相关论文: ProFit: Bayesian Profile Fitting of Galaxy Images

I introduce $Profiler$, a new, user-friendly program written in $Python$ and designed to analyse the radial surface brightness profiles of galaxies. With an intuitive graphical user interface, $Profiler$ can accurately model a wide range of…

Galaxy profile fitting is a ubiquitous technique that provides the backbone for photometric and morphological measurements in modern extragalactic surveys. A recent innovation in profile fitting algorithms is to render, or create, the model…

The S\'ersic model is known to fit well the surface brightness (or surface density) profiles of elliptical galaxies and galaxy bulges, and possibly for dwarf spheroidal galaxies and globular clusters. The deprojected density and mass…

We present an automated non-parametric light profile extraction pipeline called AutoProf. All steps for extracting surface brightness (SB) profiles are included in AutoProf, allowing streamlined analyses of galaxy images. AutoProf improves…

It is anticipated that the large sky areas covered by planned wide-field weak lensing surveys will reduce statistical errors to such an extent that systematic errors will instead become the dominant source of uncertainty. It is therefore…

We present a catalogue of two-dimensional, point spread function-corrected de Vacouleurs, S\'{e}rsic, de Vacouleurs+Exponential, and S\'{e}rsic+Exponential fits of $\sim7\times10^5$ spectroscopically selected galaxies drawn from the Sloan…

We introduce GALFIT-CORSAIR: a publicly available, fully retro-compatible modification of the 2D fitting software GALFIT (v.3) which adds an implementation of the core-Sersic model. We demonstrate the software by fitting the images of NGC…

Understanding how galaxies form and evolve requires measuring their light distributions in images taken by telescopes. This process often involves fitting mathematical models to galaxy images to extract properties such as size, brightness,…

Exponential, de Vaucouleurs, and S\'ersic profiles are simple and successful models for fitting two-dimensional images of galaxies. One numerical issue encountered in this kind of fitting is the pixel rendering and convolution (or…

Fitting parameterized models to images of galaxies has become the standard for measuring galaxy morphology. This forward modelling technique allows one to account for the PSF to effectively study semi-resolved galaxies. However, using a…

We present piXedfit, pixelized spectral energy distribution (SED) fitting, a Python package that provides tools for analyzing spatially resolved properties of galaxies using multiband imaging data alone or in combination with integral field…

We present the new ProFuse R package, a simultaneous spectral (ultraviolet to far infrared) and spatial structural decomposition tool that produces physical models of galaxies and their components. This combines the functionality of the…

The GooFit package provides physicists a simple, familiar syntax for manipulating probability density functions and performing fits, and is highly optimized for data analysis on NVIDIA GPUs and multithreaded CPU backends. GooFit was updated…

We present a proof-of-concept analysis of photometric redshifts with Bayesian priors on physical properties of galaxies. This concept is particularly suited for upcoming/on-going large imaging surveys, in which only several broad-band…

RooFit and RooStats, the toolkits for statistical modelling in ROOT, are used in most searches and measurements at the Large Hadron Collider as well as at $B$ factories. Larger datasets to be collected at e.g. the High-Luminosity LHC will…

Next generation large sky surveys will observe up to billions of galaxies for which basic structural parameters are needed to study their evolution. This is a challenging task that, for ground-based observations, is complicated by seeing…

We present a suite of IDL routines to interactively run GALFIT whereby the various surface brightness profiles (and their associated parameters) are represented by regions, which the User is expected to place. The regions may be saved…

We introduce a new galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes), to provide full posterior probability distributions and reliable confidence intervals for all model parameters. GALPHAT is designed to yield a high…

We present PriFit, a semi-supervised approach for label-efficient learning of 3D point cloud segmentation networks. PriFit combines geometric primitive fitting with point-based representation learning. Its key idea is to learn point…

We present Colibri, an open-source Python code that provides a general and flexible tool for PDF fits. The code is built so that users can implement their own PDF model, and use the built-in functionalities of Colibri for a fast computation…