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Fast follow-up using accelerated likelihood evaluation
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The calculation of posterior parameter distributions using Bayesian techniques requires repeated likelihood evaluations and can therefore be both computationally expensive and time-consuming. We will describe an approach to faster likelihood evaluation based on reduced order quadratures. A reduced spanning basis for the model space is first constructed and then a quadrature rule for that reduced basis is developed. The quadrature rule is typically cheaper to evaluate than the full likelihood, allowing accelerated follow-up. We discuss the application of these techniques to the follow-up of gravitational wave candidates identified by the LIGO interferometers.
This talk is part of the Institute of Astronomy Seminars series.
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