The RR Lyrae Delay-time Distribution: A Novel Perspective on Models of Old Stellar Populations

Sumit K. Sarbadhicary*, Mairead Heiger, Carles Badenes, Cecilia Mateu, Jeffrey A. Newman, Robin Ciardullo, Na'Ama Hallakoun, Dan Maoz, Laura Chomiuk

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The delay-time distribution (DTD) is the occurrence rate of a class of objects as a function of time after a hypothetical burst of star formation. DTDs are mainly used as a statistical test of stellar evolution scenarios for supernova progenitors, but they can be applied to many other classes of astronomical objects. We calculate the first DTD for RR Lyrae variables using 29,810 RR Lyrae from the OGLE-IV survey and a map of the stellar age distribution (SAD) in the Large Magellanic Cloud (LMC). We find that ∼46% of the OGLE-IV RR Lyrae are associated with delay times greater than 8 Gyr (main-sequence progenitor masses less than 1 M o˙), and consistent with existing constraints on their ages, but surprisingly about 51% of RR Lyrae appear to have delay times of 1.2-8 Gyr (main-sequence masses between 1 and 2 M o˙ at LMC metallicity). This intermediate-age signal also persists outside the Bar region, where crowding is less of a concern, and we verified that without this signal the spatial distribution of the OGLE-IV RR Lyrae is inconsistent with the SAD map of the LMC. Since an intermediate-age RR Lyrae channel is in tension with the lack of RR Lyrae in intermediate-age clusters (noting issues with small-number statistics), and noting the age-metallicity constraints on LMC stars, our DTD result possibly indicates that systematic uncertainties may still exist in SAD measurements of old stellar populations, perhaps stemming from the construction methodology or the stellar evolution models used. We describe tests to further investigate this issue.

Original languageEnglish
Article number140
JournalAstrophysical Journal
Volume912
Issue number2
DOIs
StatePublished - 10 May 2021

Funding

FundersFunder number
National Science Foundation1907790

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