Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology

@article{SevillaNoarbe2021DarkES,
  title={Dark Energy Survey Year 3 Results: Photometric Data Set for Cosmology},
  author={Ignacio Sevilla-Noarbe and Keith C. Bechtol and Matias Carrasco Kind and A. Carnero Rosell and Matthew R. Becker and Alex Drlica-Wagner and Robert A. Gruendl and Eli S. Rykoff and Erin S. Sheldon and Brian Yanny and Alex Alarcon and Sahar Allam and A. Amon and Aur{\'e}lien Benoit-L{\'e}vy and Gary M. Bernstein and Emmanuel Bertin and David L. Burke and Jorge Carretero and Ami Choi and H. Thomas Diehl and S. Everett and Brenna L. Flaugher and Enrique Gazta{\~n}aga and Julia Gschwend and Ian Harrison and William G. Hartley and Ben Hoyle and Michael Jarvis and M. D. Johnson and Richard Kessler and Richard G. Kron and Nikolay Kuropatkin and Boris Leistedt and T. S. Li and Felipe Menanteau and Eric Morganson and R. L. C. Ogando and Antonella Palmese and Francisco Paz-Chinch{\'o}n and A. Pieres and Cody Pond and Mario Rodr{\'i}guez-Monroy and J. Allyn Smith and K. M. Stringer and Michael Troxel and Douglas L. Tucker and Juan Carlos de Vicente and W. Wester and Y. Zhang and Timothy M. C. Abbott and Michel Aguena and James T. Annis and Santiago {\'A}vila and S. Bhargava and S. L. Bridle and David Brooks and Dillon Brout and Francisco J. Castander and R. Cawthon and C. L. Chang and Christopher J. Conselice and Matteo Costanzi and Mart{\'i}n Crocce and L. N. da Costa and M. E. S. Pereira and Tamara M. Davis and Shantanu Desai and J. P. Dietrich and Peter Doel and Kathleen D. Eckert and August E. Evrard and I. Ferrero and Pablo Fosalba and Juan Garc{\'i}a-Bellido and David W. Gerdes and T. Giannantonio and Daniel Gruen and Gaston R. Guti{\'e}rrez and Samuel R. Hinton and Devon L. Hollowood and Klaus Honscheid and Eric M. Huff and Dragan Huterer and David J. James and Tesla E. Jeltema and Kyler W. Kuehn and Ofer Lahav and Christopher E. Lidman and Marcos Lima and H. Lin and Marcio A. G. Maia and Jennifer L. Marshall and Paul Martini and Peter Melchior and Ramon Miquel and Joseph J. Mohr and Robert Morgan and Eric H. Neilsen and Andreas Alejandro Plazas and A. K. Romer and Aaron Roodman and Eusebio S{\'a}nchez and Victor E. Scarpine and Michael S. Schubnell and Santiago Serrano and M. Smith and Eric Suchyta and Gregory G. Tarl{\'e} and D. Thomas and C. To and T. N. Varga and Risa H. Wechsler and Jochen Weller and R. D. Wilkinson},
  journal={The Astrophysical Journal Supplement Series},
  year={2021},
  volume={254}
}
We describe the Dark Energy Survey (DES) photometric data set assembled from the first three years of science operations to support DES Year 3 cosmologic analyses, and provide usage notes aimed at the broad astrophysics community. Y3 GOLD improves on previous releases from DES, Y1 GOLD, and Data Release 1 (DES DR1), presenting an expanded and curated data set that incorporates algorithmic developments in image detrending and processing, photometric calibration, and object classification. Y3… 
Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog
We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We
Dark Energy Survey Year 3 results: Optimizing the lens sample in a combined galaxy clustering and galaxy-galaxy lensing analysis
We investigate potential gains in cosmological constraints from the combination of galaxy clustering and galaxy-galaxy lensing by optimizing the lens galaxy sample selection using information from
The Simons Observatory: Development and Validation of the Large Aperture Telescope Receiver
The Simons Observatory (SO) is a ground-based cosmic microwave background (CMB) survey experiment that consists of three 0.5 m small-aperture telescopes (SATs) and one 6 m large-aperture telescope
LoVoCCS. I. Survey Introduction, Data Processing Pipeline, and Early Science Results
We present the Local Volume Complete Cluster Survey (LoVoCCS; we pronounce it as “low-vox” or “law-vox,” with stress on the second syllable), an NSF’s National Optical-Infrared Astronomy Research
MUSUBI (MegaCam Ultra-deep Survey: u*-band Imaging) Data for the COSMOS and SXDS Fields
The Subaru Hyper Suprime-Cam (HSC) Strategic Survey is the latest-generation multiband optical imaging survey for galaxy evolution and structure formation. The “Ultra-deep” component of the HSC
Dark Energy Survey Year 3 Results: Three-point shear correlations and mass aperture moments
TLDR
High signal-to-noise measurements of three-point shear correlations and the third moment of the mass aperture statistic using the first 3 years of data from the Dark Energy Survey are presented and it is determined that the measured signals are likely to be of astrophysical and gravitational origin.
Constraining the Hubble constant to a precision of about 1% using multi-band dark standard siren detections
Liang-Gui Zhu, 2 Ling-Hua Xie, Yi-Ming Hu, 2, ∗ Shuai Liu, 2, † En-Kun Li, 2, ‡ Nicola R. Napolitano, Bai-Tian Tang, Jian-dong Zhang, 2 and Jianwei Mei 2 School of Physics and Astronomy, Sun Yat-sen
Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. I. Evidence for Thermal Energy Anisotropy Using Oriented Stacking
The cosmic web contains filamentary structure on a wide range of scales. On the largest scales, superclustering aligns multiple galaxy clusters along intercluster bridges, visible through their

