Inferring kilonova population properties with a hierarchical Bayesian framework I : Non-detection methodology and single-event analyses

Abstract

We present nimbus: a hierarchical Bayesian framework to infer the intrinsic luminosity parameters of kilonovae (KNe) associated with gravitational-wave (GW) events, based purely on non-detections. This framework makes use of GW 3-D distance information and electromagnetic upper limits from a given survey for multiple events, and self-consistently accounts for finite sky-coverage and probability of astrophysical origin. The framework is agnostic to the brightness evolution assumed and can account for multiple electromagnetic passbands simultaneously. Our analyses highlight the importance of accounting for model selection effects, especially in the context of non-detections. We show our methodology using a simple, two-parameter linear brightness model, taking the follow-up of GW190425 with the Zwicky Transient Facility (ZTF) as a single-event test case for two different prior choices of model parameters -(i) uniform/uninformative priors and (ii) astrophysical priors based on surrogate models of Monte Carlo radiative transfer simulations of KNe. We present results under the assumption that the KN is within the searched region to demonstrate functionality and the importance of prior choice. Our results show consistency with simsurvey -an astronomical survey simulation tool used previously in the literature to constrain the population of KNe. While our results based on uniform priors strongly constrain the parameter space, those based on astrophysical priors are largely uninformative, highlighting the need for deeper constraints. Future studies with multiple events having electromagnetic follow-up from multiple surveys should make it possible to constrain the KN population further.

Kilonova and Optical Afterglow from Binary Neutron Star Mergers. II. Optimal Search Strategy for Serendipitous Observations and Target-of-opportunity Observations of Gravitational-wave Triggers

“…Catching more kilonovae and afterglows by current and future survey projects would expand our knowl-edge about the population properties of these events. Kasliwal et al (2020); Mohite et al (2021) constrained the population properties of kilonovae based on the nondetection of GW-triggered follow-up observations during O3. Although the properties of kilonova and afterglow emissions from BNS and NSBH mergers can be reasonably well predicted, their low luminosities and fast evolution nature compared with supernova emission makes it difficult to detect them using the traditional timedomain survey projects.…”

Kilonova and Optical Afterglow from Binary Neutron Star Mergers. I. Luminosity Function and Color Evolution

“…It is predicted that there should exist kilonova emission diversity due to different mass ratios (e.g., Dietrich & Ujevic 2017), different kinds of merger remnant (e.g., Kasen et al 2015;Fujibayashi et al 2017;Gill et al 2019;Kawaguchi et al 2020Kawaguchi et al , 2021 and potential energy injections into the ejecta (Yu et al 2013;Metzger & Piro 2014;Ma et al 2018). The statistical analysis of kilonova emission in sGRB afterglows revealed that 3 Kasliwal et al (2020) and Mohite et al (2021) combined the results of GW detections and the non-detections of EM counterparts in O3 to constrain the kilonova luminosity function. the kilonova brightness may have a wide range of distribution and hence confirmed that kilonova emission should be diverse (Gompertz et al 2018;Ascenzi et al 2019;Rossi et al 2020;Rastinejad et al 2021).…”