Related papers: Kilonova modelling and parameter inference: Unders…
The kilonova (KN) associated with the binary neutron star (BNS) merger GW170817 is the only known electromagnetic counterpart to a gravitational wave source. Here we produce a sequence of radiative transfer models (using $\textsc{tardis}$)…
Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model…
The joint detection of the gravitational wave GW170817, of the short $\gamma$-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star merger observed on August 17, 2017, is a milestone in multimessenger…
Fitting a simplifying model with several parameters to real data of complex objects is a highly nontrivial task, but enables the possibility to get insights into the objects physics. Here, we present a method to infer the parameters of the…
In Hezaveh et al. 2017 we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for…
We present a rapid analytic framework for predicting kilonova light curves following neutron star (NS) mergers, where the main input parameters are binary-based properties measurable by gravitational wave detectors (chirp mass and mass…
In recent years, there have been significant advances in multi-messenger astronomy due to the discovery of the first, and so far only confirmed, gravitational wave event with a simultaneous electromagnetic (EM) counterpart, as well as…
The coalescence of a binary neutron star (BNS) pair is expected to produce gravitational waves (GW) and electromagnetic (EM) radiation, both of which may be detectable with currently available instruments. We describe a search for a…
With the increasing sensitivity of advanced gravitational wave detectors, the first joint detection of an electromagnetic and gravitational wave signal from a compact binary merger will hopefully happen within this decade. However, current…
Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using…
All 21-cm signal experiments rely on electronic receivers that affect the data via both multiplicative and additive biases through the receiver's gain and noise temperature. While experiments attempt to remove these biases, the residuals of…
Eclipsing binaries provide one of the most direct mechanisms for measuring stellar properties such as mass and radius, but historically, determining these properties has been non-trivial and computationally prohibitive. As such, only a…
The Wide-Field Infrared Transient Explorer (WINTER) is a new 1 $\text{deg}^2$ seeing-limited time-domain survey instrument designed for dedicated near-infrared follow-up of kilonovae from binary neutron star (BNS) and neutron star-black…
Rapid identification of the optical counterparts of Neutron Star (NS) merger events discovered by gravitational wave detectors may require observing a large error region and sifting through a large number of transients to identify the…
Calibration is nowadays one of the most important processes involved in the extraction of valuable data from measurements. The current availability of an optimum data cube measured from a heterogeneous set of instruments and surveys relies…
Understanding and dealing with inference biases in gravitational-wave (GW) parameter estimation when a plethora of signals are present in the data is one of the key challenges for the analysis of data from future GW detectors. Working…
In the first work of this series, we adopt a GW170817-like, viewing-angle-dependent kilonova model and the standard afterglow model with the lightcurve distribution based on the properties of cosmological short gamma-ray bursts afterglows…
We present the first effort to aggregate, homogenize, and uniformly model the combined ultraviolet, optical, and near-infrared dataset for the electromagnetic counterpart of the binary neutron star merger GW170817. By assembling all of the…
We present an inference method utilizing artificial neural networks for parameter estimation of a quantum probe monitored through a single continuous measurement. Unlike existing approaches focusing on the diffusive signals generated by…
Kilonovae (KNe) are the electromagnetic signatures of neutron star mergers and are likely the dominant site of cosmic $r$-process nucleosynthesis. However, their intrinsic rate remains poorly constrained due to a paucity of confirmed…