Related papers: Kilonova Spectral Inverse Modelling with Simulatio…
Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova…
With the next generation of both electromagnetic and gravitational wave observatories beginning to come online, rapid analysis methods for kilonova data are becoming increasingly important in astronomy. Traditional Bayesian parameter…
Detailed radiative transfer simulations of kilonovae are difficult to apply directly to observations; they only sparsely cover simulation parameters, such as the mass, velocity, morphology, and composition of the ejecta. On the other hand,…
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…
Kilonovae, possible electromagnetic counterparts to neutron star mergers, provide important information about high-energy transient phenomena and, in principle, also allow us to obtain information about the source properties responsible for…
Detailed radiative transfer simulations of kilonova spectra play an essential role in multimessenger astrophysics. Using the simulation results in parameter inference studies requires building a surrogate model from the simulation outputs…
The 2017 detection of a kilonova coincident with gravitational-wave emission has identified neutron star mergers as the major source of the heaviest elements, and dramatically constrained alternative theories of gravity. Observing a…
In the study of optical transients, parameter inference is the process of extracting physical information, i.e. constraints on the source's characteristics, by comparing the observed lightcurves to the predictions of different models and…
Computer simulations have long presented the exciting possibility of scientific insight into complex real-world processes. Despite the power of modern computing, however, it remains challenging to systematically perform inference under…
Real-time ranking of optical transient candidates during gravitational-wave (GW) and multimessenger follow-up is challenging when only sparse early-time, multi-band photometry is available.We present \texttt{KilonovaSCORER}, an open-source…
Rapid parameter estimation is critical when dealing with short lived signals such as kilonovae. We present a parameter estimation algorithm that combines likelihood-free inference with a pre-trained embedding network, optimized to…
Simulation-based inference (SBI) solves statistical inverse problems by repeatedly running a stochastic simulator and inferring posterior distributions from model-simulations. To improve simulation efficiency, several inference methods take…
Modern surveys often deliver hundreds of thousands of stellar spectra at once, which are fit to spectral models to derive stellar parameters/labels. Therefore, the technique of Amortized Neural Posterior Estimation (ANPE) stands out as 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…
Simulation-based inference (SBI) is an established approach for performing Bayesian inference on scientific simulators. SBI so far works best on low-dimensional parametric models. However, it is difficult to infer function-valued…
The coalescence of binary neutron stars in the GW170817 event led to the generation of gravitational waves, accompanied by the electromagnetic counterpart known as a kilonova (KN). Since then, it has been a prime topic of interest, as it…
Inferring the parameters of a stochastic model based on experimental observations is central to the scientific method. A particularly challenging setting is when the model is strongly indeterminate, i.e. when distinct sets of parameters…
The growing availability of large and complex datasets has increased interest in temporal stochastic processes that can capture stylized facts such as marginal skewness, non-Gaussian tails, long memory, and even non-Markovian dynamics.…
Kilonovae are likely a key site of heavy r-process element production in the Universe, and their optical/infrared spectra contain insights into both the properties of the ejecta and the conditions of the r-process. However, the event…
Some of the issues that make sampling parameter spaces of various beyond the Standard Model (BSM) scenarios computationally expensive are the high dimensionality of the input parameter space, complex likelihoods, and stringent experimental…