Single-particle entanglement dynamics in complex systems

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Shekhar, Devanshu, Shukla, Pragya
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866908588357713920
author Shekhar, Devanshu
Shukla, Pragya
author_facet Shekhar, Devanshu
Shukla, Pragya
contents We analyze the effect of varying system conditions on the single-particle entanglement entropy for an arbitrary eigenstate of a complex system that can be described by a multiparametric Gaussian ensemble. Our theoretical analysis leads to the identification of a single functional of the system parameters that governs the entropy dynamics. This reveals a sensitivity of the entropy to collective information content, characterized by the functional, instead of the individual system details. The functional can further be used to identify the universality classes as well as a deep web of connection underlying different quantum states.
format Preprint
id arxiv_https___arxiv_org_abs_2503_01989
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Single-particle entanglement dynamics in complex systems
Shekhar, Devanshu
Shukla, Pragya
Quantum Physics
Disordered Systems and Neural Networks
Mathematical Physics
We analyze the effect of varying system conditions on the single-particle entanglement entropy for an arbitrary eigenstate of a complex system that can be described by a multiparametric Gaussian ensemble. Our theoretical analysis leads to the identification of a single functional of the system parameters that governs the entropy dynamics. This reveals a sensitivity of the entropy to collective information content, characterized by the functional, instead of the individual system details. The functional can further be used to identify the universality classes as well as a deep web of connection underlying different quantum states.
title Single-particle entanglement dynamics in complex systems
topic Quantum Physics
Disordered Systems and Neural Networks
Mathematical Physics
url https://arxiv.org/abs/2503.01989