We present measurements of dust reddening using the colors of stars with spectra in the Sloan Digital Sky Survey. We measure reddening as the difference between the measured and predicted colors of a star, as derived from stellar parameters from the SEGUE Stellar Parameter Pipeline (Lee et al. 2008a). We achieve uncertainties of 56, 34, 25, and 29 mmag in the colors u − g, g − r, r − i, and i − z, per star, though the uncertainty varies depending on the stellar type and the magnitude of the star. The spectrum-based reddening measurements confirm our earlier "blue tip" reddening measurements (Schlafly et al. 2010, S10), finding reddening coefficients different by −3%, 1%, 1%, and 2% in u − g, g − r, r − i, and i − z from those found by the blue tip method, after removing a 4% normalization difference. These results prefer an R V = 3.1 Fitzpatrick (1999, F99) reddening law to O'Donnell (1994) or Cardelli et al. (1989) reddening laws. We provide a table of conversion coefficients from the Schlegel et al. (1998, SFD) maps of E(B − V ) to extinction in 88 bandpasses for 4 values of R V , using this reddening law and the 14% recalibration of SFD first reported by S10 and confirmed in this work.
We present optical light curves, redshifts, and classifications for 365 spectroscopically confirmed Type Ia supernovae (SNe Ia) discovered by the Pan-STARRS1 (PS1) Medium Deep Survey. We detail improvements to the PS1 SN photometry, astrometry and calibration that reduce the systematic uncertainties in the PS1 SN Ia distances. We combine the subset of 279 PS1 SN Ia (0.03 < z < 0.68) with useful distance estimates of SN Ia from SDSS, SNLS, various low-z and HST samples to form the largest combined sample of SN Ia consisting of a total of 1048 SN Ia ranging from 0.01 < z < 2.3, which we call the 'Pantheon Sample'. When combining Planck 2015 CMB measurements with the Pantheon SN sample, we find Ω m = 0.307±0.012 and w = −1.026±0.041 for the wCDM model. When the SN and CMB constraints are combined with constraints from BAO and local H 0 measurements, the analysis yields the most precise measurement of dark energy to date: w 0 = −1.007 ± 0.089 and w a = −0.222 ± 0.407 for the w 0 w a CDM model. Tension with a cosmological constant previously seen in an analysis of PS1 and low-z SNe has diminished after an increase of 2× in the statistics of the PS1 sample, improved calibration and photometry, and stricter light-curve quality cuts. We find the systematic uncertainties in our measurements of dark energy are almost as large as the statistical uncertainties, primarily due to limitations of modeling the low-redshift sample. This must be addressed for future progress in using SN Ia to measure dark energy.
We present a new three-dimensional map of dust reddening, based on Gaia parallaxes and stellar photometry from Pan-STARRS 1 and 2MASS. This map covers the sky north of a declination of −30 • , out to a distance of several kiloparsecs. This new map contains three major improvements over our previous work. First, the inclusion of Gaia parallaxes dramatically improves distance estimates to nearby stars. Second, we incorporate a spatial prior that correlates the dust density across nearby sightlines. This produces a smoother map, with more isotropic clouds and smaller distance uncertainties, particularly to clouds within the nearest kiloparsec. Third, we infer the dust density with a distance resolution that is four times finer than in our previous work, to accommodate the improvements in signal-to-noise enabled by the other improvements. As part of this work, we infer the distances, reddenings and types of 799 million stars. We obtain typical reddening uncertainties that are ∼30% smaller than those reported in the Gaia DR2 catalog, reflecting the greater number of photometric passbands that enter into our analysis. Our 3D dust map can be accessed at doi:10.7910/DVN/2EJ9TX or through the Python package dustmaps. Our catalog of stellar parameters can be accessed at
The DESI Legacy Imaging Surveys (http://legacysurvey.org/) are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image ≈14,000 deg 2 of the extragalactic sky visible from the northern hemisphere in three optical bands (g, r, and z) using telescopes at the Kitt Peak National Observatory and the Cerro Tololo Inter-American Observatory. The combined survey footprint is split into two contiguous areas by the Galactic plane. The optical imaging is conducted using a unique strategy of dynamically adjusting the exposure times and pointing selection during observing that results in a survey of nearly uniform depth. In addition to calibrated images, the project is delivering a catalog, constructed by using a probabilistic inference-based approach to estimate source shapes and brightnesses. The catalog includes photometry from the grz optical bands and from four mid-infrared bands (at 3.4, 4.6, 12, and 22 μm) observed by the Wide-field Infrared Survey Explorer satellite during its full operational lifetime. The project plans two public data releases each year. All the software used to generate the catalogs is also released with the data. This paper provides an overview of the Legacy Surveys project.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.