scholarly journals Galaxy formation and evolution with the Dark Energy Survey

2012 ◽  
Vol 8 (S295) ◽  
pp. 137-140
Author(s):  
Diego Capozzi ◽  
Daniel Thomas ◽  
Claudia Maraston ◽  
Luke J. M. Davies
Keyword(s):  
Dark Energy ◽  
Galaxy Evolution ◽  
Galaxy Formation ◽  
Large Scale ◽  
Time Range ◽  
Data Set ◽  
Dark Energy Survey ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Energy Survey

AbstractThe Dark Energy Survey (DES) will be the new state-of the-art in large-scale galaxy imaging surveys. With 5,000 deg2, it will cover an area of the sky similar to SDSS-II, but will go over two magnitudes deeper, reaching 24th magnitude in all four optical bands (griz). DES will further provide observations in the redder Y-band and will be complemented with VISTA observations in the near-infrared bands JHK. Hence DES will furnish an unprecedented combination of sky and wavelength coverage and depth, unreached by any of the existing galaxy surveys. The very nature of the DES data set – large volume at intermediate photometric depth – allows us to probe galaxy formation and evolution within a cosmic-time range of ~ 10 Gyr and in different environments. In fact there will be many galaxy clusters available for galaxy evolution studies, given that one of the main aims of DES is to use their abundance to constrain the equation of state of dark energy. The X-ray follow up of these clusters, coupled with the use of gravitational lensing, will provide very precise measures of their masses, enabling us to study in detail the influence of the environment on galaxy formation and evolution processes. DES will leverage the study of these processes by allowing us to perform a detailed investigation of the galaxy luminosity and stellar mass functions and of the relationship between dark and baryonic matter as described by the Halo Occupation Distribution.

scholarly journals Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

2021 ◽  
Vol 503 (2) ◽  
pp. 2688-2705
Author(s):  
C Doux ◽  
E Baxter ◽  
P Lemos ◽  
C Chang ◽  
A Alarcon ◽  
...  
Keyword(s):  
Dark Energy ◽  
Internal Consistency ◽  
Goodness Of Fit ◽  
Small Scale ◽  
P Value ◽  
Posterior Predictive Distribution ◽  
Data Set ◽  
Dark Energy Survey ◽  
Data Vector ◽  
Energy Survey

ABSTRACT Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. We present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

scholarly journals C iv black hole mass measurements with the Australian Dark Energy Survey (OzDES)

2019 ◽  
Vol 487 (3) ◽  
pp. 3650-3663 ◽  
Author(s):  
J K Hoormann ◽  
P Martini ◽  
T M Davis ◽  
A King ◽  
C Lidman ◽  
...  
Keyword(s):  
Black Holes ◽  
Black Hole ◽  
Dark Energy ◽  
Emission Line ◽  
Galaxy Evolution ◽  
Supermassive Black Holes ◽  
Black Hole Mass ◽  
Mass Measurements ◽  
Dark Energy Survey ◽  
Energy Survey

ABSTRACT Black hole mass measurements outside the local Universe are critically important to derive the growth of supermassive black holes over cosmic time, and to study the interplay between black hole growth and galaxy evolution. In this paper, we present two measurements of supermassive black hole masses from reverberation mapping (RM) of the broad C iv emission line. These measurements are based on multiyear photometry and spectroscopy from the Dark Energy Survey Supernova Program (DES-SN) and the Australian Dark Energy Survey (OzDES), which together constitute the OzDES RM Program. The observed reverberation lag between the DES continuum photometry and the OzDES emission line fluxes is measured to be $358^{+126}_{-123}$ and $343^{+58}_{-84}$ d for two quasars at redshifts of 1.905 and 2.593, respectively. The corresponding masses of the two supermassive black holes are 4.4 × 109 and 3.3 × 109 M⊙, which are among the highest redshift and highest mass black holes measured to date with RM studies. We use these new measurements to better determine the C iv radius−luminosity relationship for high-luminosity quasars, which is fundamental to many quasar black hole mass estimates and demographic studies.

scholarly journals Deep learning for intensity mapping observations: component extraction

2020 ◽  
Vol 496 (1) ◽  
pp. L54-L58 ◽  
Author(s):  
Kana Moriwaki ◽  
Nina Filippova ◽  
Masato Shirasaki ◽  
Naoki Yoshida
Keyword(s):  
Deep Learning ◽  
Galaxy Formation ◽  
Large Scale ◽  
Generative Adversarial Networks ◽  
Intensity Mapping ◽  
Adversarial Networks ◽  
Galaxy Formation And Evolution ◽  
Formation And Evolution ◽  
Emission Line Galaxies ◽  
Two Populations

ABSTRACT Line intensity mapping (LIM) is an emerging observational method to study the large-scale structure of the Universe and its evolution. LIM does not resolve individual sources but probes the fluctuations of integrated line emissions. A serious limitation with LIM is that contributions of different emission lines from sources at different redshifts are all confused at an observed wavelength. We propose a deep learning application to solve this problem. We use conditional generative adversarial networks to extract designated information from LIM. We consider a simple case with two populations of emission-line galaxies; H $\rm \alpha$ emitting galaxies at $z$ = 1.3 are confused with [O iii] emitters at $z$ = 2.0 in a single observed waveband at 1.5 $\mu{\textrm m}$. Our networks trained with 30 000 mock observation maps are able to extract the total intensity and the spatial distribution of H $\rm \alpha$ emitting galaxies at $z$ = 1.3. The intensity peaks are successfully located with 74 per cent precision. The precision increases to 91 per cent when we combine five networks. The mean intensity and the power spectrum are reconstructed with an accuracy of ∼10 per cent. The extracted galaxy distributions at a wider range of redshift can be used for studies on cosmology and on galaxy formation and evolution.

