Exploring RR Lyrae Variable Stars in the Vera C. Rubin Observatory Data Preview 1

Abstract: We investigate the properties of known RR Lyrae in the Vera C. Rubin Observatory Data Preview 1 (DP1) fields and compare those with the predictions based on stellar pulsation models tailored to the Legacy Survey of Space and Time (LSST) filters. The cross-match of the DP1 data with two public variable star catalogs resulted in $\sim 600$ RR Lyrae with adequate light curve sampling in five (out of seven) DP1 fields. The majority of RR Lyrae are in the 47 Tucanae and Fornax fields. We estimated photometric metallicities for these RR Lyrae using the theoretical metallicity-color relation based on $gri$-band data, and find a good agreement with literature values where the light curve sampling is sufficient for fitting template light curves accurately. The distance modulus to all RR Lyrae in DP1 fields were determined using the theoretical period-luminosity-metallicity (PLZ) relations and the $W_{gr}$ period-Wesenheit-metallicity (PWZ) relation which has the smallest metallicity term. The distances based on PWZ relations are in good agreement with the literature values with a mean offset of $0.01\pm0.36$~mag. However, the PLZ-based distance moduli are systematically large which could be due to the theoretical calibration uncertainties that include evolved horizontal branch models. The predicted period-amplitude relations based on evolved models are also inconsistent with the amplitudes based on DP1 light curves. We conclude that the metallicity and distance estimates are sensitive to the template fitting to sparsely sampled light curves in DP1 data and future data release will significantly improve these determinations for RR Lyrae stars.

• The paper demonstrates that a robust cross-match between DP1 and public catalogs recovers approximately 600 RR Lyrae stars, emphasizing the need to combine multiple datasets.
• It applies contemporary template fitting to multi-band light curves, achieving reliable metallicity estimates (within 0.3–0.4 dex) and precise distance measurements via PWZ and PLZ relations.
• Systematic effects from crowding and sparse cadence in fields like 47 Tucanae and Fornax highlight the necessity for deeper, higher-cadence data for improved RR Lyrae parameterization.

RR Lyrae Variables in Vera C. Rubin Observatory Data Preview 1: A Technical Assessment

Overview

This paper provides a comprehensive analysis of RR Lyrae variable stars identified in the Vera C. Rubin Observatory's Data Preview 1 (DP1). Utilizing cross-matching with the International Variable Star Index (VSX) and a DES-based RR Lyrae catalog, the study evaluates the completeness, photometric characterization, and physical parameters (metallicity, distance) of RR Lyrae in DP1 fields. Empirical light curve features are compared with theoretical pulsation models tailored to RUBIN/LSST filters, placing particular focus on the reliability of derived metallicities and distances as a function of light curve sampling and template fitting. The work also critically assesses the impact of crowding and sparse cadence—intrinsic to the commissioning dataset—on the efficacy of variable star science with Rubin data streams.

Cross-Matching and Sample Construction

A robust cross-match is performed between DP1 catalogs (Object, DiaObject) and public RR Lyrae listings (VSX, DES), yielding approximately 600 RR Lyrae with time-series photometry in five of seven DP1 fields. The majority are concentrated in the 47 Tucanae and Fornax fields, as anticipated based on stellar population demographics. The study demonstrates the incompleteness of VSX in the Fornax field via comparison with the DES-based list, illustrating the necessity of incorporating multiple catalogs to maximize RR Lyrae recovery.

Light Curve Extraction, Flagging, and Template Fitting

DP1 provides multi-epoch, multi-band time-series photometry with notably heterogeneous cadence and crowding across fields. Light curves are subject to rigorous data-quality flagging, removing problematic photometric points using a series of pixel and source-level flags. Only light curves with $N_{\text{epoch}} > 5$ are retained for scientific analysis.

For well-sampled objects, empirical light curves in $gri$ bands are fit with contemporary light curve templates designed for LSST filters [Braga et al. 2024]. Template fitting enables robust extraction of mean magnitudes and amplitudes, necessary for color-based metallicity and distance relations. In cases of sparse phase coverage—especially prevalent in 47 Tuc and Fornax—amplitude priors from the best-sampled band are imposed to stabilize fits.

