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Continuum Percolation
Abstract
Many phenomena in physics, chemistry, and biology can be modelled by spatial random processes. One such process is continuum percolation, which is used when the phenomenon being modelled is made up of individual events that overlap, for example, the way individual raindrops eventually make the ground evenly wet. This is a systematic rigorous account of continuum percolation. Two models, the Boolean model and the random connection model, are treated in detail, and related continuum models are discussed. All important techniques and methods are explained and applied to obtain results on the existence of phase transitions, equality and continuity of critical densities, compressions, rarefaction, and other aspects of continuum models. This self-contained treatment, assuming only familiarity with measure theory and basic probability theory, will appeal to students and researchers in probability and stochastic geometry.
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Cited by
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Newman, M. E. J. (2003) · SIAM Review · doi:10.1137/s003614450342480 · Cited by 18,719
Stochastic geometry and random graphs for the analysis and design of wireless networks
Haenggi, M., Andrews, J. G., Baccelli, F., Dousse, O., & Franceschetti, M. (2009) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2009.090902 · Cited by 1,719
Scaling law of urban ride sharing
Tachet, R., Sagarra, O., Santi, P., Resta, G., Szell, M., Strogatz, S. H., & Ratti, C. (2017) · Scientific Reports · doi:10.1038/srep42868 · Cited by 1
Metadata
- Authors
- Meester, R., & Roy, R.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 1996-06-13
- OpenAlex
- W587813246
- Cited by
- 853
- References
- 0
- FWCI
- 4.06
- Type
- book
- Language
- en
- Open access
- closed
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- Meester, R., & Roy, R. (1996). Continuum Percolation. Cambridge University Press eBooks. https://doi.org/10.1017/cbo9780511895357
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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.