Please use this identifier to cite or link to this item:
http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/806
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Bose, Sukanta | en_US |
dc.contributor.author | KULKARNI, SUMEET | en_US |
dc.date.accessioned | 2018-04-19T04:42:15Z | |
dc.date.available | 2018-04-19T04:42:15Z | |
dc.date.issued | 2017-04 | en_US |
dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/806 | - |
dc.description.abstract | The rst observation run of advanced LIGO returned a surprising 3 detections of coalescing Binary Black Hole (BBH) systems. Having shown much promise as strong Gravitational Wave candidates lying within the aLIGO detector sensitivity, e orts are now being directed at ne-tuning our searches to detect more Compact Binary Coalescence (CBC) sources, especially ones involving Neutron Stars. A combination of algorithmic and software speedup strategies have been explored for achieving a low-latency detection of signals from these systems, to generate timely alerts for Electromagnetic Follow-up observations. In this study, we investigate another mathematical technique, called Random Projection,which guarantees the preservation of information in high-dimensional data structures under projection to a lower dimension following the Johnson-Lindenstrauss lemma. We explore the applicability of Random Projections for reducing Gravitational Wave templates in order to speed up the computation of matched filtering in the time domain. | en_US |
dc.language.iso | en | en_US |
dc.subject | 2017 | |
dc.subject | Physics | en_US |
dc.subject | Random Projections | en_US |
dc.subject | Gravitational Wave | en_US |
dc.subject | Data Analysis | en_US |
dc.title | Exploring the use of Random Projections for Gravitational Wave Data Analysis | en_US |
dc.type | Thesis | en_US |
dc.type.degree | BS-MS | en_US |
dc.contributor.department | Dept. of Physics | en_US |
dc.contributor.registration | 20121054 | en_US |
Appears in Collections: | MS THESES |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
20121054_Sumeet_Kulkarni.pdf | 9.94 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.