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dc.contributor.advisorLega, Jocelineen
dc.contributor.authorYoung, Alexander L.
dc.creatorYoung, Alexander L.en
dc.date.accessioned2017-06-30T16:09:44Z
dc.date.available2017-06-30T16:09:44Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10150/624567
dc.description.abstractComplex systems offer broad, unique research challenges due to their inability to be understood through a classic reductionist perspective, as they exhibit emergent phenomena that arise through the interactions of their components. In this thesis, we briefly review some characteristics of complex systems and the interplay of mathematical and computational methods to study them. We then discuss these approaches, how they are implemented, and how they support one another in three settings. First, we present a study that connects weather data to seasonal population-abundance of mosquitoes, using a microscopic model. Secondly, we consider the collective motions that arise in ensembles of disks interacting through non-elastic collisions and investigate how such behaviors affect macroscopic transport properties. Finally, we consider a 'self-sorting' one-dimensional collection of point-particles. In all of these cases, agent-based models and simulations are used to guide analysis, and in the final example, we explain how the simulations led to new theorems. Articles and molecular dynamics computer codes are provided as appendices.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectAgent-based modelsen
dc.subjectComplex systemsen
dc.subjectMaximum order statisticsen
dc.subjectMolecular dynamicsen
dc.titleThree Essays on Complex Systems: Self-Sorting in a One-Dimensional Gas, Collective Motion in a Two-Dimensional Ensemble of Disks, and Environment-Driven Seasonality of Mosquito Abundanceen_US
dc.typetexten
dc.typeElectronic Dissertationen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.leveldoctoralen
dc.contributor.committeememberLega, Jocelineen
dc.contributor.committeememberSethuraman, Sunderen
dc.contributor.committeememberLin, Kevinen
dc.contributor.committeememberBrio, Moyseyen
thesis.degree.disciplineGraduate Collegeen
thesis.degree.disciplineMathematicsen
thesis.degree.namePh.D.en
refterms.dateFOA2018-09-11T20:59:04Z
html.description.abstractComplex systems offer broad, unique research challenges due to their inability to be understood through a classic reductionist perspective, as they exhibit emergent phenomena that arise through the interactions of their components. In this thesis, we briefly review some characteristics of complex systems and the interplay of mathematical and computational methods to study them. We then discuss these approaches, how they are implemented, and how they support one another in three settings. First, we present a study that connects weather data to seasonal population-abundance of mosquitoes, using a microscopic model. Secondly, we consider the collective motions that arise in ensembles of disks interacting through non-elastic collisions and investigate how such behaviors affect macroscopic transport properties. Finally, we consider a 'self-sorting' one-dimensional collection of point-particles. In all of these cases, agent-based models and simulations are used to guide analysis, and in the final example, we explain how the simulations led to new theorems. Articles and molecular dynamics computer codes are provided as appendices.


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