Related papers: Inferring Galactic Parameters from Chemical Abunda…
The distribution of metals in the intracluster medium (ICM) of galaxy clusters provides valuable information on their formation and evolution, on the connection with the cosmic star formation and on the effects of different gas processes.…
Chemical evolution models are powerful tools for interpreting stellar abundance surveys and understanding galaxy evolution. However, their predictions depend heavily on the treatment of inflow, outflow, star formation efficiency (SFE), the…
A chemical characterization of the Galactic Center is essential for understanding its formation and structural evolution. Trends of alpha-elements, such as Mg, Si, and Ca, serve as powerful diagnostic tools, offering insights into…
One-zone Galactic Chemical Evolution (GCE) models have provided useful insights on a great wealth of average abundance patterns in many environments, especially for the Milky Way and its satellites. However, the scatter of such abundance…
Hamiltonian Monte Carlo (HMC) is a powerful and accurate method to sample from the posterior distribution in Bayesian inference. However, HMC techniques are computationally demanding for Bayesian neural networks due to the high…
Bayesian posterior distributions naturally represent parameter uncertainty informed by data. However, when the parameter space is complex, as in many nonparametric settings where it is infinite-dimensional or combinatorially large, standard…
Chemical abundance determinations from stellar spectra are challenged by observational noise, limitations in stellar models, and departures from simplifying assumptions. While traditional and supervised machine learning methods have made…
Accurately estimating parameters of physiological models is essential to achieving reliable digital twins. For Type 1 Diabetes, this is particularly challenging due to the complexity of glucose-insulin interactions. Traditional methods…
We present a cosmologically motivated model for the hierachical formation of the stellar halo which includes a semi-analytic treatment of galactic chemical enrichment coupled to numerical simulations that track the orbital evolution and…
We present a scalable approach to performing approximate fully Bayesian inference in generic state space models. The proposed method is an alternative to particle MCMC that provides fully Bayesian inference of both the dynamic latent states…
We present a novel framework to self-consistently model the effects of radiation fields, dust physics and molecular chemistry (H$_2$) in the interstellar medium (ISM) of galaxies. The model combines a state-of-the-art radiation…
We present a Bayesian inference method to characterise the dust emission properties using the well-known dust-HI correlation in the diffuse interstellar medium at Planck frequencies $\nu \ge 217$ GHz. We use the Galactic HI map from the…
Symbiotic stars (SySt) are binaries composed of a star in the later stages of evolution and a stellar remnant. The enhanced mass-loss from the giant drives interacting mass exchange and makes these systems laboratories for understanding…
[Abridged] Motivated by upcoming data from astrometric and spectroscopic surveys of the Galaxy, we explore the chemical abundance properties and phase-space distributions in hierarchically-formed stellar halo simulations set in a LambdaCDM…
The non-Gaussisan spatial distribution of galaxies traces the large-scale structure of the Universe and therefore constitutes a prime observable to constrain cosmological parameters. We conduct Bayesian inference of the $\Lambda$CDM…
We employ the SIMBA-C cosmological simulation to study the impact of its upgraded chemical enrichment model (Chem5) on the distribution of metals in the intragroup medium (IGrM). We investigate the projected X-ray emission-weighted…
Monte Carlo techniques have been used to evaluate the statistical and systematic uncertainties in the helium abundances derived from extragalactic H~II regions. The helium abundance is sensitive to several physical parameters associated…
Chemical enrichment signatures strongly constrain galaxy formation and evolution, and a detailed understanding of abundance patterns provides clues regarding the nucleosynthetic production pathways of elements. Using the SDSS-IV MaNGA IFU…
In genomics, differential abundance and expression analyses are complicated by the compositional nature of sequence count data, which reflect only relative-not absolute-abundances or expression levels. Many existing methods attempt to…
We characterize the properties of the intergalactic medium (IGM) around a sample of galaxies extracted from state-of-the-art hydrodynamical simulations of structure formation in a cosmological volume of 25 Mpc comoving at $z\sim 2$. The…