The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Robustness of a network formed byninterdependent networks with a one-to-one correspondence of dependent nodes
Open accessAbstract
Many real-world networks interact with and depend upon other networks. We develop an analytical framework for studying a network formed by n fully interdependent randomly connected networks, each composed of the same number of nodes N. The dependency links connecting nodes from different networks establish a unique one-to-one correspondence between the nodes of one network and the nodes of the other network. We study the dynamics of the cascades of failures in such a network of networks (NON) caused by a random initial attack on one of the networks, after which a fraction p of its nodes survives. We find for the fully interdependent loopless NON that the final state of the NON does not depend on the dynamics of the cascades but is determined by a uniquely defined mutual giant component of the NON, which generalizes both the giant component of regular percolation of a single network (n=1) and the recently studied case of the mutual giant component of two interdependent networks (n=2). We also find that the mutual giant component does not depend on the topology of the NON and express it in terms of generating functions of the degree distributions of the network. Our results show that, for any n≥2 there exists a critical p=p(c)>0 below which the mutual giant component abruptly collapses from a finite nonzero value for p≥p(c) to zero for p 2, a RR NON is stable for any n with p(c)<1). This results arises from the critical role played by singly connected nodes which exist in an ER NON and enhance the cascading failures, but do not exist in a RR NON.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Newman, M. (2010) · doi:10.1093/acprof:oso/9780199206650.001.0001 · Cited by 6,595
Identifying, understanding, and analyzing critical infrastructure interdependencies
(2001) · IEEE Control Systems · doi:10.1109/37.969131 · Cited by 2,851
Dynamical Processes on Complex Networks
Barrat, A., Barthélemy, M., & Vespignani, A. (2008) · doi:10.1017/cbo9780511791383 · Cited by 2,704 · cited 1×
“Our results show that, for any n 2 there exists a critical p = pc > 0 below which the mutual giant component abruptly collapses from a finite nonzero value for p pc to zero for p pc, as in a first-order phase transition.”
BackgroundDorogovtsev, S. N., & Mendes, J. F. F. (2003) · doi:10.1093/acprof:oso/9780198515906.001.0001 · Cited by 1,563
Cited by
Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014) · Journal of Complex Networks · doi:10.1093/comnet/cnu016 · Cited by 3,235
The structure and dynamics of multilayer networks
Boccaletti, S., Bianconi, G., Criado, R., del Genio, C. I., Gómez-Gardeñes, J., Romance, M., Sendiña-Nadal, I., Wang, Z., & Zanin, M. (2014) · Physics Reports · doi:10.1016/j.physrep.2014.07.001 · Cited by 3,125
Interdependent network reciprocity in evolutionary games
Wang, Z., Szolnoki, A., & Perc, M. (2013) · Scientific Reports · doi:10.1038/srep01183 · Cited by 485
Evolution of Cooperation in Multiplex Networks
Gómez-Gardeñes, J., Reinares, I., Arenas, A., & Floría, L. M. (2012) · Scientific Reports · doi:10.1038/srep00620 · Cited by 462
Optimal interdependence between networks for the evolution of cooperation
Wang, Z., Szolnoki, A., & Perc, M. (2013) · Scientific Reports · doi:10.1038/srep02470 · Cited by 311
Metadata
- Authors
- Gao, J., Buldyrev, S. V., Havlin, S., & Stanley, H. E.
- Venue
- Physical Review E
- Publisher
- American Physical Society (APS)
- Published
- 2012-06-29
- Volume
- 85
- Issue
- 6
- Pages
- 066134-066134
- ISSN
- 1539-3755 (ISSN-L)
- 1550-2376
- OpenAlex
- W1555596743
- Cited by
- 237
- References
- 5
- FWCI
- 18.98
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Robustness of a network formed byninterdependent networks with a one-to-one correspondence of dependent nodes. https://app.cochat.ai/papers/10.1103/physreve.85.066134
- The paper
- Gao, J., Buldyrev, S. V., Havlin, S., & Stanley, H. E. (2012). Robustness of a network formed byninterdependent networks with a one-to-one correspondence of dependent nodes. Physical Review E. https://doi.org/10.1103/physreve.85.066134
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.