1,472 research outputs found
IYV Global Evaluation
This is a report on the global evaluation of the International Year of Volunteers (IYV)
UK-wide evaluation of the Millennium Volunteers Programme
The Millennium Volunteers programme is a UK-wide government supported initiative designed to promote sustained volunteering among young people aged 16-24
An Efficient Approximation to the Likelihood for Gravitational Wave Stochastic Background Detection Using Pulsar Timing Data
Direct detection of gravitational waves by pulsar timing arrays will become
feasible over the next few years. In the low frequency regime ( Hz --
Hz), we expect that a superposition of gravitational waves from many
sources will manifest itself as an isotropic stochastic gravitational wave
background. Currently, a number of techniques exist to detect such a signal;
however, many detection methods are computationally challenging. Here we
introduce an approximation to the full likelihood function for a pulsar timing
array that results in computational savings proportional to the square of the
number of pulsars in the array. Through a series of simulations we show that
the approximate likelihood function reproduces results obtained from the full
likelihood function. We further show, both analytically and through
simulations, that, on average, this approximate likelihood function gives
unbiased parameter estimates for astrophysically realistic stochastic
background amplitudes.Comment: 10 pages, 3 figure
Searching for Gravitational Waves Using Pulsar Timing Arrays
Gravitational Waves (GWs) are tiny ripples in the fabric of spacetime predicted by Einstein\u27s theory of General Relativity. Pulsar timing arrays (PTAs) offer a unique opportunity to detect low frequency GWs in the near future. Such a detection would be complementary to both LISA and LIGO GW efforts. In this frequency band, the expected source of GWs are Supermassive Black Hole Binaries (SMBHBs) that will most likely form an ensemble creating a stochastic GW background with possibly a few nearby/massive sources that will be individually resolvable. A direct detection of GWs will open a new window into the fields of astronomy and astrophysics by allowing us to constrain the coalescence rate of SMBHBs, providing us with further tests on the theory of General Relativity, and giving us access to properties of black holes not accessible by current astronomical techniques.
This dissertation work focuses primarily on the development of several robust data analysis pipelines for the detection and characterization of continuous GWs and a stochastic GW background. The data analysis problem for PTAs is quite difficult as one must fully take into account the timing model that must be fit in order to obtain the residuals, uneven sampling (including large gaps), and potential red noise processes. The data analysis techniques presented here handle all of these effects completely while allowing additional freedom in parameterizing the noise present in the data. The accumulation of work from this dissertation has resulted in a fully functional, robust, and efficient data analysis pipeline that has been successfully applied to the 5- and 9-year NANOGrav data releases
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