scholarly journals MaNGA: Mapping Nearby Galaxies at Apache Point Observatory

2014 ◽  
Vol 10 (S311) ◽  
pp. 100-103
Author(s):  
Kevin Bundy
Keyword(s):  
Galaxy Formation ◽  
Signal To Noise Ratio ◽  
Data Set ◽  
Chemical Enrichment ◽  
Early Results ◽  
Galaxy Formation And Evolution ◽  
Nearby Galaxies ◽  
Formation And Evolution ◽  
Large Telescopes ◽  
Star Formation Histories

AbstractI describe a new integral field spectroscopic survey called MaNGA (Mapping Nearby Galaxies at Apache Point Observatory). One of three core programs in the 6-year SDSS-IV project† that began on July 1st, 2014, MaNGA will deploy 17 fiber-bundle IFUs across the Sloan 2.5m Telescope's 3 degree field-of-view, targeting a mass-selected sample with a median redshift of 0.03, typical spatial resolution of 1-2 kpc, and a per-fiber signal-to-noise ratio of 4-8 in the outskirts of target galaxies. For each galaxy in the sample, MaNGA will provide maps and measured gradients of the composition and dynamics of both stars and gas. I discuss early results that highlight MaNGA's potential to shed light on the ionization and chemical enrichment of gas in galaxies, spatial patterns in their star formation histories, and the internal makeup of stellar populations. MaNGA's unprecedented data set will not only provide powerful new insight on galaxy formation and evolution but will serve as a valuable benchmark for future high-z observations from large telescopes and space-based facilities.

scholarly journals Ridges in the Dark Energy Survey for cosmic trough identification

2020 ◽  
Vol 500 (1) ◽  
pp. 859-870
Author(s):  
Ben Moews ◽  
Morgan A Schmitz ◽  
Andrew J Lawler ◽  
Joe Zuntz ◽  
Alex I Malz ◽  
...  
Keyword(s):  
Dark Energy ◽  
Large Scale ◽  
Mass Density ◽  
Mean Shift ◽  
Large Scale Structure ◽  
Wasserstein Distance ◽  
Scale Structure ◽  
Weak Lensing ◽  
Dark Energy Survey ◽  
Energy Survey

ABSTRACT Cosmic voids and their corresponding redshift-projected mass densities, known as troughs, play an important role in our attempt to model the large-scale structure of the Universe. Understanding these structures enables us to compare the standard model with alternative cosmologies, constrain the dark energy equation of state, and distinguish between different gravitational theories. In this paper, we extend the subspace-constrained mean shift algorithm, a recently introduced method to estimate density ridges, and apply it to 2D weak lensing mass density maps from the Dark Energy Survey Y1 data release to identify curvilinear filamentary structures. We compare the obtained ridges with previous approaches to extract trough structure in the same data, and apply curvelets as an alternative wavelet-based method to constrain densities. We then invoke the Wasserstein distance between noisy and noiseless simulations to validate the denoising capabilities of our method. Our results demonstrate the viability of ridge estimation as a precursor for denoising weak lensing observables to recover the large-scale structure, paving the way for a more versatile and effective search for troughs.

scholarly journals The WiggleZ Dark Energy Survey: probing the epoch of radiation domination using large-scale structure

2013 ◽  
Vol 429 (3) ◽  
pp. 1902-1912 ◽  
Author(s):  
Gregory B. Poole ◽  
Chris Blake ◽  
David Parkinson ◽  
Sarah Brough ◽  
Matthew Colless ◽  
...  
Keyword(s):  
Dark Energy ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Dark Energy Survey ◽  
Energy Survey

scholarly journals Dusty Starbursts within a z=3 Large Scale Structure revealed by ALMA

2015 ◽  
Vol 11 (S319) ◽  
pp. 109-109
Author(s):  
Hideki Umehata
Keyword(s):  
Galaxy Formation ◽  
Large Scale ◽  
Large Scale Structure ◽  
Scale Structure ◽  
Massive Black Hole ◽  
Rich Cluster ◽  
Galaxy Formation And Evolution ◽  
Submillimeter Galaxies ◽  
Formation And Evolution

AbstractThe role of the large-scale structure is one of the most important theme in studying galaxy formation and evolution. However, it has been still mystery especially at z>2. On the basis of our ALMA 1.1 mm observations in a z ~ 3 protocluster field, it is suggested that submillimeter galaxies (SMGs) preferentially reside in the densest environment at z ~ 3. Furthermore we find a rich cluster of AGN-host SMGs at the core of the protocluster, combining with Chandra X-ray data. Our results indicate the vigorous star-formation and accelerated super massive black hole (SMBH) growth in the node of the cosmic web.

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