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We present Augustus , a catalog of distance, extinction, and stellar parameter estimates for 170 million stars from 14 mag < r < 20 mag and with ∣ b ∣ > 10° drawing on a combination of optical to near-infrared photometry from Pan-STARRS, 2MASS, UKIDSS, and unWISE along with parallax measurements from Gaia DR2 and 3D dust extinction maps. After applying quality cuts, we find 125 million objects have “high-quality” posteriors with statistical distance uncertainties of ≲10% for objects with well-constrained stellar types. This is a substantial improvement over the distance estimates derived from Gaia parallaxes alone and in line with the recent results from Anders et al. We find the fits are able to reproduce the dereddened Gaia color–magnitude diagram accurately, which serves as a useful consistency check of our results. We show that we are able to detect large, kinematically coherent substructures in our data clearly relative to the input priors, including the Monoceros Ring and the Sagittarius Stream, attesting to the quality of the catalog. Our results are publicly available at doi:10.7910/DVN/WYMSXV. An accompanying interactive visualization can be found at http://allsky.s3-website.us-east-2.amazonaws.com .

Diffuse interstellar bands (DIBs) are broad absorption features associated with interstellar dust and can serve as chemical and kinematic tracers. Conventional measurements of DIBs in stellar spectra are complicated by residuals between observations and best-fit stellar models. To overcome this, we simultaneously model the spectrum as a combination of stellar, dust, and residual components, with full posteriors on the joint distribution of the components. This decomposition is obtained by modeling each component as a draw from a high-dimensional Gaussian distribution in the data space (the observed spectrum)—a method we call “Marginalized Analytic Data-space Gaussian Inference for Component Separation” (MADGICS). We use a data-driven prior for the stellar component, which avoids missing stellar features not well modeled by synthetic spectra. This technique provides statistically rigorous uncertainties and detection thresholds, which are required to work in the low signal-to-noise regime that is commonplace for dusty lines of sight. We reprocess all public Gaia DR3 RVS spectra and present an improved 8621 Å DIB catalog, free of detectable stellar line contamination. We constrain the rest-frame wavelength to 8623.14 ± 0.087 Å (vacuum), find no significant evidence for DIBs in the Local Bubble from the 1/6th of RVS spectra that are public, and show unprecedented correlation with kinematic substructure in Galactic CO maps. We validate the catalog, its reported uncertainties, and biases using synthetic injection tests. We believe MADGICS provides a viable path forward for large-scale spectral line measurements in the presence of complex spectral contamination.

Deep optical and near-infrared imaging of the entire Galactic plane is essential for understanding our Galaxy’s stars, gas, and dust. The second data release of the Dark Energy Camera (DECam) Plane Survey extends the five-band optical and near-infrared survey of the southern Galactic plane to cover 6.5% of the sky, ∣ b ∣ ≤ 10°, and 6° > ℓ > −124°, complementary to coverage by Pan-STARRS1. Typical single-exposure effective depths, including crowding effects and other complications, are 23.5, 22.6, 22.1, 21.6, and 20.8 mag in g , r , i , z , and Y bands, respectively, with around 1″ seeing. The survey comprises 3.32 billion objects built from 34 billion detections in 21,400 exposures, totaling 260 hr open shutter time on the DECam at Cerro Tololo. The data reduction pipeline features several improvements, including the addition of synthetic source injection tests to validate photometric solutions across the entire survey footprint. A convenient functional form for the detection bias in the faint limit was derived and leveraged to characterize the photometric pipeline performance. A new postprocessing technique was applied to every detection to debias and improve uncertainty estimates of the flux in the presence of structured backgrounds, specifically targeting nebulosity. The images and source catalogs are publicly available at http://decaps.skymaps.info/ .