ArticleNature communications2025
Hybrid universality classes of systemic cascades.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Temporal self-similarity reveals percolation universality classes in complex networks.Nature communications · 2026Article
- Recent Progress on Hybrid Percolation Transitions.Entropy (Basel, Switzerland) · 2026Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Cascades are self-reinforcing processes underlying the systemic risk of many complex systems. Understanding the universal aspects of these phenomena is of fundamental interest, yet typically bound to numerical observations in ad-hoc models and limited insights. Here, we develop a unifying approach that reveals two distinct universality classes of cascades determined by the global symmetry of the cascading process. We provide hyperscaling arguments predicting hybrid critical phenomena characterized by a combination of both mean-field spinodal exponents and d-dimensional corrections, and show how parity invariance influences the geometry and lifetime of critical avalanches. Our theory applies to a wide range of networked systems in arbitrary dimensions, as we demonstrate by simulations encompassing classic and novel cascade models, revealing universal principles of cascade critical phenomena amenable to experimental validation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.