Probing the distance and morphology of the Large Magellanic Cloud with RR Lyrae stars
Christopher R. Klein, S. B. Cenko, Adam A. Miller, Dara J. Norman, and, Joshua S. Bloom

TL;DR
This study uses Bayesian analysis of RR Lyrae stars' light curves to precisely measure the Large Magellanic Cloud's distance and morphology, improving accuracy over previous estimates.
Contribution
It introduces a Bayesian method combining multi-band light curves to determine LMC distances and structure with unprecedented precision.
Findings
Measured LMC distance as 50.25 kpc with 0.4% statistical error
Determined maximum tilt angle of 11.84 degrees
Provided highly precise RR Lyrae period-magnitude relations
Abstract
We present a Bayesian analysis of the distances to 15,040 Large Magellanic Cloud (LMC) RR Lyrae stars using - and -band light curves from the Optical Gravitational Lensing Experiment, in combination with new -band observations from the Dark Energy Camera. Our median individual RR Lyrae distance statistical error is 1.89 kpc (fractional distance error of 3.76 per cent). We present three-dimensional contour plots of the number density of LMC RR Lyrae stars and measure a distance to the core LMC RR Lyrae centre of , equivalently . This finding is statistically consistent with and four times more precise than the canonical value determined by a recent meta-analysis of 233 separate LMC distance determinations. We also measure a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomical Observations and Instrumentation · Adaptive optics and wavefront sensing
