Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data
Abstract
We study the clustering of galaxies detected at i < 22.5 in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using 2.3 × 106 galaxies over a contiguous 116 deg2 region in five bins of photometric redshift width Δz = 0.2 in the range 0.2 < z < 1.2. The impact of photometric redshift errors is assessed by comparing results using a template-based photo-zalgorithm (BPZ) to a machine-learning algorithm (TPZ). A companion paper presents maps of several observational variables (e.g. seeing, sky brightness) which could modulate the galaxy density. Here we characterize and mitigate systematic errors on the measured clustering which arise from these observational variables, in addition to others such as Galactic dust and stellar contamination. After correcting for systematic effects, we then measure galaxy bias over a broad range of linear scales relative to mass clustering predicted from the Planck Λ cold dark matter model, finding agreement with the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) measurements with χ2 of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. Furthermore, we test a ‘linear bias’ model, in which the galaxy clustering is a fixed multiple of the predicted non-linear darkmore »
- Authors:
-
- Institut de Ciencies de l'Espai, Barcelona (Spain). et al.
- Publication Date:
- Research Org.:
- Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Contributing Org.:
- DES Collaboration
- OSTI Identifier:
- 1223231
- Report Number(s):
- FERMILAB-PUB-15-305
Journal ID: ISSN 1365-2966; arXiv eprint number arXiv:1507.05360
- Grant/Contract Number:
- AC02-07CH11359
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Monthly Notices of the Royal Astronomical Society (Online)
- Additional Journal Information:
- Journal Name: Monthly Notices of the Royal Astronomical Society (Online); Journal Volume: 455; Journal Issue: 4; Journal ID: ISSN 1365-2966
- Publisher:
- Royal Astronomical Society
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTRONOMY AND ASTROPHYSICS; surveys; cosmology: observations; large-scale structure of Universe
Citation Formats
Crocce, M. Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data. United States: N. p., 2015.
Web. doi:10.1093/mnras/stv2590.
Crocce, M. Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data. United States. https://doi.org/10.1093/mnras/stv2590
Crocce, M. Wed .
"Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data". United States. https://doi.org/10.1093/mnras/stv2590. https://www.osti.gov/servlets/purl/1223231.
@article{osti_1223231,
title = {Galaxy Clustering, Photometric Redshifts and Diagnosis of Systematics in the DES Science Verification Data},
author = {Crocce, M.},
abstractNote = {We study the clustering of galaxies detected at i < 22.5 in the Science Verification observations of the Dark Energy Survey (DES). Two-point correlation functions are measured using 2.3 × 106 galaxies over a contiguous 116 deg2 region in five bins of photometric redshift width Δz = 0.2 in the range 0.2 < z < 1.2. The impact of photometric redshift errors is assessed by comparing results using a template-based photo-zalgorithm (BPZ) to a machine-learning algorithm (TPZ). A companion paper presents maps of several observational variables (e.g. seeing, sky brightness) which could modulate the galaxy density. Here we characterize and mitigate systematic errors on the measured clustering which arise from these observational variables, in addition to others such as Galactic dust and stellar contamination. After correcting for systematic effects, we then measure galaxy bias over a broad range of linear scales relative to mass clustering predicted from the Planck Λ cold dark matter model, finding agreement with the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) measurements with χ2 of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. Furthermore, we test a ‘linear bias’ model, in which the galaxy clustering is a fixed multiple of the predicted non-linear dark matter clustering. The precision of the data allows us to determine that the linear bias model describes the observed galaxy clustering to 2.5 percent accuracy down to scales at least 4–10 times smaller than those on which linear theory is expected to be sufficient.},
doi = {10.1093/mnras/stv2590},
journal = {Monthly Notices of the Royal Astronomical Society (Online)},
number = 4,
volume = 455,
place = {United States},
year = {Wed Dec 09 00:00:00 EST 2015},
month = {Wed Dec 09 00:00:00 EST 2015}
}
Web of Science
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CMB lensing tomography with the DES Science Verification galaxies
text, January 2015
- Giannantonio, T.; Fosalba, P.; Cawthon, R.
- arXiv
The Dark Energy Survey: more than dark energy - an overview
text, January 2016
- Collaboration, Dark Energy Survey; Abbott, T.; Abdalla, F. B.
- arXiv
Large-scale retrospective relative spectro-photometric self-calibration in space
text, January 2016
- Markovic, Katarina; Percival, Will J.; Scodeggio, Marco
- arXiv
Reconstruction of interaction rate in Holographic dark energy
text, January 2016
- Mukherjee, Ankan
- arXiv
KiDS+GAMA: Cosmology constraints from a joint analysis of cosmic shear, galaxy-galaxy lensing and angular clustering
text, January 2017
- van Uitert, Edo; Joachimi, Benjamin; Joudaki, Shahab
- arXiv
Dark Energy Survey Year 1 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
text, January 2017
- Collaboration, Des; Abbott, T. M. C.; Abdalla, F. B.
- arXiv
Dark Energy Survey Year 1 Results: Galaxy-Galaxy Lensing
text, January 2017
- Prat, J.; Sánchez, C.; Fang, Y.
- arXiv
Density split statistics: Cosmological constraints from counts and lensing in cells in DES Y1 and SDSS data
text, January 2017
- Gruen, D.; Friedrich, O.; Krause, E.
- arXiv
Hierarchical modeling and statistical calibration for photometric redshifts
text, January 2018
- Leistedt, Boris; Hogg, David W.; Wechsler, Risa H.
- arXiv
Measuring Linear and Non-linear Galaxy Bias Using Counts-in-Cells in the Dark Energy Survey Science Verification Data
text, January 2018
- Salvador, A. I.; Sánchez, F. J.; Pagul, A.
- arXiv
Producing a BOSS-CMASS sample with DES imaging
text, January 2019
- Lee, S.; Huff, E. M.; Ross, A. J.
- arXiv
Dark sectors with dynamical coupling
text, January 2019
- Yang, Weiqiang; Mena, Olga; Pan, Supriya
- arXiv
A new estimator for gravitational lensing using galaxy and intensity mapping surveys
text, January 2019
- Jalilvand, Mona; Majerotto, Elisabetta; Bonvin, Camille
- arXiv
Optimizing galaxy samples for clustering measurements in photometric surveys
text, January 2019
- Tanoglidis, Dimitrios; Chang, Chihway; Frieman, Joshua
- arXiv
A new sample of southern radio galaxies: Host galaxy masses and star-formation rates
text, January 2019
- Marubini, Takalani; Jarvis, Matt J.; Fine, Stephen
- arXiv
Weak lensing deflection of three-point correlation functions
text, January 2017
- Pyne, Susan; Joachimi, Benjamin; Peiris, Hiranya V.
- arXiv