Deterministic phase transitions and self-organization in logistic cellular automata

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buir.contributor.authorİbrahimi, Muhamet
buir.contributor.authorGülseren, Oğuz
buir.contributor.authorJahangirov, Seymur
dc.citation.epage042216-9en_US
dc.citation.issueNumber4en_US
dc.citation.spage042216-1en_US
dc.citation.volumeNumber100en_US
dc.contributor.authorİbrahimi, Muhameten_US
dc.contributor.authorGülseren, Oğuzen_US
dc.contributor.authorJahangirov, Seymuren_US
dc.date.accessioned2020-02-11T07:32:56Z
dc.date.available2020-02-11T07:32:56Z
dc.date.issued2019
dc.departmentDepartment of Physicsen_US
dc.departmentInstitute of Materials Science and Nanotechnology (UNAM)en_US
dc.departmentInterdisciplinary Program in Neuroscience (NEUROSCIENCE)en_US
dc.departmentAysel Sabuncu Brain Research Center (BAM)en_US
dc.description.abstractWe present a simple extension in which a single parameter tunes the dynamics of cellular automata (CA) by consequently expanding their discrete state space into a Cantor set. Such an implementation serves as a potent platform for further investigation of several emergent phenomena, including deterministic phase transitions, pattern formation, autocatalysis, and self-organization. We first apply this approach to Conway's Game of Life and observe sudden changes in the asymptotic dynamics of the system accompanied by the emergence of complex propagators. Incorporation of the new state space with system features is used to explain the transitions and formulate the tuning parameter range where the propagators adaptively survive by investigating their autocatalytic local interactions. Similar behavior is present when the same recipe is applied to Rule 90, an outer totalistic elementary one-dimensional cellular automaton. In addition, the latter case shows that deterministic transitions between classes of CA can be achieved by tuning a single parameter continuously.en_US
dc.description.provenanceSubmitted by Zeynep Aykut (zeynepay@bilkent.edu.tr) on 2020-02-11T07:32:56Z No. of bitstreams: 1 Deterministic_phase_transitions_and_self_organization_in_logistic_cellular_automata.pdf: 4211969 bytes, checksum: be635fa2e167006c90ce0ce7f4d7b83d (MD5)en
dc.description.provenanceMade available in DSpace on 2020-02-11T07:32:56Z (GMT). No. of bitstreams: 1 Deterministic_phase_transitions_and_self_organization_in_logistic_cellular_automata.pdf: 4211969 bytes, checksum: be635fa2e167006c90ce0ce7f4d7b83d (MD5) Previous issue date: 2019en
dc.identifier.doi10.1103/PhysRevE.100.042216en_US
dc.identifier.issn2470-0045
dc.identifier.urihttp://hdl.handle.net/11693/53254
dc.language.isoEnglishen_US
dc.publisherAmerican Physical Societyen_US
dc.relation.isversionofhttps://dx.doi.org/10.1103/PhysRevE.100.042216en_US
dc.source.titlePhysical Review Een_US
dc.subjectChaosen_US
dc.subjectComplex systemsen_US
dc.subjectEmergence of patternsen_US
dc.subjectPhase transitionsen_US
dc.titleDeterministic phase transitions and self-organization in logistic cellular automataen_US
dc.typeArticleen_US

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