Accelerating Tests of General Relativity with Gravitational-Wave Signals using Hybrid Sampling
POSTER
Abstract
The Advanced LIGO/Virgo interferometers have observed ~100 gravitational-wave transients
enabling new questions to be answered about relativity, astrophysics, and cosmology. However, many
of our current procedures for computing these constraints will not scale well with the increased size of
future transient catalogs. We introduce a novel hybrid sampling method in order to more efficiently
perform parameterized tests of general relativity with gravitational-wave signals. Applying our
method to the binary black hole merger GW150914 and simulated signals we find that our method
is approximately an order of magnitude more efficient than the current method with conservative
settings for our hybrid analysis. While we have focused on the specific problem of measuring
potential deviations from relativity, our method is of much wider applicability to any problem that
can be decomposed into a simple and more complex model(s).
enabling new questions to be answered about relativity, astrophysics, and cosmology. However, many
of our current procedures for computing these constraints will not scale well with the increased size of
future transient catalogs. We introduce a novel hybrid sampling method in order to more efficiently
perform parameterized tests of general relativity with gravitational-wave signals. Applying our
method to the binary black hole merger GW150914 and simulated signals we find that our method
is approximately an order of magnitude more efficient than the current method with conservative
settings for our hybrid analysis. While we have focused on the specific problem of measuring
potential deviations from relativity, our method is of much wider applicability to any problem that
can be decomposed into a simple and more complex model(s).
Presenters
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Noah E Wolfe
Massachusetts Institute of Technology
Authors
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Noah E Wolfe
Massachusetts Institute of Technology
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Colm Talbot
Massachusetts Institute of Technology
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Jacob Golomb
California Institute of Technology