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CATEGORIES:Data Intensive Science Seminar Series
SUMMARY:Bayesian inference with likelihood reweighting: mo
tivation\, method\, and application to gravitation
al-wave astrophysics - Isobel Romero-Shaw (DAMTP)
DTSTART;TZID=Europe/London:20221110T130000
DTEND;TZID=Europe/London:20221110T143000
UID:TALK177434AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/177434
DESCRIPTION:Bayesian inference is the workhorse of gravitation
al-wave astrophysics. By analysing a gravitational
-wave signal with computational Bayesian methods\,
we obtain a posterior probability distribution th
e high-dimensional parameter space that describes
its source. This relies on computationally-intensi
ve models for the signal\, which must be sufficien
tly efficient that they can be evaluated hundreds
of thousands of times per event. In the case that
the model is not sufficiently efficient\, there is
a shortcut: likelihood reweighting. In this talk\
, I introduce Bayes theorem and show how it is imp
lemented for gravitational-wave astrophysics. I de
monstrate the logic behind likelihood reweighting\
, and explore the different situations in which it
can be useful. I also give examples of the succes
sful use of likelihood reweighting to measure the
properties of gravitational-wave sources.
LOCATION:Hoyle Lecture Theatre\, Institute of Astronomy\, M
adingley Rise
CONTACT:James Fergusson
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