Local Information Flow in Quantum Quench Dynamics

TL;DR

This paper introduces a local information lattice framework to analyze quantum information flow in out-of-equilibrium one-dimensional systems after a quench, revealing detailed local correlation structures and topological effects.

Contribution

It develops a scale- and space-resolved method for studying quantum information dynamics, applicable to various systems, and uncovers local signatures of topological edge modes and fractional entropy.

Findings

Revealed local correlation buildup in fermionic chains after quenches.

Identified signatures of topological edge modes in information flow.

Explained fractional von Neumann entropy in Majorana protocols.

Abstract

We investigate the out-of-equilibrium dynamics of quantum information in one-dimensional systems undergoing a quantum quench using a local perspective based on the information lattice. This framework provides a scale- and space-resolved decomposition of quantum correlations, enabling a hydrodynamic description of the information flow through well-defined local densities -- termed local information -- and currents. We apply this framework to three local quenches in noninteracting fermionic chains: (i) the release of a single particle into an empty tight-binding chain, (ii) the connection of two critical chains via the removal of a central barrier, and (iii) the coupling of a topological Kitaev chain to a critical chain. In each case, the information lattice reveals the local structure of correlation buildup and information interface effects, going beyond global measures such as the von Neumann entropy. In particular, through the information lattice we uncover the signatures in the local information flow associated with topological edge modes and analytically explain the fractional von Neumann entropy values observed in Majorana quench protocols. Our approach is general and applicable to interacting, disordered, and open systems, providing a powerful tool for characterizing quantum information dynamics.