Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization
Gatti, M.1; Vielzeuf, P.1; Davis, C.2; Cawthon, R.3; Rau, M. M.4; DeRose, J.2,5; De Vicente, J.6; Alarcon, A.7; Rozo, E.8; Gaztanaga, E.7; Hoyle, B.4; Miquel, R.1,9; Bernstein, G. M.10; Bonnett, C.1; Rosell, A. Carnero11,12; Castander, F. J.14,15; Chang, C.16; da Costa, L. N.17,18; Gruen, D.11,12; Gschwend, J.11,12; Hartley, W. G.14,15; Lin, H.16; MacCrann, N.17,18; Maia, M. A. G.11,12; Ogando, R. L. C.11,12; Roodman, A.2,13; Sevilla-Noarbe, I.6; Troxel, M. A.17,18; Wechsler, R. H.2,5,13; Asorey, J.19,20; Davis, T. M.19,20; Glazebrook, K.21; Hinton, S. R.20; Lewis, G.19,22; Lidman, C.19,23; Macaulay, E.20; Moeller, A.19,24; O'Neill, C. R.19; Sommer, N. E.19,24; Uddin, S. A.19,25; Yuan, F.19,24; Zhang, B.19,24; Abbott, T. M. C.26; Allam, S.16; Annis, J.16; Bechtol, K.27; Brooks, D.14; Burke, D. L.2,13; Carollo, D.19,28; Kind, M. Carrasco29,30; Carretero, J.1; Cunha, C. E.2; D'Andrea, C. B.10; Depoy, D. L.31,32; Desai, S.33; Eifler, T. F.34,35; Evrard, A. E.36,37; Flaugher, B.16; Fosalba, P.7; Frieman, J.3,16; Garcia-Bellido, J.38; Gerdes, D. W.36,37; Goldstein, D. A.39,40; Gruendl, R. A.29,30; Gutierrez, G.16; Honscheid, K.17,18; Hoormann, J. K.20; Jain, B.10; James, D. J.41; Jarvis, M.10; Jeltema, T.42; Johnson, M. W. G.28; Johnson, M. D.28; Krause, E.2; Kuehn, K.23; Kuhlmann, S.43; Kuropatkin, N.16; Li, T. S.16; Lima, M.11,44; Marshall, J. L.31,32; Melchior, P.45; Menanteau, F.28,29; Nichol, R. C.46; Nord, B.16; Plazas, A. A.35; Reil, K.13; Rykoff, E. S.2,13; Sako, M.; Sanchez, E.6; Scarpine, V.16; Schubnell, M.37; Sheldon, E.47; Smith, M.48; Smith, R. C.26; Soares-Santos, M.16; Sobreira, F.11,49; Suchyta, E.50; Swanson, M. E. C.30; Tarle, G.37; Thomas, D.46; Tucker, B. E.19,24; Tucker, D. L.16; Vikram, V.43; Walker, A. R.26; Weller, J.4,51,52; Wester, W.16; Wolf, R. C.

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing source galaxies from the Dark Energy Survey Year 1 sample with redMaGiC galaxies (luminous red galaxies with secure photometric redshifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We apply the method to two photo-z codes run in our simulated data: Bayesian Photometric Redshift and Directional Neighbourhood Fitting. We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering versus photo-zs. The systematic uncertainty in the mean redshift bias of the source galaxy sample is Delta z less than or similar to 0.02, though the precise value depends on the redshift bin under consideration. We discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

Keywordgalaxies: distances and redshifts cosmology: observations
Indexed BySCI
WOS Research AreaAstronomy & Astrophysics
WOS SubjectAstronomy & Astrophysics
WOS IDWOS:000434663200014
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Document Type期刊论文
Corresponding AuthorGatti, M.; Vielzeuf, P.
Affiliation1.Barcelona Inst Sci & Technol, IFAE, Campus UAB, E-08193 Bellaterra, Barcelona, Spain
2.Stanford Univ, Kavli Inst for Particle Astrophys & Cosmol, POB 2450, Stanford, CA 94305 USA
3.Univ Chicago, Kavli Inst Cosmol Phys, Chicago, IL 60637 USA
4.Ludwig Maximilians Univ Munchen, Univ Sternwarte, Fak Phys, Scheinerstr 1, D-81679 Munich, Germany
5.Stanford Univ, Dept Phys, 382 Via Pueblo Mall, Stanford, CA 94305 USA
6.Ctr Invest Energet Medioambientales & Tecnol CIEM, E-28040 Madrid, Spain
7.CSIC, IEEC, Inst Space Sci, Campus UAB,Carrer Can Magrans S-N, E-08193 Barcelona, Spain
8.Univ Arizona, Dept Phys, Tucson, AZ 85721 USA
9.Ist Cataluna Recerca & Estudis Avancats, E-08010 Barcelona, Spain
10.Univ Penn, Dept Phys & Astron, Philadelphia, PA 19104 USA
11.Lab Interinst e Astron LIneA, Rua Gal Jose Cristino 77, BR-20921400 Rio De Janeiro, RJ, Brazil
12.Obser Nacl, Rua Gal Jose Cristino 77, BR-20921400 Rio De Janeiro, RJ, