Novel methods of supernova classification and type probability estimation

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dc.contributor.authorNewling, Jamesen_ZA
dc.date.accessioned2015-01-03T18:14:21Z
dc.date.available2015-01-03T18:14:21Z
dc.date.issued2011en_ZA
dc.description.abstractFuture photometric surveys will provide vastly more supernovae than have presently been observed, the majority of which will not be spectroscopically typed. Key to extracting information from these future datasets will be the efficient use of light-curves. In the first part of this thesis we introduce two methods for distinguishing type Ia supernovae from their contaminating counterparts, kernel density estimation and boosting. In the second half of this thesis we shift focus from classification to the related problem of type probability estimation, and ask how best to use type probabilities.en_ZA
dc.identifier.apacitationNewling, J. (2011). <i>Novel methods of supernova classification and type probability estimation</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/11174en_ZA
dc.identifier.chicagocitationNewling, James. <i>"Novel methods of supernova classification and type probability estimation."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2011. http://hdl.handle.net/11427/11174en_ZA
dc.identifier.citationNewling, J. 2011. Novel methods of supernova classification and type probability estimation. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Newling, James AB - Future photometric surveys will provide vastly more supernovae than have presently been observed, the majority of which will not be spectroscopically typed. Key to extracting information from these future datasets will be the efficient use of light-curves. In the first part of this thesis we introduce two methods for distinguishing type Ia supernovae from their contaminating counterparts, kernel density estimation and boosting. In the second half of this thesis we shift focus from classification to the related problem of type probability estimation, and ask how best to use type probabilities. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - Novel methods of supernova classification and type probability estimation TI - Novel methods of supernova classification and type probability estimation UR - http://hdl.handle.net/11427/11174 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/11174
dc.identifier.vancouvercitationNewling J. Novel methods of supernova classification and type probability estimation. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/11174en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Mathematics and Applied Mathematicsen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMaths and Applied Mathematicsen_ZA
dc.titleNovel methods of supernova classification and type probability estimationen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMScen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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