{
  "annotation_id": "a2162583-aef8-4134-8da5-05b6b544cc33",
  "date_created": "2026-02-17T05:53:04.880000Z",
  "date_modified": "2026-02-17T05:53:04.880000Z",
  "file_hash": "53fa5eeffc8a630e801ba219f73700a6ad49ff05c31bbebfdeaf7b386a74d1c2",
  "private": false,
  "record": {
    "abstract": "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, components, and shape. GALFIT is a widely used tool for this purpose, but it requires careful preparation of input files and interpretation of results, which can be a barrier to efficient use. GALFITools is a Python library that streamlines this workflow by automating many of the tasks surrounding the use of GALFIT. These include generating image masks, estimating sky background, modeling the telescope\u0027s point spread function (PSF), and extracting physical parameters from GALFIT outputs. The software is designed for researchers and students who work with galaxy image modeling and aims to make the process more reproducible, accessible, and scalable.",
    "arxiv_id": "2601.05291",
    "authors": [
      "Christopher A\u00f1orve"
    ],
    "categories": [
      "astro-ph.IM"
    ],
    "doi": "10.21105/joss.09534",
    "journal_ref": "Journal of Open Source Software, 10(116), 9534 (2025)",
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "GALFITools: A Python library to enhance GALFIT usage in galaxy image modeling",
    "url": "https://arxiv.org/abs/2601.05291",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "c25e05fd-7cee-40ac-bf04-69189f6a5b43",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}