The Astrophysical Journal Supplement Series (Jan 2023)

The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog

  • Mallory Molina,
  • Laura Duffy,
  • Michael Eracleous,
  • Mary Ogborn,
  • Mary E. Kaldor,
  • Renbin Yan,
  • Caryl Gronwall,
  • Robin Ciardullo,
  • Nikhil Ajgaonkar

DOI
https://doi.org/10.3847/1538-4365/acf578
Journal volume & issue
Vol. 268, no. 2
p. 63

Abstract

Read online

We present the the new Swift/UVOT+MaNGA (SwiM) catalog (SwiM_v4.1). SwiM_v4.1 is designed to study star formation and dust attenuation within nearby galaxies given the unique overlap of Swift/UVOT near-ultraviolet (NUV) imaging and MaNGA integral field optical spectroscopy. SwiM_v4.1 comprises 559 objects, ∼4 times more than the original SwiM catalog (SwiM_v3.1), spans the redshift range z ≈ 0.0002–0.1482, and provides a more diverse and rich sample. Approximately 5% of the final MaNGA sample is included in SwiM_v4.1, and 42% of the SwiM_v4.1 galaxies are cross-listed with other well-known catalogs. We present the same data as SwiM_v3.1, including UVOT images, Sloan Digital Sky Survey (SDSS) images, and MaNGA emission-line and spectral index maps with the same pixel size and angular resolution for each galaxy, and a file containing galaxy and observational properties. We designed SwiM_v4.1 to be unbiased, which resulted in some objects having low signal-to-noise ratios in their MaNGA or Swift data. We addressed this by providing a new file containing the fraction of science-ready pixels in each MaNGA emission-line map, and the integrated flux and inverse variance for all three NUV filters. The uniform angular resolution and sampling in SwiM_v4.1 will help answer a number of scientific questions, including constraining quenching and attenuation in the local Universe and studying the effects of black hole feedback. The galaxy maps, catalog files, and their associated data models are publicly released on the SDSS website (a description of the SwiM VAC is provided at https://www.sdss4.org/dr17/data_access/value-added-catalogs/?vac_id=swift-manga-value-added-catalog , and the data are stored on the SDSS Science Archive Server at https://data.sdss.org/sas/dr17/manga/swim/v4.1/ ).

Keywords