Related papers: Deriving star formation histories: Inverting HR di…
Subsampling is a widely used and effective approach for addressing the computational challenges posed by massive datasets. Substantial progress has been made in developing non-uniform, probability-based subsampling schemes that prioritize…
With recent advances in modelling stars using high-precision asteroseismology, the systematic effects associated with our assumptions of stellar helium abundance ($Y$) and the mixing-length theory parameter ($\alpha_\mathrm{MLT}$) are…
Radial-velocity (RV) signals induce RV variations an order of magnitude larger than the signal created by the orbit of Earth-twins, thus preventing their detection. The goal of this paper is to compare the efficiency of the different…
Motivation: Radiomics refers to the high-throughput mining of quantitative features from radiographic images. It is a promising field in that it may provide a non-invasive solution for screening and classification. Standard machine learning…
Understanding the rate at which stars form is central to studies of galaxy formation. Observationally, the star formation rates (SFRs) of galaxies are measured using the luminosity in different frequency bands, often under the assumption of…
We study the stellar population history and chemical evolution of the Milky Way (MW) in a hierarchical LCDM model for structure formation. Using a Monte Carlo method based on the semi-analytical EPS formalism, we reconstruct the merger tree…
We consider the task of obtaining the maximum a posteriori estimate of discrete pairwise random fields with arbitrary unary potentials and semimetric pairwise potentials. For this problem, we propose an accurate hierarchical move making…
High-resolution galaxy spectra encode information about the stellar populations within galaxies. The properties of the stars, such as their ages, masses, and metallicities, provide insights into the underlying physical processes that drive…
We consider the maximum likelihood estimation of sparse inverse covariance matrices. We demonstrate that current heuristic approaches primarily encourage robustness, instead of the desired sparsity. We give a novel approach that solves the…
Inferring the source properties of a gravitational wave signal has traditionally been very computationally intensive and time consuming. In recent years, several techniques have been developed that can significantly reduce the computational…
Structured variational inference constitutes a core methodology in modern statistical applications. Unlike mean-field variational inference, the approximate posterior is assumed to have interdependent structure. We consider the natural…
The Hertzsprung-Russell diagram is an essential diagnostic diagram for stellar structure and evolution, which has now been in use for more than 100 years. Our spectroscopic Hertzsprung-Russell (sHR) diagram shows the inverse of the…
We obtain a new determination of the metallicity distribution function (MDF) of stars within $\sim5$-$10$ kpc of the Sun, based on recently improved co-adds of $ugriz$ photometry for Stripe 82 from the Sloan Digital Sky Survey. Our new…
In many statistical problems, the data distribution is specified through a generative process for which the likelihood function is analytically intractable, yet inference on the associated model parameters remains of primary interest. We…
The termination in the white dwarf luminosity function is a standard diagnostic tool for measuring the total age of nearby stellar populations. In this paper, an algorithm is presented for inverting the full white dwarf luminosity function…
The Gaia DR2 catalog is the best source of stellar astrometric and photometric data available today. The history of the Milky Way galaxy is written in stone in this data set. Parallaxes and photometry tell us where the stars are today, when…
An overview of pulsating variable stars across the observational Hertzprung-Russel (HR) diagram is presented, together with a summary of their global properties. The HR diagram is presented with a third colour-coded dimension, visualizing…
We consider optimal decision-making problems in an uncertain environment. In particular, we consider the case in which the distribution of the input is unknown, yet there is abundant historical data drawn from the distribution. In this…
High-contrast imaging of exoplanets hinges on powerful post-processing methods to denoise the data and separate the signal of a companion from its host star, which is typically orders of magnitude brighter. Existing post-processing…
A statistical analysis of the observed perturbations in the density of stellar streams can in principle set stringent contraints on the mass function of dark matter subhaloes, which in turn can be used to constrain the mass of the dark…