On the basis of the Galaxy Evolution Explore (GALEX) ultraviolet (UV) data, many studies have demonstrated that recent star foation (RSF) is common in early-type galaxies. In particular, near-ultraviolet (NUV) light is used to investigate star foation activity in early-type galaxies, owing to its high sensitivity to the presence of young stars. This study characterized the stellar population properties of luminous early-type galaxies (Mr ≤ -20.65 mag) in the redshift range 0.005 ≤ z ≤ 0.09 on the basis of the Sloan Digital Sky Survey (SDSS) data. Initially, the most frequently used criterion of NUV $-, r$ ≤ 5.4 was applied to identify early-type galaxies with RSF, and 19 per cent (172/913) of the sample galaxies met this criterion, in agreement with previous studies. A more robust sample of galaxies with RSF along with a stricter criterion (70 galaxies with NUV $-, r$ ≤ 5.0) were then used for further analysis, and consequently 7.7 per cent (70/913; lower limit of the RSF fraction) of the sample galaxies were classified as early-type galaxies with RSF. These galaxies tended to exhibit higher H β absorption-line strengths and stronger emission lines than quiescent (QST, NUV $-, r$ > 5.4) early-type galaxies. The most prominent feature of early-type galaxies with RSF identified in this study was that they were more metal-poor than QST galaxies owing to metal-poor stellar populations that were possibly foed from materials accreted from gas-rich satellites during (minor) mergers or interactions. The results strongly indicate that the observed RSF in the sample galaxies at the present epoch is mainly driven by external processes (i.e. mergers or interactions).
|Number of pages||9|
|Journal||Monthly Notices of the Royal Astronomical Society|
|Publication status||Published - 2022 Jan 1|
Bibliographical notePublisher Copyright:
© 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science