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  STROOPWAFEL: Simulating rare outcomes from astrophysical populations, with application to gravitational-wave sources

Broekgaarden, F. S., Justham, S., de Mink, S. E., Gair, J., Mandel, I., Stevenson, S., et al. (2019). STROOPWAFEL: Simulating rare outcomes from astrophysical populations, with application to gravitational-wave sources. Monthly notices of the Royal Astronomical Society, 490(4), 5228-5248. doi:10.1093/mnras/stz2558.

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 Creators:
Broekgaarden, Floor S., Author
Justham, Stephen, Author
de Mink, Selma E., Author
Gair, Jonathan1, Author           
Mandel, Ilya, Author
Stevenson, Simon, Author
Barrett, Jim W., Author
Vigna-Gómez, Alejandro, Author
Neijssel, Coenraad2, Author           
Affiliations:
1Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society, ou_1933290              
2Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society, ou_24011              

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Free keywords: Astrophysics, High Energy Astrophysical Phenomena, astro-ph.HE, Astrophysics, Instrumentation and Methods for Astrophysics, astro-ph.IM, Astrophysics, Solar and Stellar Astrophysics, astro-ph.SR, Physics, Data Analysis, Statistics and Probability, physics.data-an
 Abstract: Gravitational-wave observations of double compact object (DCO) mergers are
providing new insights into the physics of massive stars and the evolution of
binary systems. Making the most of expected near-future observations for
understanding stellar physics will rely on comparisons with binary population
synthesis models. However, the vast majority of simulated binaries never
produce DCOs, which makes calculating such populations computationally
inefficient. We present an importance sampling algorithm, STROOPWAFEL, that
improves the computational efficiency of population studies of rare events, by
focusing the simulation around regions of the initial parameter space found to
produce outputs of interest. We implement the algorithm in the binary
population synthesis code COMPAS, and compare the efficiency of our
implementation to the standard method of Monte Carlo sampling from the birth
probability distributions. STROOPWAFEL finds $\sim$25-200 times more DCO
mergers than the standard sampling method with the same simulation size, and so
speeds up simulations by up to two orders of magnitude. Finding more DCO
mergers automatically maps the parameter space with far higher resolution than
when using the traditional sampling. This increase in efficiency also leads to
a decrease of a factor $\sim$3-10 in statistical sampling uncertainty for the
predictions from the simulations. This is particularly notable for the
distribution functions of observable quantities such as the black hole and
neutron star chirp mass distribution, including in the tails of the
distribution functions where predictions using standard sampling can be
dominated by sampling noise.

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 Dates: 2019-05-022019
 Publication Status: Issued
 Pages: Submitted. Data and the code for the STROOPWAFEL algorithm will be made publicly available after acceptance. Early inquiries can be addressed to the lead author
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Degree: -

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Title: Monthly notices of the Royal Astronomical Society
Source Genre: Journal
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Pages: - Volume / Issue: 490 (4) Sequence Number: - Start / End Page: 5228 - 5248 Identifier: -