Statistical Properties of Galactic δ Scuti Stars: Revisited

Abstract

We present statistical characteristics of 1,578 δ Scuti stars including nearby field stars and cluster member stars within the Milky Way. We obtained 46% of these stars (718 stars) from the works done by Rodríguez and collected the remaining 54% stars (860 stars) from other literatures. We updated the entries with the latest information of sky coordinate, color, rotational velocity, spectral type, period, amplitude and binarity. The majority of our sample are well characterized in terms of typical period range (0.02-0.25 days), pulsation amplitudes (<0.5 mag) and spectral types (A-F type). Given this list of δ Scuti stars, we examined relations between their physical properties (i.e., periods, amplitudes, spectral types and rotational velocities) for field stars and cluster members, and confirmed that the correlations of properties are not significantly different from those reported in the Rodríguez's works. All the δ Scuti stars are cross-matched with several X-ray and UV catalogs, resulting in 27 X-ray and 41 UV-only counterparts. These counterparts are interesting targets for further study because of their rarity and uniqueness in showing δ Scuti-type variability and X-ray/UV emission at the same time. The compiled catalog can be accessed through the web interface http://stardb.yonsei.ac.kr/DeltaScuti

15 pages, 8 figures, 6 tables. Accepted for publication in AJ. The catalog is available at http://stardb.yonsei.ac.kr/DeltaScuti

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• The OmegaWhite Survey for Short-Period Variable Stars I: Overview and First Results
• The OmegaWhite Survey for short period variable stars II: An overview of results from the first four years
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• The DECam Minute Cadence Survey II: 49 Variables but No Planetary Transits of a White Dwarf
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• TESS search for substellar companions through pulsation timing of $\delta$ Scuti stars. I. Discovery of companions around Chang 134 and V393 Car
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• Investigating the Period-Luminosity Relations of delta Scuti Stars: A Pathway to Distance and 3-D Dust Map Inference