Characterization of the measurement uncertainty dynamics in an open system

TL;DR

This paper studies how environmental noise affects the evolution of quantum measurement uncertainty, specifically von Neumann entropy, in open systems, and proposes strategies to mitigate this uncertainty.

Contribution

It analyzes the impact of AD and BPF noise channels on quantum entropy uncertainty and suggests methods to reduce measurement uncertainty in open quantum systems.

Findings

Environmental noise increases entropy uncertainty over time.

AD and BPF channels differently influence the uncertainty dynamics.

Proposed strategies effectively reduce measurement uncertainty.

Abstract

Uncertainty principle plays a crucial role in quantum mechanics, because it captures the essence of the inevitable randomness associated with the outcomes of two incompatible quantum measurements. Information entropy can perfectly describe this type of randomness in information theory, because entropy can measure the degree of chaos in a given quantum system. However, the quantum-assisted uncertainty of entropy eventually inflate inevitably as the quantum correlations of the system are progressively corrupted by noise from the surrounding environment. In this paper, we investigate the dynamical features of the von Neumann entropic uncertainty in the presence of quantum memory, exploring the time evolution of entropic uncertainty suffer noise from the surrounding. Noteworthily, how the environmental noises affect the uncertainty of entropy is revealed, and specifically we verify how two types of noise environments, AD channel and BPF channel, influence the uncertainty. Meanwhile, we put forward some effective operation strategies to reduce the magnitude of the measurement uncertainty under the open systems. Furthermore, we explore the applications of the uncertainty relation investigated on entanglement witness and quantum channel capacity. Therefore , in open quantum correlation systems, our investigations could provide an insight into quantum measurement estimation