References

SHOWING 1-10 OF 101 REFERENCES
SExtractor: Software for source extraction
We present the automated techniques we have developed for new software that optimally detects, deblends, measures and classifies sources from astronomical images: SExtractor ( Source Extractor  ). We
Bayesian Photometric Redshift Estimation
Photometric redshifts are quickly becoming an essential tool of observational cosmology, although their utilization is somewhat hindered by certain shortcomings of the existing methods, e.g., the
The impact of spectroscopic incompleteness in direct calibration of redshift distributions for weak lensing surveys
Obtaining accurate distributions of galaxy redshifts is a critical aspect of weak lensing cosmology experiments. One of the methods used to estimate and validate redshift distributions is apply
Dark Energy Survey Year 1 Results: The Photometric Data Set for Cosmology
We describe the creation, content, and validation of the Dark Energy Survey (DES) internal year-one cosmology data set, Y1A1 GOLD, in support of upcoming cosmological analyses. The Y1A1 GOLD data set
A New, Large-scale Map of Interstellar Reddening Derived from H i Emission
We present a new map of interstellar reddening, covering the 39% of the sky with low H i column densities ( N H I < 4 × 10 20 cm−2 or E ( B − V ) ≈ 45 mmag) at 16 .′ 1 resolution, based on all-sky
Techniques and Review of Absolute Flux Calibration from the Ultraviolet to the Mid-Infrared
The measurement of precise absolute fluxes for stellar sources has been pursued with increased vigor since the discovery of dark energy and the realization that its detailed understanding requires
ANNz: Estimating Photometric Redshifts Using Artificial Neural Networks
We introduce ANNz, a freely available software package for photometric redshift estimation using artificial neural networks. ANNz learns the relation between photometry and redshift from an
DES science portal: Creating science-ready catalogs
The Dark Energy Survey Image Processing Pipeline
The Dark Energy Survey (DES) is a five-year optical imaging campaign with the goal of understanding the origin of cosmic acceleration. DES performs a ∼5000 deg2 survey of the southern sky in five
ANNz2: Photometric Redshift and Probability Distribution Function Estimation using Machine Learning
We present ANNz2, a new implementation of the public software for photometric redshift (photo-z) estimation of Collister & Lahav, which now includes generation of full probability distribution
...
...