scholarly journals Pushing automated morphological classifications to their limits with the Dark Energy Survey

2021 ◽  
Author(s):  
J Vega-Ferrero ◽  
H Domínguez Sánchez ◽  
M Bernardi ◽  
M Huertas-Company ◽  
R Morgan ◽  
...  
Keyword(s):  
Dark Energy ◽  
Classification Scheme ◽  
Learning Algorithm ◽  
Small Subset ◽  
Early Type ◽  
Lenticular Galaxies ◽  
Dark Energy Survey ◽  
Deep Learning Algorithm ◽  
Data Release ◽  
Energy Survey

Abstract We present morphological classifications of ∼27 million galaxies from the Dark Energy Survey (DES) Data Release 1 (DR1) using a supervised deep learning algorithm. The classification scheme separates: (a) early-type galaxies (ETGs) from late-types (LTGs), and (b) face-on galaxies from edge-on. Our Convolutional Neural Networks (CNNs) are trained on a small subset of DES objects with previously known classifications. These typically have mr ≲ 17.7mag; we model fainter objects to mr < 21.5 mag by simulating what the brighter objects with well determined classifications would look like if they were at higher redshifts. The CNNs reach 97% accuracy to mr < 21.5 on their training sets, suggesting that they are able to recover features more accurately than the human eye. We then used the trained CNNs to classify the vast majority of the other DES images. The final catalog comprises five independent CNN predictions for each classification scheme, helping to determine if the CNN predictions are robust or not. We obtain secure classifications for ∼ 87% and 73% of the catalog for the ETG vs. LTG and edge-on vs. face-on models, respectively. Combining the two classifications (a) and (b) helps to increase the purity of the ETG sample and to identify edge-on lenticular galaxies (as ETGs with high ellipticity). Where a comparison is possible, our classifications correlate very well with Sérsic index (n), ellipticity (ε) and spectral type, even for the fainter galaxies. This is the largest multi-band catalog of automated galaxy morphologies to date.

scholarly journals OzDES multifibre spectroscopy for the Dark Energy Survey: 3-yr results and first data release

2017 ◽  
Vol 472 (1) ◽  
pp. 273-288 ◽  
Author(s):  
M. J. Childress ◽  
C. Lidman ◽  
T. M. Davis ◽  
B. E. Tucker ◽  
J. Asorey ◽  
...  
Keyword(s):  
Dark Energy ◽  
Dark Energy Survey ◽  
Data Release ◽  
Energy Survey

scholarly journals The Dark Energy Survey: Data Release 1

2018 ◽  
Vol 239 (2) ◽  
pp. 18 ◽  
Author(s):  
T. M. C. Abbott ◽  
F. B. Abdalla ◽  
S. Allam ◽  
A. Amara ◽  
J. Annis ◽  
...  
Keyword(s):  
Dark Energy ◽  
Survey Data ◽  
Dark Energy Survey ◽  
Data Release ◽  
Energy Survey

scholarly journals The WiggleZ Dark Energy Survey: final data release and the metallicity of UV-luminous galaxies

2017 ◽  
Vol 474 (3) ◽  
pp. 4151-4168 ◽  
Author(s):  
Michael J Drinkwater ◽  
Zachary J Byrne ◽  
Chris Blake ◽  
Karl Glazebrook ◽  
Sarah Brough ◽  
...  
Keyword(s):  
Dark Energy ◽  
Dark Energy Survey ◽  
Luminous Galaxies ◽  
Data Release ◽  
Final Data ◽  
Energy Survey

scholarly journals Quasar lenses in the south: searches over the DES public footprint

2019 ◽  
Vol 489 (2) ◽  
pp. 2525-2535 ◽  
Author(s):  
Adriano Agnello ◽  
Chiara Spiniello
Keyword(s):  
Dark Energy ◽  
Selection Criteria ◽  
High Grade ◽  
X Ray ◽  
Dark Energy Survey ◽  
Public Data ◽  
Data Release ◽  
Energy Survey ◽  
Selection Of

ABSTRACT We have scanned 5000 deg2 of Southern Sky to search for strongly lensed quasars with five methods, all source oriented, but based on different assumptions and selection criteria. We present a list of high-grade candidates from each method (totalling 98 unique, new candidates), to facilitate follow-up spectroscopic campaigns, including two previously unknown quadruplets, WG 210014.9-445206.4 and WG 021416.37-210535.3. We analyse morphological searches based on Gaia multiplet detection and astrometric offsets, fibre-spectroscopic pre-selection, and X-ray and radio pre-selection. The performance and complementarity of the methods are evaluated on a common sample of known lenses in the Dark Energy Survey public Data Release 1 (DR1) footprint. We recovered in total 13 known lenses, of which 8 are quadruplets. Morphological and colour selection of objects, from the WISE andGaia-DR2 surveys, recovers most of those known lenses, but searches in the radio and X-ray cover regimes that are beyond the completeness of Gaia. Given the footprint, pre-selection, and depth limits, the current number of quads indicates that the union of these searches is complete, and the expected purity on high-grade candidates is ${\approx}60{{\ \rm per\ cent}}$. Ongoing, spectroscopic campaigns confirm this estimate.

