Characterizing spatial point processes by percolation transitions
A set of discrete individual points located in an embedding continuum space can be seen as percolating or non-percolating, depending on the radius of the discs/spheres associated with each of them. This problem is relevant in theoretical ecology to analyze, e.g., the spatial percolation of a tree sp...
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Veröffentlicht in: | Journal of statistical mechanics 2022-07, Vol.2022 (7), p.73202 |
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creator | Villegas, Pablo Gili, Tommaso Gabrielli, Andrea Caldarelli, Guido |
description | A set of discrete individual points located in an embedding continuum space can be seen as percolating or non-percolating, depending on the radius of the discs/spheres associated with each of them. This problem is relevant in theoretical ecology to analyze, e.g., the spatial percolation of a tree species in a tropical forest or a savanna. Here, we revisit the problem of aggregating random points in continuum systems (from 2 to 6-dimensional Euclidean spaces) to analyze the nature of the corresponding percolation transition in spatial point processes. This problem finds a natural description in terms of the canonical ensemble but not in the usual grand-canonical one, customarily employed to describe percolation transitions. This leads us to analyze the question of ensemble equivalence and study whether the resulting canonical continuum percolation transition shares its universal properties with standard percolation transitions, analyzing diverse homogeneous and heterogeneous spatial point processes. We, therefore, provide a powerful tool to characterize and classify a vast class of natural point patterns, revealing their fundamental properties based on percolation phase transitions. |
doi_str_mv | 10.1088/1742-5468/ac7a2c |
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This problem is relevant in theoretical ecology to analyze, e.g., the spatial percolation of a tree species in a tropical forest or a savanna. Here, we revisit the problem of aggregating random points in continuum systems (from 2 to 6-dimensional Euclidean spaces) to analyze the nature of the corresponding percolation transition in spatial point processes. This problem finds a natural description in terms of the canonical ensemble but not in the usual grand-canonical one, customarily employed to describe percolation transitions. This leads us to analyze the question of ensemble equivalence and study whether the resulting canonical continuum percolation transition shares its universal properties with standard percolation transitions, analyzing diverse homogeneous and heterogeneous spatial point processes. 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Stat. Mech</addtitle><description>A set of discrete individual points located in an embedding continuum space can be seen as percolating or non-percolating, depending on the radius of the discs/spheres associated with each of them. This problem is relevant in theoretical ecology to analyze, e.g., the spatial percolation of a tree species in a tropical forest or a savanna. Here, we revisit the problem of aggregating random points in continuum systems (from 2 to 6-dimensional Euclidean spaces) to analyze the nature of the corresponding percolation transition in spatial point processes. This problem finds a natural description in terms of the canonical ensemble but not in the usual grand-canonical one, customarily employed to describe percolation transitions. This leads us to analyze the question of ensemble equivalence and study whether the resulting canonical continuum percolation transition shares its universal properties with standard percolation transitions, analyzing diverse homogeneous and heterogeneous spatial point processes. We, therefore, provide a powerful tool to characterize and classify a vast class of natural point patterns, revealing their fundamental properties based on percolation phase transitions.</description><subject>cluster aggregation</subject><subject>computational biology</subject><subject>percolation problems</subject><issn>1742-5468</issn><issn>1742-5468</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1UMFKxDAUDKLgunr3mA-wbtqkTTwuRV1hwYuew8trollqE5J6WL_elop48fSGN28eM0PIdcluS6bUppSiKmrRqA2ghApPyOp3dfoHn5OLnA-M8YoJtSLb9h0S4GiT__LDG80RRg89jcEPI40poM3ZZmqONNqEoZ_oMNAxwZD9DPMlOXPQZ3v1M9fk9eH-pd0V--fHp3a7L7BSbCxspYQz0nDFZNOhdQYaQF67ToEEFIYLiaXpuFTY1WCEBKGcEA3yu05axteELX8xhZyTdTom_wHpqEum5wr0nFHPGfVSwSS5WSQ-RH0In2mYDP5__g2GE1_4</recordid><startdate>20220701</startdate><enddate>20220701</enddate><creator>Villegas, Pablo</creator><creator>Gili, Tommaso</creator><creator>Gabrielli, Andrea</creator><creator>Caldarelli, Guido</creator><general>IOP Publishing and SISSA</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0001-9154-1758</orcidid><orcidid>https://orcid.org/0000-0001-9377-3616</orcidid><orcidid>https://orcid.org/0000-0003-3705-7281</orcidid><orcidid>https://orcid.org/0000-0002-1627-3754</orcidid></search><sort><creationdate>20220701</creationdate><title>Characterizing spatial point processes by percolation transitions</title><author>Villegas, Pablo ; Gili, Tommaso ; Gabrielli, Andrea ; Caldarelli, Guido</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c280t-e284fb7b38076dcefba6ac35fd8a7ac4b347c1bd378cd5ab47a48f446c39d7e03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>cluster aggregation</topic><topic>computational biology</topic><topic>percolation problems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Villegas, Pablo</creatorcontrib><creatorcontrib>Gili, Tommaso</creatorcontrib><creatorcontrib>Gabrielli, Andrea</creatorcontrib><creatorcontrib>Caldarelli, Guido</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of statistical mechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Villegas, Pablo</au><au>Gili, Tommaso</au><au>Gabrielli, Andrea</au><au>Caldarelli, Guido</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Characterizing spatial point processes by percolation transitions</atitle><jtitle>Journal of statistical mechanics</jtitle><stitle>JSTAT</stitle><addtitle>J. Stat. Mech</addtitle><date>2022-07-01</date><risdate>2022</risdate><volume>2022</volume><issue>7</issue><spage>73202</spage><pages>73202-</pages><issn>1742-5468</issn><eissn>1742-5468</eissn><coden>JSMTC6</coden><abstract>A set of discrete individual points located in an embedding continuum space can be seen as percolating or non-percolating, depending on the radius of the discs/spheres associated with each of them. This problem is relevant in theoretical ecology to analyze, e.g., the spatial percolation of a tree species in a tropical forest or a savanna. Here, we revisit the problem of aggregating random points in continuum systems (from 2 to 6-dimensional Euclidean spaces) to analyze the nature of the corresponding percolation transition in spatial point processes. This problem finds a natural description in terms of the canonical ensemble but not in the usual grand-canonical one, customarily employed to describe percolation transitions. This leads us to analyze the question of ensemble equivalence and study whether the resulting canonical continuum percolation transition shares its universal properties with standard percolation transitions, analyzing diverse homogeneous and heterogeneous spatial point processes. We, therefore, provide a powerful tool to characterize and classify a vast class of natural point patterns, revealing their fundamental properties based on percolation phase transitions.</abstract><pub>IOP Publishing and SISSA</pub><doi>10.1088/1742-5468/ac7a2c</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0001-9154-1758</orcidid><orcidid>https://orcid.org/0000-0001-9377-3616</orcidid><orcidid>https://orcid.org/0000-0003-3705-7281</orcidid><orcidid>https://orcid.org/0000-0002-1627-3754</orcidid></addata></record> |
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subjects | cluster aggregation computational biology percolation problems |
title | Characterizing spatial point processes by percolation transitions |
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