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| dc.contributor.author |
Newling, James
|
en_ZA |
| dc.date.accessioned | 2015-01-03T18:14:21Z | |
| dc.date.available | 2015-01-03T18:14:21Z | |
| dc.date.issued | 2011 | en_ZA |
| dc.identifier.citation | Newling, J. 2011. Novel methods of supernova classification and type probability estimation. University of Cape Town. | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/11174 | |
| dc.description.abstract | 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. | en_ZA |
| dc.language.iso | eng | en_ZA |
| dc.subject.other | Maths and Applied Mathematics | en_ZA |
| dc.title | Novel methods of supernova classification and type probability estimation | en_ZA |
| dc.type | Master Thesis | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Thesis | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.department | Department of Mathematics and Applied Mathematics | en_ZA |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc | en_ZA |
| uct.type.filetype | Text | |
| uct.type.filetype | Image | |
| dc.identifier.apacitation | Newling, 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/11427/11174 | en_ZA |
| dc.identifier.chicagocitation | Newling, 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/11427/11174 | en_ZA |
| dc.identifier.vancouvercitation | Newling 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/11427/11174 | 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 |