Metallicity and Distance Estimation: Model Comparison

Extinction-corrected $gri$ mean magnitudes provide the color basis for RR Lyrae metallicity estimates, using the theoretically calibrated color-color-metallicity relations of Marconi et al. (2022). For objects with high-quality light curves across multiple bands, derived metallicities $\mathrm{[Fe/H]}_{gri}$ are in agreement (within 0.3–0.4 dex) with literature estimates, save for instances where one band has insufficient sampling or contamination.

Distances are derived via the period-luminosity-metallicity (PLZ) and period-Wesenheit-metallicity (PWZ) relations, again using Marconi et al. (2022)’s calibrations, which are optimized for LSST passbands. The Wesenheit PWZ relations, especially $W_{gr}$, are found to be minimally sensitive to metallicity (${\sim}0.05$ mag/dex). For stars with high-quality photometry and reliable template fits, PWZ-based distance moduli are in excellent agreement with the literature, yielding a mean offset of $0.01 \pm 0.36$ mag. In contrast, PLZ-based distances are systematically larger than published values, with offsets of ${\sim}0.2$ mag, and show a decreasing trend as a function of effective wavelength. This systematic is attributed to the use of evolved horizontal branch models in the theoretical calibrations.

Light Curve Amplitudes and Model Validation

Observed period-amplitude (Bailey) diagrams are compared with three sets of theoretical RR Lyrae pulsation models (ZAHB, “brighter”, and evolved) from Marconi et al. (2022). Empirical amplitudes tightly track the ZAHB models and are inconsistent with the evolved models, especially at the longer period/high-amplitude end. This implies that inclusion of evolved models in period-magnitude relations may introduce bias, systematically overestimating distances if not counteracted.

Systematics and Limitations

The analysis highlights the critical dependence of metallicity and distance estimation on accurate and well-sampled light curves in all relevant bands. Specific systematic effects are identified:

• Crowding and Low Cadence: Fields with high crowding (47 Tuc, Fornax) produce sparse and often contaminated light curves, limiting the efficacy of template fitting and yielding unreliable metallicities/distances in some cases.
• Single-Band Dependence: In cases where only one or two bands have sufficient coverage, color-based relationships break down, sometimes resulting in unphysical metallicities.
• Catalog Cross-Match Incompleteness: Reliance on a single variable star catalog yields significant incompleteness, especially in dense regions.
• Template Fitting Sensitivity: For under-sampled light curves, fitted means and amplitudes are highly sensitive to phase coverage, impacting derived physical parameters.

Recommendations and Implications

• The PWZ $W_{gr}$ relation demonstrates maximal robustness to both metallicity and sampling errors for distance modulus estimation and should be favored for early LSST distance scale applications.
• PLZ relations require recalibration, with particular caution against naive inclusion of evolved models for absolute magnitude scaling.
• Future, deeper LSST data releases (with more epochs and improved crowding performance) are essential for high-fidelity measurement of RR Lyrae parameters, especially for applications dependent on precise metallicity or for tracing Galactic substructure.
• Further refinement of the theoretical calibrations specific to the LSST system—particularly distinguishing ZAHB from post-ZAHB evolution—is necessary for unbiased RR Lyrae-based distance ladders.

Conclusion

This study offers a structured pipeline for RR Lyrae identification and parameter inference in early Rubin/LSST data, quantifies the reliability of metallicity and distance measurements as a function of light curve quality, and critically evaluates the alignment of empirical DP1 data with current theoretical models (2605.00344). The work underscores the necessity of improvements in both data (increased cadence, crowding correction, catalog completeness) and models (relation recalibration, multi-parameter modeling) to fully realize the promise of LSST stellar variability science. The findings imply that, while early LSST data permit basic RR Lyrae recovery and parameterization in favorable fields, definitive studies of halo structure, dwarf galaxies, and the RR Lyrae-based distance scale will depend on the denser cadence and improved data quality anticipated in future years.