Dynamics of Critical Cascades in Interdependent Networks

The failure of interdependent networks, as well as similar avalanche phenomena, is driven by cascading failures. At the critical point, the cascade begins as a critical branching process, where each failing node (element) triggers, on average, the failure of one other node. As nodes continue to fail, the network becomes increasingly fragile, and the branching factor grows. If the failure process does not reach extinction during its critical phase, the network undergoes an abrupt collapse. Here, we implement the analogy between this dynamic and birth-death processes to derive new analytical results and significantly optimize numerical calculations. Using this approach, we analyze three key aspects of the dynamics: the probability of collapse, the duration of avalanches, and the length of the cascading plateau phase preceding a collapse. This analysis quantifies how the system size and the intensity of the initial triggering event influence these characteristics.

Authors

Institutions

Publication Details

Journal
Physical Review Letters
Published
2025-05-07
DOI
https://doi.org/10.1103/physrevlett.134.187401
Citations
3
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamics of Critical Cascades in Interdependent Networks

Nadav M. Shnerb, Bnaya Gross, Shlomo Havlin, Dolev Dilmoney
3 citations
Physical Review Letters
Complex Network Analysis Techniques
3.97
article

Dynamics of Critical Cascades in Interdependent Networks

Nadav M. Shnerb, Bnaya Gross, Shlomo Havlin, Dolev Dilmoney
article en
3 citations

Abstract

The failure of interdependent networks, as well as similar avalanche phenomena, is driven by cascading failures. At the critical point, the cascade begins as a critical branching process, where each failing node (element) triggers, on average, the failure of one other node. As nodes continue to fail, the network becomes increasingly fragile, and the branching factor grows. If the failure process does not reach extinction during its critical phase, the network undergoes an abrupt collapse. Here, we implement the analogy between this dynamic and birth-death processes to derive new analytical results and significantly optimize numerical calculations. Using this approach, we analyze three key aspects of the dynamics: the probability of collapse, the duration of avalanches, and the length of the cascading plateau phase preceding a collapse. This analysis quantifies how the system size and the intensity of the initial triggering event influence these characteristics.

Physical Review LettersVol. 134(18)
Bar-Ilan University (IL), Universidad del Noreste (MX)
Israel Science Foundation, H2020 European Research Council
Openalex Percentile: Top 7%
Complex Network Analysis Techniques
3.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Dynamics of Critical Cascades in Interdependent Networks — Nadav M. Shnerb, Bnaya Gross, et al. · Physical Review Letters (2025) | TGRS Research Map | TGRS