Inferring the Properties of a Population of Compact Binaries in Presence of Selection Effects
Name
2007.05579.pdf
Description
Accepted version
Size
3.32 MB
Format
Adobe PDF
Checksum (MD5)
0545cd8b8022461d3efe7785f4366b54
Author(s)
Vitale, Salvatore
Gerosa, Davide
Farr, Will M
Taylor, Stephen R
Date Issued
2021
Journal
Chapter of "Handbook of Gravitational Wave Astronomy" (Eds. C. Bambi, S. Katsanevas and K. Kokkotas; Springer Singapore, 2021)
Publisher
Springer Singapore
Citation
Vitale, Salvatore, Gerosa, Davide, Farr, Will M and Taylor, Stephen R. 2021. "Inferring the Properties of a Population of Compact Binaries in Presence of Selection Effects." Chapter of "Handbook of Gravitational Wave Astronomy" (Eds. C. Bambi, S. Katsanevas and K. Kokkotas; Springer Singapore, 2021).
Version
Author's final manuscript
Abstract
Shortly after a new class of objects is discovered, the attention shifts from
the properties of the individual sources to the question of their origin: do
all sources come from the same underlying population, or several populations
are required? What are the properties of these populations? As the detection of
gravitational waves is becoming routine and the size of the event catalog
increases, finer and finer details of the astrophysical distribution of compact
binaries are now within our grasp. This Chapter presents a pedagogical
introduction to the main statistical tool required for these analyses:
hierarchical Bayesian inference in the presence of selection effects. All key
equations are obtained from first principles, followed by two examples of
increasing complexity. Although many remarks made in this Chapter refer to
gravitational-wave astronomy, the write-up is generic enough to be useful to
researchers and graduate students from other fields.
MIT Department
Massachusetts Institute of Technology. Department of Physics
MIT Kavli Institute for Astrophysics and Space Research
LIGO (Observatory : Massachusetts Institute of Technology)
Terms of Use
Attribution-NonCommercial-ShareAlike 4.0 International
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1007/978-981-15-4702-7_45-1
