Unveiling Long-Period Variables in M33's Central Region: Insights into Stellar Evolution and Star Formation via Near-Infrared Photometry

TL;DR

This study uses near-infrared photometry and PSF analysis of M33's core to identify and characterize long-period variable stars, enhancing understanding of stellar evolution and star formation in dense regions.

Contribution

It introduces a PSF photometry method applied to multi-epoch near-infrared data to effectively detect and analyze LPVs in M33's crowded central region, improving upon traditional aperture photometry.

Findings

Identified approximately 750 LPVs in M33's center.

Demonstrated PSF photometry's superiority in crowded fields.

Provided a comprehensive catalog for future stellar variability studies.

Abstract

We present an analysis of UKIRT observations obtained between 2003 and 2007 to investigate the evolved stellar populations within the central square kiloparsec of M33. Point-spread function (PSF) photometry is employed to mitigate the effects of stellar crowding and to ensure accurate measurements in this densely populated region. This method, applied to merged observations from UIST and WFCAM in the $J$, $H$, and $K$ bands, extracts $211,179$ stars by cross-matching frame-by-frame across 39 observing nights in three bands. From this, we identify approximately 750 long-period variables (LPVs), predominantly Asymptotic Giant Branch (AGB) stars, by cross-matching PSF results with aperture photometry, focusing on the UIST field for robust variability confirmation. The PSF approach proves particularly effective for resolving blended sources and detecting faint, dusty variables that might remain undetected. We also examined aperture photometry data to validate our results; however, the PSF-derived measurements provide superior depth and completeness, particularly for obscured stellar populations. The resulting master catalog provides a basis for future analyses of variability amplitudes, periods, and star-formation history (SFH), paving the way for a deeper understanding of mass-loss and the dynamical evolution of the central region of M33.