scholarly journals OzDES multi-object fibre spectroscopy for the Dark Energy Survey: results and second data release

2020 ◽  
Vol 496 (1) ◽  
pp. 19-35 ◽  
Author(s):  
C Lidman ◽  
B E Tucker ◽  
T M Davis ◽  
S A Uddin ◽  
J Asorey ◽  
...  
Keyword(s):  
Dark Energy ◽  
Galactic Nuclei ◽  
Wide Field ◽  
Dark Energy Survey ◽  
Data Release ◽  
History Of ◽  
Survey Results ◽  
Deep Fields ◽  
The Masses ◽  
Energy Survey

ABSTRACT We present a description of the Australian Dark Energy Survey (OzDES) and summarize the results from its 6 years of operations. Using the 2dF fibre positioner and AAOmega spectrograph on the 3.9-m Anglo-Australian Telescope, OzDES has monitored 771 active galactic nuclei, classified hundreds of supernovae, and obtained redshifts for thousands of galaxies that hosted a transient within the 10 deep fields of the Dark Energy Survey. We also present the second OzDES data release, containing the redshifts of almost 30 000 sources, some as faint as rAB = 24 mag, and 375 000 individual spectra. These data, in combination with the time-series photometry from the Dark Energy Survey, will be used to measure the expansion history of the Universe out to z ∼ 1.2 and the masses of hundreds of black holes out to z ∼ 4. OzDES is a template for future surveys that combine simultaneous monitoring of targets with wide-field imaging cameras and wide-field multi-object spectrographs.

scholarly journals The WiggleZ Dark Energy Survey: survey design and first data release

2010 ◽  
Vol 401 (3) ◽  
pp. 1429-1452 ◽  
Author(s):  
Michael J. Drinkwater ◽  
Russell J. Jurek ◽  
Chris Blake ◽  
David Woods ◽  
Kevin A. Pimbblet ◽  
...  
Keyword(s):  
Dark Energy ◽  
Survey Design ◽  
Dark Energy Survey ◽  
Data Release ◽  
Energy Survey

scholarly journals Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

2022 ◽  
Vol 258 (1) ◽  
pp. 15
Author(s):  
S. Everett ◽  
B. Yanny ◽  
N. Kuropatkin ◽  
E. M. Huff ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Dark Energy ◽  
Transfer Function ◽  
Real Data ◽  
Generative Models ◽  
Density Fluctuations ◽  
Proximity Effects ◽  
Small Subset ◽  
Data Set ◽  
Dark Energy Survey ◽  
Energy Survey

Abstract 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 systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant “source” galaxies and magnification biases of nearer “lens” galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1–8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

scholarly journals Remarkable Spiral Galaxies in Dark Energy Survey Data Release 2

2021 ◽  
Author(s):  
Michael J Longo
Keyword(s):  
Dark Energy ◽  
Survey Data ◽  
Spiral Galaxies ◽  
Massive Black Hole ◽  
Dark Energy Survey ◽  
Data Release ◽  
The Galaxy ◽  
Long Tails ◽  
Apparent Diameter ◽  
Energy Survey

A visual study of spiral galaxies from a subset of spiral galaxies in the Dark Energy Survey Data Release 2 finds that a significant number show long tails of baryonic matter, often much longer than the apparent diameter of the galaxy. Examples from less than 10% of the candidates are shown here and their possible origin is discussed. The tails were only seen connected to spiral galaxies; no examples of tails connected to elliptical galaxies or to artifacts were found. In many examples the tail is associated with what appears to be a colliding galaxy, but in many others there is no sign of one. An intriguing possibility is that in the latter cases the tails are produced by an encounter with an unseen object, either a massive black hole or a compact galaxy with mostly dark matter.

scholarly journals First Cosmology Results Using Type Ia Supernovae from the Dark Energy Survey: Photometric Pipeline and Light-curve Data Release

2019 ◽  
Vol 874 (1) ◽  
pp. 106 ◽  
Author(s):  
D. Brout ◽  
M. Sako ◽  
D. Scolnic ◽  
R. Kessler ◽  
C. B. D’Andrea ◽  
...  
Keyword(s):  
Dark Energy ◽  
Light Curve ◽  
Type Ia Supernovae ◽  
Dark Energy Survey ◽  
Data Release ◽  
Type Ia ◽  
Ia Supernovae ◽  
Energy Survey
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