Published January 25, 2021 | Version v1
Dataset Open

SPICY - The Spitzer/IRAC Candidate YSO Catalog for the Inner Galactic Midplane Stamp Album

  • 1. Department of Astronomy, California Institute of Technology
  • 2. Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory
  • 3. Donald Bren School of Information and Computer Sciences, University of California
  • 4. Institut de Ciències del Cosmos, Universitat de Barcelona (IEEC-UB)
  • 5. Université Clermont Auvergne, CNRS/IN2P3, LPC
  • 6. Department of Physics and Astronomy, California State Polytechnic University Pomona

Description

We present an album with image stamps in the PNG and FITS formats of the environment of ~120,000 Spitzer/IRAC candidate young stellar objects (YSOs). There is a total of 586238 images included in this dataset. The SPICY YSO candidates were selected based on surveys of the Galactic midplane between l~255 deg and 110 deg, including the GLIMPSE I, II, and 3D, Vela-Carina, Cygnus X, and SMOG surveys, comprising 613 square degrees, augmented by near-infrared catalogs. We employed a classification scheme that uses the flexibility of a tailored statistical learning method and curated YSO datasets to take full advantage of IRAC's spatial resolution and sensitivity in the mid-infrared ~3-9 micron range. Most of the candidates are in regions with mid-IR nebulosity, associated with star-forming clouds, but others appear distributed in the field. Given that no current or planned instruments will significantly exceed IRAC's spatial resolution while possessing its wide-area mapping capabilities, Spitzer-based catalogs such as ours will remain the main resources for mid-infrared YSOs in the Galactic midplane for the near future. For more information about the catalog see https://arxiv.org/abs/2011.12961. The data in this album were used to produce the simple YSO environment classification in the aforementioned work, and they can be used to facilitate the study of the local environments around YSOs as well as to provide a curated dataset to promote further development of content-based information retrieval systems and of methods to classify and cluster images that are able to cope with challenging astronomical regions.

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Related works

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Preprint: arXiv:2011.12961 (arXiv)