Comparing inclination dependent analyses of kilonova transients

Abstract

The detection of AT2017gfo proved that binary neutron star mergers are progenitors of kilonovae. Using a combination of numerical-relativity and radiative-transfer simulations, the community has developed sophisticated models for these transients for a wide portion of the expected parameter space. Using these simulations and surrogate models made from them, it has been possible to perform Bayesian inference of the observed signals to infer properties of the ejected matter. It has been pointed out that combining inclination constraints derived from the kilonova with gravitational-wave measurements increases the accuracy with which binary parameters can be measured and allows a more accurate inference of the Hubble Constant. In order to not introduce biases, constraints on the inclination angle for AT2017gfo should be insensitive to the employed models. In this work, we compare different assumptions about the ejecta and radiative reprocesses used by the community and we investigate their impact on the parameter inference. While most inferred parameters agree, we find disagreement between posteriors for the inclination angle for different geometries that have been used in the literature. According to our study, the inclusion of reprocessing of the photons between different ejecta types improves the modeling fits to AT2017gfo and in some cases affects the inferred constraints. Our study motivates the inclusion of large ∼ 1 mag uncertainties in the kilonova models employed for Bayesian analysis to capture yet unknown systematics, especially when inferring inclination angles, although smaller uncertainties seem appropriate to capture model systematics for other parameters. We also use this method to impose soft constraints on the ejecta geometry of the kilonova AT2017gfo.

The Challenges Ahead for Multimessenger Analyses of Gravitational Waves and Kilonova: a Case Study on GW190425

“…Secondly, information on the viewing angle is potentially obtainable from the observation of a relativistic jet, which can improve parameter estimation on systems with asymmetric outflow geometries (see, e.g., Heinzel et al 2021). Currently, the relativistic jet that is launched in some mergers (see, e.g.…”

“…In order to better understand modelling errors, our kilonova model cross-comparison should be extended to incorporate parameter inference (see, e.g. Heinzel et al 2021).…”

“…Waxman et al 2019), both the effect of the time delay between photon production and photon emergence and the gradient in the velocity are incorporated. We note, however, that the code does not take into account the asymmetric geometry of the outflows (see, e.g., Barbieri et al 2019;Bulla 2019;Kawaguchi et al 2020;Zhu et al 2020;Heinzel et al 2021, for viewing angle dependent light curve models) which can have a significant impact on the luminosity and color of the observed light curve (Bulla 2019;Darbha & Kasen 2020;Korobkin et al 2020). We also fix, for an increase in computational efficiency, 6 the nuclear heating rate to the model by Korobkin et al (2012) (with thermalization efficiency = 0.5).…”

A Broad Grid of 2D Kilonova Emission Models

“…The differences in ejecta properties seen both in simulations and in the analysis of GW170817 have motivated a broad set of additional studies of both ejecta morphology, composition, masses, and velocities (Fontes et al 2020;Tanaka et al 2020;Kawaguchi et al 2020;Krüger & Foucart 2020;Korobkin et al 2020;Barnes et al 2020;Heinzel et al 2020). These sets of detailed kilonova models that cover a broad range of the parameter space are essential in the analysis of kilonova observations.…”

Implementation of Monte-Carlo transport in the general relativistic SpEC code

“…The joint detection of gravitational waves and electromagnetic signals from the first confirmed neutron star merger observation (GW170817) Abbott et al (2017); Kasliwal et al (2017); Chornock et al (2017); Smartt et al (2017); Soares-Santos et al (2017); Cowperthwaite et al (2017) recently demonstrated the potential power of these systems to study general relativity, nuclear physics, astrophysical nucleosynthesis, and the properties of compact objects. However, theoretical uncertainties in the amount of mass ejected by a given merger Krüger & Foucart (2020) and its composition Wanajo et al (2014); Foucart et al (2018), radiation transport in that ejecta Heinzel et al (2020), the outcome of nucleosynthesis Barnes & Kasen (2013), and the energy that released by nuclear reactions in the ejecta Barnes et al (2016) limit the amount of information that we can extract from merger observations. Numerical simulations of neutron star mergers play an important role in our ability to analyze these systems.…”