Related papers: GalaPy, the highly optimised C++/Python spectral m…
Distant galaxies encapsulate the various stages of galaxy evolution and formation from over 95% of the development of the universe. As early as twenty-five years ago, little was known about them, however since the first systematic survey…
Dust plays crucial roles in galaxy formation and evolution. In the early epoch of galaxy evolution dust is only supplied by supernovae (SNe). With the aid of a new physical model of dust production by SNe, we constructed a model of dust…
We test the efficacy of the energy-balance spectral energy distribution (SED) fitting code Magphys for recovering the spatially-resolved properties of a simulated isolated disc galaxy, for which it was not designed. We perform 226,950…
State-of-the-art galaxy formation simulations generate data within weeks or months. Their results consist of a random sub-sample of possible galaxies with a fixed number of stars. We propose a ML based method, GalacticFlow, that generalizes…
Stellar physics and evolution calculations enable a broad range of research in astrophysics. Modules for Experiments in Stellar Astrophysics (MESA) is a suite of open source libraries for a wide range of applications in computational…
\textbf{GalRotpy} is an educational \verb+Python3+-based visual tool, which is useful to undestand how is the contribution of each mass component to the gravitational potential of disc-like galaxies by means of their rotation curve.…
Measuring the physical properties of galaxies such as redshift frequently requires the use of Spectral Energy Distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space.…
Photometric redshift estimation is an indispensable tool of precision cosmology. One problem that plagues the use of this tool in the era of large-scale sky surveys is that the bright galaxies that are selected for spectroscopic observation…
Spatially-resolved emission line kinematics are invaluable to investigating fundamental galaxy properties and have become increasingly accessible for galaxies at $z\gtrsim0.5$ through sensitive near-infrared imaging spectroscopy and…
We present a new tool for the photometric estimate of stellar masses in distant galaxies. The observed SEDs are fitted by combining single stellar populations, with different SFRs and amounts of dust extinction. This approach gives us the…
The Herschel Extragalactic Legacy Project (HELP) focuses to publish an astronomical multiwavelength catalogue of millions of objects over 1300~deg$^2$ of the Herschel Space Observatory survey fields. Millions of galaxies with…
We present a new machine learning model for estimating photometric redshifts with improved accuracy for galaxies in Pan-STARRS1 data release 1. Depending on the estimation range of redshifts, this model based on neural networks can handle…
We present a new software pipeline -- PyMorph -- for automated estimation of structural parameters of galaxies. Both parametric fits through a two dimensional bulge disk decomposition as well as structural parameter measurements like…
State-of-the-art spectral energy distribution (SED) analyses use a Bayesian framework to infer the physical properties of galaxies from observed photometry or spectra. They require sampling from a high-dimensional space of SED model…
We have developed a software library for chemical evolution simulations of galaxy formation under the simple stellar population (SSP) approximation. In this library, all of the necessary components concerning chemical evolution, such as…
The large-scale imaging survey will produce massive photometric data in multi-bands for billions of galaxies. Defining strategies to quickly and efficiently extract useful physical information from this data is mandatory. Among the stellar…
Accurately characterizing the redshift distributions of galaxies is essential for analysing deep photometric surveys and testing cosmological models. We present a technique to simultaneously infer redshift distributions and individual…
Cloud computing offers an opportunity to run compute-resource intensive climate models at scale by parallelising model runs such that datasets useful to the exoplanet community can be produced efficiently. To better understand the…
To understand the role of the environment in galaxy formation, evolution, and present-day properties, it is essential to study the multi-frequency behavior of different galaxy populations under various environmental conditions. We…
We present new fully self-consistent models of the formation and evolution of isolated dwarf galaxies. We have used the publicly available N-body/SPH code HYDRA, to which we have added a set of star formation criteria, and prescriptions for…