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Estimation of the sensitive volume for gravitational-wave source populations using weighted Monte Carlo integration

Tiwari, Vaibhav 2018. Estimation of the sensitive volume for gravitational-wave source populations using weighted Monte Carlo integration. Classical and Quantum Gravity 35 (14) , -. 10.1088/1361-6382/aac89d

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The population analysis and estimation of merger rates of compact binaries is one of the important topics in gravitational wave astronomy. The primary ingredient in these analyses is the population-averaged sensitive volume. Typically, sensitive volume, of a given search to a given simulated source population, is estimated by drawing signals from the population model and adding them to the detector data as injections. Subsequently injections, which are simulated gravitational waveforms, are searched for by the search pipelines and their signal-to-noise ratio (SNR) is determined. Sensitive volume is estimated, by using Monte-Carlo (MC) integration, from the total number of injections added to the data, the number of injections that cross a chosen threshold on SNR and the astrophysical volume in which the injections are placed. So far, only fixed population models have been used in the estimation of binary black holes (BBH) merger rates. However, as the scope of population analysis broaden in terms of the methodologies and source properties considered, due to an increase in the number of observed gravitational wave (GW) signals, the procedure will need to be repeated multiple times at a large computational cost. In this letter we address the problem by performing a weighted MC integration. We show how a single set of generic injections can be weighted to estimate the sensitive volume for multiple population models; thereby greatly reducing the computational cost. The weights in this MC integral are the ratios of the output probabilities, determined by the population model and standard cosmology, and the injection probability, determined by the distribution function of the generic injections. Unlike analytical/semi-analytical methods, which usually estimate sensitive volume using single detector sensitivity, the method is accurate within statistical errors, comes at no added cost and requires minimal computational resources.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Advanced Research Computing @ Cardiff (ARCCA)
Publisher: IOP Publishing
ISSN: 0264-9381
Date of First Compliant Deposit: 15 January 2019
Date of Acceptance: 30 May 2018
Last Modified: 20 Oct 2019 00:53

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