Memory Formation in Adaptive Networks

Komal Bhattacharyya, David Zwicker, Karen Alim

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

The continuous adaptation of networks like our vasculature ensures optimal network performance when challenged with changing loads. Here, we show that adaptation dynamics allow a network to memorize the position of an applied load within its network morphology. We identify that the irreversible dynamics of vanishing network links encode memory. Our analytical theory successfully predicts the role of all system parameters during memory formation, including parameter values which prevent memory formation. We thus provide analytical insight on the theory of memory formation in disordered systems.

Original languageEnglish
Article number028101
JournalPhysical Review Letters
Volume129
Issue number2
DOIs
StatePublished - 8 Jul 2022

Fingerprint

Dive into the research topics of 'Memory Formation in Adaptive Networks'. Together they form a unique fingerprint.

Cite this