Bayesian Parameter Estimation from Gravitational Wave Signals

10/17/2011 - 3:00pm to 4:00pm
Benjamin Farr
Speaker affiliation: 
Nortwestern University
Building 78, Room 2130

Once LIGO has made its first gravitational wave detection, it can finally begin operation as a true observatory.  For the first time astronomical observations can be performed outside of the electromagnetic spectrum, and we can learn a great deal more about compact objects (e.g. neutron stars, black holes) than possible using light alone.  To be able to make these statements however, there must be a framework in place that is capable of characterizing the signals to the greatest extent that the data will allow.  Bayesian parameter estimation methods satisfy this need by providing a means to determine the full multidimensional probability density function for the parameters of the system.  In this talk I will give an introduction to gravitational waves, their sources, and characterization of these sources using Bayesian methods, with particular emphasis on Markov Chain Monte Carlo. 

PDF icon Farr_slides.pdf6.61 MB

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