Related papers: Understanding and reducing statistical uncertainti…
We exploit the great potential offered by Bayesian Neural Networks (BNNs) to directly decipher the internal composition of neutron stars (NSs) based on their macroscopic properties. By analyzing a set of simulated observations, namely NS…
We present a new tool for the analysis of the optical emission lines of the gas in the Narrow Line Region (NLR) around Active Galactic Nuclei (AGNs). This new tool can be used in large samples of objects in a consistent way using different…
Explanation methods help understand the reasons for a model's prediction. These methods are increasingly involved in model debugging, performance optimization, and gaining insights into the workings of a model. With such critical…
Background and objective: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly…
It has recently been noted that there seems to be a strong correlation between planetary nebulae with close binary central stars, and highly enhanced recombination line abundances. We present new deep spectra of seven objects known to have…
Context. Departures from local thermodynamic equilibrium (LTE) distort the calcium abundance derived from stellar spectra in various ways, depending on the lines used and the stellar atmospheric parameters. The collection of atomic data…
Correlations between planetary and stellar properties, particularly age, can provide insight on planetary formation and evolution processes. However, the underlying source of such trends can be unclear, and measurement uncertainties and…
Accurate measurements of europium abundances in cool stars are essential for an enhanced understanding of the r-process mechanisms. We measure the abundance of Eu in solar spectra and a sample of metal-poor stars in the Galactic halo and…
Diagnostic diagrams of forbidden lines have been a useful tool for observers in astrophysics for many decades now. They are used to obtain information on the basic physical properties of thin gaseous nebulae. Some diagnostic diagrams are in…
We present a method for computing uncertainties in spectral models, i.e. level populations, line emissivities, and emission line ratios, based upon the propagation of uncertainties originating from atomic data. We provide analytic…
Bayesian neural networks and deep ensemble methods have been proposed for uncertainty quantification; however, they are computationally intensive and require large storage. By utilizing a single deterministic model, we can solve the above…
Non-Maxwellian $\kappa$ electron energy distributions (EEDs) have been proposed in recent years to resolve the so-called ``electron temperature and abundance discrepancy problem'' in the study of planetary nebulae (PNe). Thus the need to…
The near infrared extinction powerlaw index ($\beta$) and its uncertainty is derived from three different techniques based on star counts, colour excess and a combination of them. We have applied these methods to 2MASS data to determine…
We present an adapted version of the code HII-CHI-Mistry-UV (P\'erez-Montero & Amor\'in 2017) to derive chemical abundances from emission lines in the ultraviolet, for use in narrow line regions (NLR) of Active Galactic Nuclei (AGN). We…
Causal inference from observational data provides strong evidence for the best action in decision-making without performing expensive randomized trials. The effect of an action is usually not identifiable under unobserved confounding, even…
Atomic diffusion with radiative levitation is a major transport process to consider to explain abundance anomalies in Am stars. Radiative accelerations vary from one species to another, yielding different abundance anomalies at the stellar…
Context: Astronomy and astrophysics demand rigorous handling of uncertainties to ensure the credibility of outcomes. The growing integration of artificial intelligence offers a novel avenue to address this necessity. This convergence…
We examine contributions of second order physical processes to results of stellar evolution calculations amenable to direct observational testing. In the first paper in the series (Young et al. 2001) we established baseline results using…
Direct sampling of neutral interstellar (NIS) atoms by the Interstellar Boundary Explorer (IBEX) can potentially provide a complementary method for studying element abundances in the Local Interstellar Cloud and processes in the heliosphere…
Graph Neural Networks (GNNs) have shown remarkable performance in the healthcare domain. However, what remained challenging is quantifying the predictive uncertainty of GNNs, which is an important aspect of trustworthiness in clinical…