相关论文: Beyond the best-fit parameter: new insight on gala…

With the advent of large scale surveys (i.e., Legacy Surveys) it is now possible to start looking beyond the galaxy luminosity function (LF) to more detailed statistical representations of the galaxy population, i.e., multivariate…

Gaussian processes are a powerful framework for quantifying uncertainty and for sequential decision-making but are limited by the requirement of solving linear systems. In general, this has a cubic cost in dataset size and is sensitive to…

This paper presents a new technique for reconstructing the spatial distributions of hydrogen, temperature and metal abundance of a galaxy cluster. These quantities are worked out from the X-ray spectrum, modeled starting from few analytical…

Here, we present a machine vision approach, combining a VAE framework with PCA, to decipher galaxy images. Using mock gri-band images from the EAGLE simulation, the VAE finds that around 35 features are needed to describe the images. Adding…

Modern spectroscopic surveys can only target a small fraction of the vast amount of photometrically cataloged sources in wide-field surveys. Here, we report the development of a generative AI method capable of predicting optical galaxy…

Bulge-disc decomposition is a valuable tool for understanding galaxies. However, achieving robust measurements of component properties is difficult, even with high quality imaging, and it becomes even more so with the imaging typical of…

We present the results of the most complete ever scan of the parameter space for cosmic ray (CR) injection and propagation. We perform a Bayesian search of the main GALPROP parameters, using the MultiNest nested sampling algorithm,…

We describe the application of the `shapelet' linear decomposition of galaxy images to multi-wavelength morphological classification using the $u,g,r,i,$ and $z$-band images of 1519 galaxies from the Sloan Digital Sky Survey. We utilize…

Aims: We discuss the applicability and reliability of the shapelet technique for scientific image analysis. Methods: We quantify the effects of non-orthogonality of sampled shapelet basis functions and misestimation of shapelet parameters.…

Our understanding of the dynamics of the interstellar medium is informed by the study of the detailed velocity structure of emission line observations. One approach to study the velocity structure is to decompose the spectra into individual…

Three methods for detecting and characterizing structure in point data, such as that generated by redshift surveys, are described: classification using self-organizing maps, segmentation using Bayesian blocks, and density estimation using…

We describe a new technique for measuring accurate galaxy colours from images taken under different seeing conditions. The method involves two ingredients. First we define the Gaussian-aperture-and-PSF flux, which is the Gaussian-weighted…

Gradient pattern analysis (GPA) is a well-established technique for measuring gradient bilateral asymmetries of a square numerical lattice. This paper introduces an improved version of GPA designed for galaxy morphometry. We show the…

Multi-band images of galaxies reveal a huge amount of information about their morphology and structure. However, inferring properties of the underlying stellar populations such as age, metallicity or kinematics from those images is…

This paper presents a new Expectation Propagation (EP) framework for image restoration using patch-based prior distributions. While Monte Carlo techniques are classically used to sample from intractable posterior distributions, they can…

We study the potential of GLAST to unveil particle dark matter properties with gamma-ray observations of the Galactic center region. We present full GLAST simulations including all gamma-ray sources known to date in a region of 4 degrees…

We present a new approach to measure the shapes of galaxies, a fundamental task in observational astronomy. This approach is based on the decomposition of a galaxy image into a series of orthogonal basis functions, or `shapelets'. Our…

In this paper, we discuss computational aspects to obtain accurate inferences for the parameters of the generalized gamma (GG) distribution. Usually, the solution of the maximum likelihood estimators (MLE) for the GG distribution have no…

This project uses the 2MASS all-sky image database to study the structure of galaxies over a range of luminosities, sizes and morphological types. This first paper in this series will outline the techniques, reliability and data products to…

Likelihood fitting to two-point clustering statistics made from galaxy surveys usually assumes a multivariate normal distribution for the measurements, with justification based on the central limit theorem given the large number of…