Photometric recalibration of the SDSS Stripe 82 to a few milimagnitude precision with the stellar color regression method and Gaia EDR3

Abstract

By combining spectroscopic data from the LAMOST DR7, SDSS DR12, and corrected photometric data from the Gaia EDR3, we apply the Stellar Color Regression (SCR; Yuan et al. 2015a) method to recalibrate the SDSS Stripe 82 standard stars catalog of Ivezić et al. (2007). With a total number of about 30,000 spectroscopically targeted stars, we have mapped out the relatively large and strongly correlated photometric zero-point errors present in the catalog, $\sim$2.5 per cent in the $u$ band and $\sim$ 1 per cent in the $griz$ bands. Our study also confirms some small but significant magnitude dependence errors in the $z$ band for some charge-coupled devices. Various tests show that we have achieved an internal precision of about 5 mmag in the $u$ band and about 2 mmag in the $griz$ bands, which is about 5 times better than previous results. We also apply the method to the latest version of the catalog (V4.2; Thanjavur et al. 2021), and find modest systematic calibration errors up to $\sim$ 1 per cent along the R.A. direction and smaller errors along the Dec. direction. The results demonstrate the power of the SCR method when combining spectroscopic data and Gaia photometry in breaking the 1 percent precision barrier of ground-based photometric surveys. Our work paves the way for the re-calibration of the whole SDSS photometric survey and has important implications for the calibration of future surveys. Future implementations and improvements of the SCR method under different situations are also discussed.

arXiv comment21 pages, 20 figures, 9 tables, ApJS in press

References in corpus (47)

• Maps of Dust IR Emission for Use in Estimation of Reddening and CMBR Foregrounds
• The Sloan Digital Sky Survey: Technical Summary
• Gaia Data Release 2. Summary of the contents and survey properties
• The Gaia mission
• LSST: from Science Drivers to Reference Design and Anticipated Data Products
• The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III
• SEGUE: A Spectroscopic Survey of 240,000 stars with g=14-20
• The First Data Release (DR1) of the LAMOST general survey
• The GALAH Survey: Scientific Motivation
• Planck 2013 results. XI. All-sky model of thermal dust emission
• Gaia Early Data Release 3: Photometric content and validation
• Homogeneous Photometry for Star Clusters and Resolved Galaxies. II. Photometric Standard Stars
• LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) The survey science plan
• The SEGUE Stellar Parameter Pipeline. I. Description and Initial Validation Tests
• APOGEE Data and Spectral Analysis from SDSS Data Release 16: Seven Years of Observations Including First Results from APOGEE-South
• SDSS Data Management and Photometric Quality Assessment
• SkyMapper Southern Survey: First Data Release (DR1)
• Photometric Calibration of the First 1.5 Years of the Pan-STARRS1 Survey
• Empirical extinction coefficients for the GALEX, SDSS, 2MASS and WISE passbands
• UBVRI Photometric Standard Stars Around the Celestial Equator: Updates and Additions
• SDSS Standard Star Catalog for Stripe 82: the Dawn of Industrial 1% Optical Photometry
• The SEGUE Stellar Parameter Pipeline. II. Validation with Galactic Globular and Open Clusters
• J-PLUS: The Javalambre Photometric Local Universe Survey
• Automatic Determination of Stellar Atmospheric Parameters and Construction of Stellar Spectral Templates of the Guoshoujing Telescope (LAMOST)
• The Southern Photometric Local Universe Survey (S-PLUS): improved SEDs, morphologies and redshifts with 12 optical filters
• The LAMOST Stellar Parameter Pipeline at Peking University --- LSP3
• Hypercalibration: A Pan-STARRS1-based recalibration of the Sloan Digital Sky Survey
• Stellar Locus Regression: Accurate Color Calibration, and the Real-time Determination of Galaxy Cluster Photometric Redshifts
• Forward Global Photometric Calibration of the Dark Energy Survey
• Toward 1% Photometry: End-to-end Calibration of Astronomical Telescopes and Detectors
• Estimating stellar atmospheric parameters, absolute magnitudes and elemental abundances from the LAMOST spectra with Kernel-based Principal Component Analysis
• Beyond spectroscopy. I. Metallicities, distances, and age estimates for over twenty million stars from SMSS DR2 and Gaia EDR3
• LSS-GAC - A LAMOST Spectroscopic Survey of the Galactic Anti-center
• Milky Way Tomography with the SkyMapper Southern Survey. II. Photometric Re-calibration of SMSS DR2
• J-PLUS: photometric calibration of large area multi-filter surveys with stellar and white dwarf loci
• Stellar color regression: a spectroscopy based method for color calibration to a few mmag accuracy and the recalibration of Stripe 82
• The SAGE Photometric Sky Survey: Technical Description
• Stellar Loci V: Photometric Metallicities of 27 Million FGK Stars based on Gaia Early Data Release 3
• Stellar loci I. Metallicity dependence and intrinsic widths
• Correction to the photometric colors of Gaia Early Data Release 3
• Photometric Cross-Calibration of the SDSS Stripe 82 Standard Stars catalogue with Gaia EDR3, and Comparison with Pan-STARRS1, DES, CFIS and GALEX catalogues
• Correction to the photometric magnitudes of the Gaia Early Data Release 3
• Stellar loci III: Photometric metallicities for half million FGK stars of Stripe 82
• Correction to the photometric colors of the Gaia Data Release 2 with the stellar color regression method
• Dust in the outskirts of M31 and M33
• Determining thermal dust emission from Planck HFI data using a sparse, parametric technique
• Photometric calibration for the Beijing-Arizona Sky Survey and Mayall z-band Legacy Survey

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• Gaia Data Release 3: The Galaxy in your preferred colours. Synthetic photometry from Gaia low-resolution spectra
• Empirical temperature- and extinction-dependent extinction coefficients for the GALEX, Pan-STARRS1, Gaia, SDSS, 2MASS, and WISE passbands
• J-PLUS: Stellar Parameters, C, N, Mg, Ca and [α/Fe] Abundances for Two Million Stars from DR1
• Photometric calibration of the Stellar Abundance and Galactic Evolution Survey (SAGES): Nanshan One-meter Wide-field Telescope g, r, and i band imaging data
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