Related papers: GalaPy, the highly optimised C++/Python spectral m…
The star formation history (SFH) of galaxies allow us to investigate when galaxies formed their stars and assembled their mass. We can constrain the SFH with high level of precision from galaxies with resolved stellar populations, since we…
Unveiling the evolutionary history of galaxies necessitates a precise understanding of their physical properties. Traditionally, astronomers achieve this through spectral energy distribution (SED) fitting. However, this approach can be…
We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation will support and advance research on galaxies in the era of…
We present model spectral energy distribution (SED) fits to ultraviolet/optical/infrared observations for the 258 nearby galaxies in the Local Volume Legacy survey, a sample dominated by lower-luminosity dwarf irregular systems. The data…
We present a numerical code to simulate maps of Galactic emission in intensity and polarization at microwave frequencies, aiding in the design of Cosmic Microwave Background experiments. This Python code builds on existing efforts to…
Understanding the lives and interior structures of stellar objects is a fundamental objective of astrophysics. Research in this domain often relies on the visualization of astrophysical data, for instance, the results of theoretical…
Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a…
We present here a model for simulating the panchromatic spectral energy distribution of galaxies, which aims to be a complete tool to study the complex multi-wavelength picture of the universe. The model take into account all important…
We present results from a new modelling technique which can account for the observed optical/NIR - FIR/submm spectral energy distributions (SEDs) of normal star-forming galaxies in terms of a minimum number of essential parameters…
I present StarEstate, an open-source Python package for producing rapid, statistically robust galactic population synthesis models. By utilizing optimized pre-calculated inverse-cumulative distribution function samplers, the tool generates…
We have developed a new stellar population synthesis model designed to study early-type galaxies. It provides optical and near-infrared colors, and line indices for 25 absorption lines. It can synthesize single age, single metallicity…
We present cogsworth, an open-source Python tool for producing self-consistent population synthesis and galactic dynamics simulations. With cogsworth one can (1) sample a population of binaries and star formation history, (2) perform rapid…
Cosmologists at the Institute of Computational Cosmology, Durham University, have developed a state of the art model of galaxy formation known as Galform, intended to contribute to our understanding of the formation, growth and subsequent…
Photometric data of galaxies covering the rest-frame wavelength range from far-UV to far-IR make it possible to derive galaxy properties with a high reliability by fitting the attenuated stellar emission and the related dust emission at the…
We present models of photometric evolution of galaxies in which the effects of a dusty interstellar medium have been included with particular care. A chemical evolution code follows the star formation rate, the gas fraction and the…
This paper presents the simulation of the GLAST high energy gamma-ray telescope. The simulation package, written in C++, is based on the Geant4 toolkit, and it is integrated into a general framework used to process events. A detailed…
Galaxy spectral energy distributions (SEDs) remain among the most challenging yet informative quantities to reproduce in simulations due to the large and complex mixture of physical processes that shape the radiation output of a galaxy.…
Improving upon the standard evolutionary population synthesis (EPS) technique, we present spectrophotometric models of galaxies whose morphology goes from spherical structures to discs, properly accounting for the effect of dust in the…
Observational astronomy relies on visual feature identification to detect critical astrophysical phenomena. While machine learning (ML) increasingly automates this process, models often struggle with generalization in large-scale surveys…
We introduce a procedure developed by the ``Teramo Stellar Populations Tools'' group (Teramo-SPoT), specifically optimized to obtain realistic simulations of CCD images of elliptical galaxies. Particular attention is devoted to include the…