Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data. Issue 4 (7th December 2015)
- Record Type:
- Journal Article
- Title:
- Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data. Issue 4 (7th December 2015)
- Main Title:
- Galaxy clustering, photometric redshifts and diagnosis of systematics in the DES Science Verification data
- Authors:
- Crocce, M.
Carretero, J.
Bauer, A. H.
Ross, A. J.
Sevilla-Noarbe, I.
Giannantonio, T.
Sobreira, F.
Sanchez, J.
Gaztanaga, E.
Kind, M. Carrasco
Sánchez, C.
Bonnett, C.
Benoit-Lévy, A.
Brunner, R. J.
Rosell, A. Carnero
Cawthon, R.
Fosalba, P.
Hartley, W.
Kim, E. J.
Leistedt, B.
Miquel, R.
Peiris, H. V.
Percival, W. J.
Rosenfeld, R.
Rykoff, E. S.
Sánchez, E.
Abbott, T.
Abdalla, F. B.
Allam, S.
Banerji, M.
Bernstein, G. M.
Bertin, E.
Brooks, D.
Buckley-Geer, E.
Burke, D. L.
Capozzi, D.
Castander, F. J.
Cunha, C. E.
D'Andrea, C. B.
da Costa, L. N.
Desai, S.
Diehl, H. T.
Eifler, T. F.
Evrard, A. E.
Neto, A. Fausti
Fernandez, E.
Finley, D. A.
Flaugher, B.
Frieman, J.
Gerdes, D. W.
Gruen, D.
Gruendl, R. A.
Gutierrez, G.
Honscheid, K.
James, D. J.
Kuehn, K.
Kuropatkin, N.
Lahav, O.
Li, T. S.
Lima, M.
Maia, M. A. G.
March, M.
Marshall, J. L.
Martini, P.
Melchior, P.
Miller, C. J.
Neilsen, E.
Nichol, R. C.
Nord, B.
Ogando, R.
Plazas, A. A.
Romer, A. K.
Sako, M.
Santiago, B.
Schubnell, M.
Smith, R. C.
Soares-Santos, M.
Suchyta, E.
Swanson, M. E. C.
Tarle, G.
Thaler, J.
Thomas, D.
Vikram, V.
Walker, A. R.
Wechsler, R. H.
Weller, J.
Zuntz, J.
… (more) - Abstract:
- 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 × 10 6 galaxies over a contiguous 116 deg 2 region in five bins of photometric redshift width Δ z = 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- z algorithm (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 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 χ 2 of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. 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 per cent accuracy down to scales at least 4–10 times smallerAbstract: 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 × 10 6 galaxies over a contiguous 116 deg 2 region in five bins of photometric redshift width Δ z = 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- z algorithm (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 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 χ 2 of 4.0 (8.7) with 5 degrees of freedom for the TPZ (BPZ) redshifts. 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 per cent accuracy down to scales at least 4–10 times smaller than those on which linear theory is expected to be sufficient. … (more)
- Is Part Of:
- Monthly notices of the Royal Astronomical Society. Volume 455:Issue 4(2016)
- Journal:
- Monthly notices of the Royal Astronomical Society
- Issue:
- Volume 455:Issue 4(2016)
- Issue Display:
- Volume 455, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 455
- Issue:
- 4
- Issue Sort Value:
- 2016-0455-0004-0000
- Page Start:
- 4301
- Page End:
- 4324
- Publication Date:
- 2015-12-07
- Subjects:
- surveys -- cosmology: observations -- large-scale structure of Universe
Astronomy -- Periodicals
Periodicals
520.5 - Journal URLs:
- http://mnras.oxfordjournals.org/ ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2966 ↗
http://www.blackwell-synergy.com/issuelist.asp?journal=mnr ↗
http://www.blackwell-synergy.com/loi/mnr ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/mnras/stv2590 ↗
- Languages:
- English
- ISSNs:
- 0035-8711
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5943.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24976.xml