Related papers: Detecting episodes of star formation using Bayesia…
JWST observations have revealed an overabundance of bright galaxies at $z \geq 9$, creating apparent tensions with theoretical predictions within standard $\Lambda$CDM cosmology. We address this challenge using a semi-empirical approach…
Broadband spectral energy distribution (SED) fitting is used to study a deep sample of UV-selected sub-L* galaxies at z~2. They are found to be less dusty than L* galaxies, and to contribute more mass to the cosmic mass budget at this epoch…
Submillimetre (submm) galaxies are among the most rapidly star-forming and most massive high-redshift galaxies; thus, their properties provide important constraints on galaxy evolution models. However, there is still a debate about their…
We provide a library of some 7000 SEDs (available at www.eso.org/~rsiebenm) for the nuclei of starburst and ultra luminous galaxies. Its purpose is to quickly obtain estimates of the basic parameters, such as luminosity, size and dust or…
Bayesian analysis plays a crucial role in estimating distribution of unknown parameters for given data and model. Due to the curse of dimensionality, it becomes difficult for high-dimensional problems, especially when multiple modes exist.…
Nested sampling is a promising tool for Bayesian statistical analysis because it simultaneously performs parameter estimation and facilitates model comparison. MultiNest is one of the most popular nested sampling implementations, and has…
ABRIDGED. The analysis of spectral energy distributions (SEDs) of protoplanetary disks to determine their physical properties is known to be highly degenerate. Hence, a Bayesian analysis is required to obtain parameter uncertainties and…
We introduce a new conservative test for quantifying the consistency of two or more datasets. The test is based on the Bayesian answer to the question, ``How much more probable is it that all my data were generated from the same model…
The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ($M_*$), star formation rate (${\rm SFR}$), stellar metallicity ($Z_{\rm MW}$), and stellar age…
This project establishes parameters to characterize galaxy Star Formation History (SFH) beyond mean stellar age. We use ages at which fixed star fractions form to characterize SFH duration. We define Deltaage_n = (age_10 - age_90)/age_50…
In this paper, we discuss measurements of the stellar population and star forming properties for 43 spectroscopically confirmed publicly available high-redshift $z > 7$ JWST galaxies in the JADES and CEERS observational programs. We carry…
Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technology. To this day, however, all the theoretical models that…
We compare the predictions of three independently developed semi-analytic galaxy formation models that are being used to aid in the interpretation of results from the CANDELS survey. These models are each applied to the same set of halo…
With the advent of billion-galaxy surveys with complex data, the need of the hour is to efficiently model galaxy spectral energy distributions (SEDs) with robust uncertainty quantification. The combination of Simulation-Based inference…
Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…
Stochastic differential equations (SDEs) provide a natural framework for modelling intrinsic stochasticity inherent in many continuous-time physical processes. When such processes are observed in multiple individuals or experimental units,…
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…
This thesis responds to the challenges of using a large number, such as thousands, of features in regression and classification problems. There are two situations where such high dimensional features arise. One is when high dimensional…
The current and forthcoming observations of large samples of high-redshift galaxies selected according to various photometric and spectroscopic criteria can be interpreted in the context of galaxy formation, by means of models of evolving…
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…