Gravitational Wave Source Identification

Manoj, Kovalam Lakshmi Narasimha (2016) Gravitational Wave Source Identification. Masters thesis, Indian Institute of Science Education and Research Kolkata.

PDF (MS dissertation of Kovalam Lakshmi Narasimha Manoj (11MS084)) Manoj_Kovalam-L-N-11MS084-Thesis.pdf - Submitted Version Restricted to Repository staff only Download (1MB)

Abstract

With the recent discovery of gravitational waves, we have proved what Einstein predicted decades ago, that these waves are generated by the dynamics of massive objects. It has taken us almost a century to make some theoretical development, speculation, observation and an intense experimental preparation to achieve this. The most prominent reason behind the achievement is the detector data analysis which is being carried out and the ongoing effort to increase the sensitivity of the detector. With every discovery comes the eager and curiosity to know more about it. Some of the fundamental questions surrounding the gravitational waves are tackled in this report. Some question like, What do the gravitational wave signals look like? What class of objects does the signal come from? What are the system’s physical parameters? Do we understand the physics of likely sources well enough to generate ideal, template signals? What are the underlying physical principles that determine how much information is in a gravitational wave signal? Most importantly, Can we model a gravitational wave source and use it to analyze the data we get from a gravitational wave detector? This thesis focuses on the challenges faced during the analysis of the detector data, and identifying the source of the Gravitational waves that is detected after the analysis. We are particularly interested in the binary coalescence of massive stars. A compact binary system consisting of two massive systems (Neutron stars or Black holes) loses its energy and angular momentum in the form of gravitational waves, as they orbit around their center of mass. The orbit then shrinks gradually, and this is called the inspiral phase. Using different approximation schemes one can compute the gravitational waveforms for this phase. This allows us to use data analysis techniques to estimate the parameters of the signal and in turn identify the source. This thesis presents i) The detection statistics that one need to know before signal precessing. Statistics like probability of detection, false alarms, ROC’s etc. These are essential to determine the accuracy and reliability of the detection algorithms used. ii) Detection techniques, Matched filtering in particular. Construction of waveform templates plays an essential role in the detection. iii) The need to further improve and fine tune these algorithms for future benefits.

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