GalaPy, the highly optimised C++/Python spectral modelling tool for galaxies -- I. Library presentation and photometric fitting

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Main Authors: Ronconi, Tommaso, Lapi, Andrea, Torsello, Martina, Bressan, Alessandro, Donevski, Darko, Pantoni, Lara, Behiri, Meriem, Boco, Lumen, Cimatti, Andrea, D'Amato, Quirino, Danese, Luigi, Giulietti, Marika, Perrotta, Francesca, Silva, Laura, Talia, Margherita, Massardi, Marcella
Format: Preprint
Published: 2024
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author Ronconi, Tommaso
Lapi, Andrea
Torsello, Martina
Bressan, Alessandro
Donevski, Darko
Pantoni, Lara
Behiri, Meriem
Boco, Lumen
Cimatti, Andrea
D'Amato, Quirino
Danese, Luigi
Giulietti, Marika
Perrotta, Francesca
Silva, Laura
Talia, Margherita
Massardi, Marcella
author_facet Ronconi, Tommaso
Lapi, Andrea
Torsello, Martina
Bressan, Alessandro
Donevski, Darko
Pantoni, Lara
Behiri, Meriem
Boco, Lumen
Cimatti, Andrea
D'Amato, Quirino
Danese, Luigi
Giulietti, Marika
Perrotta, Francesca
Silva, Laura
Talia, Margherita
Massardi, Marcella
contents Fostered by upcoming data from new generation observational campaigns, we are about to enter a new era for the study of how galaxies form and evolve. The unprecedented quantity of data that will be collected, from distances only marginally grasped up to now, will require analysis tools designed to target the specific physical peculiarities of the observed sources and handle extremely large datasets. One powerful method to investigate the complex astrophysical processes that govern the properties of galaxies is to model their observed spectral energy distribution (SED) at different stages of evolution and times throughout the history of the Universe. To address these challenges, we have developed GalaPy, a new library for modelling and fitting SEDs of galaxies from the X-ray to the radio band, as well as the evolution of their components and dust attenuation/reradiation. GalaPy incorporates both empirical and physically-motivated star formation histories, state-of-the-art single stellar population synthesis libraries, a two-component dust model for attenuation, an age-dependent energy conservation algorithm to compute dust reradiation, and additional sources of stellar continuum such as synchrotron, nebular/free-free emission and X-ray radiation from low and high mass binary stars. GalaPy has a hybrid implementation that combines the high performance of compiled C++ with the flexibility of Python, and exploits an object-oriented design. It generates models on the fly without relying on templates, and exploits fully Bayesian parameter space sampling. In this first work, we introduce the project and showcase the photometric SED fitting tools already available to users. The library is available on the Python Package Index (PyPI) and comes with extensive online documentation and tutorials.
format Preprint
id arxiv_https___arxiv_org_abs_2402_12427
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle GalaPy, the highly optimised C++/Python spectral modelling tool for galaxies -- I. Library presentation and photometric fitting
Ronconi, Tommaso
Lapi, Andrea
Torsello, Martina
Bressan, Alessandro
Donevski, Darko
Pantoni, Lara
Behiri, Meriem
Boco, Lumen
Cimatti, Andrea
D'Amato, Quirino
Danese, Luigi
Giulietti, Marika
Perrotta, Francesca
Silva, Laura
Talia, Margherita
Massardi, Marcella
Astrophysics of Galaxies
Instrumentation and Methods for Astrophysics
Fostered by upcoming data from new generation observational campaigns, we are about to enter a new era for the study of how galaxies form and evolve. The unprecedented quantity of data that will be collected, from distances only marginally grasped up to now, will require analysis tools designed to target the specific physical peculiarities of the observed sources and handle extremely large datasets. One powerful method to investigate the complex astrophysical processes that govern the properties of galaxies is to model their observed spectral energy distribution (SED) at different stages of evolution and times throughout the history of the Universe. To address these challenges, we have developed GalaPy, a new library for modelling and fitting SEDs of galaxies from the X-ray to the radio band, as well as the evolution of their components and dust attenuation/reradiation. GalaPy incorporates both empirical and physically-motivated star formation histories, state-of-the-art single stellar population synthesis libraries, a two-component dust model for attenuation, an age-dependent energy conservation algorithm to compute dust reradiation, and additional sources of stellar continuum such as synchrotron, nebular/free-free emission and X-ray radiation from low and high mass binary stars. GalaPy has a hybrid implementation that combines the high performance of compiled C++ with the flexibility of Python, and exploits an object-oriented design. It generates models on the fly without relying on templates, and exploits fully Bayesian parameter space sampling. In this first work, we introduce the project and showcase the photometric SED fitting tools already available to users. The library is available on the Python Package Index (PyPI) and comes with extensive online documentation and tutorials.
title GalaPy, the highly optimised C++/Python spectral modelling tool for galaxies -- I. Library presentation and photometric fitting
topic Astrophysics of Galaxies
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2402.12427