (IBTRES) and no system-environment correlation effect (SECE). The action of IBTRES produces non-Markovian effects by flowing the information of quantum operations performed by an experimenter at earlier times back to the system through the environment, while the SECE can produce non-Markovian effect without carrying any earlier quantum operation information. We give the necessary and sufficient conditions for no IBTRES and no SECE, respectively, and show that a process is Markovian if and only if it has no IBTRES and no SECE. The quantitative measures and algorithms for calculating non-Markovianity, IBTRES and soly-SECE are explicitly presented.