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arXiv · 2507.01343

47 Tuc in Rubin Data Preview 1: Exploring Early LSST Data and Science Potential

Yumi Choi·Knut A. G. Olsen·Jeffrey L. Carlin·Yuankun·Wang·Fred Moolekamp·Abhijit Saha·Ian Sullivan·Colin T. Slater·Douglas L. Tucker·Christina L. Adair·Peter S. Ferguson·Yijung Kang·Karla Peña Ramírez·Markus Rabus
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Abstract

We present analyses of the early data from Rubin Observatory's Data Preview 1 (DP1) for the globular cluster 47 Tuc field. The DP1 dataset for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands ($ugriy$). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star-galaxy separation by fitting fifth-degree polynomials to the stellar loci in color-color diagrams and applying multi-dimensional sigma clipping. We compile a catalog of 3,576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color-color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color-color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover five known variable stars, including three RR Lyrae and two eclipsing binaries, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely-sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

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Yumi Choi, Knut A. G. Olsen, Jeffrey L. Carlin, Yuankun, Wang, Fred Moolekamp, Abhijit Saha, Ian Sullivan, Colin T. Slater, Douglas L. Tucker, Christina L. Adair, Peter S. Ferguson, Yijung Kang, Karla Peña Ramírez, Markus Rabus. 2025-07-02. 47 Tuc in Rubin Data Preview 1: Exploring Early LSST Data and Science Potential. https://arxiv.org/abs/2507.01343

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