| Name: | Neev Shah |
| Affiliation: | Indian Institute of Science Education and Research, Pune |
| Conference ID : | ASI2024_474 |
| Title : | Population Inference of Merging Compact Binaries in the Presence of Lensing |
| Authors : | Neev Shah1,2, Mukesh Kumar Singh2, Parameswaran Ajith2 |
| Authors Affiliation: | 1 Indian Institute of Science Education and Research, Pune - 411008, India
2 International Centre for Theoretical Sciences, TIFR, Bangalore - 560089, India |
| Mode of Presentation: | Poster |
| Abstract Category : | High Energy Phenomena, Fundamental Physics and Astronomy |
| Abstract : | Gravitational lensing due to intervening matter such as clusters or galaxies can (de)magnify a gravitational-wave (GW) event, leading to a biased measurement of the source mass and redshift. Hierarchical inference on the detected GW events can be performed to estimate the population properties of binary black holes, such as their underlying mass and redshift distributions. These distributions provide vital information about the properties of black holes, their progenitors and their formation channels. Currently, it is assumed that the detected events are not significantly magnified due to their low lensing probability, hence effects of lensing are not accounted for in population inference analyses. When the lensing probability is higher (as expected for future detectors), this can bias our estimation of the population hyper-parameters. In this work, we develop a Bayesian hierarchical inference formalism to estimate the true population hyper-parameters of the GW sources as well as lenses.
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