ArtPop: A Stellar Population and Image Simulation Python Package

TL;DR

ArtPop is an open-source Python package that synthesizes stellar populations and generates artificial images, aiding astronomical research and education with modular, user-friendly tools for various scientific applications.

Contribution

This paper introduces ArtPop, a new modular Python package for stellar population synthesis and image simulation, with versatile applications in astronomy.

Findings

Demonstrated ArtPop's capability to simulate stellar populations.

Showcased applications in survey detection efficiency measurement.

Validated the package's use for stellar parameter calculations.

Abstract

We present Artificial Stellar Populations (ArtPop), an open-source Python package for synthesizing stellar populations and generating artificial images of fully populated stellar systems. The code is designed to be intuitive to use and as modular as possible, making it possible to use each of its functionalities independently or together. ArtPop has a wide range of scientific and pedagogical use cases, including the measurement of detection efficiencies in current and future imaging surveys, the calculation of integrated stellar population parameters, quantitative comparisons of isochrone models, and the development and validation of astronomical image processing algorithms. In this paper, we give an overview of the ArtPop package, provide simple coding examples to demonstrate its implementation, and present results from some potential applications of the code. We provide links to the source code that created each example and figure throughout the paper. ArtPop is under active development, and we welcome bug reports, feature requests, and code contributions from the community.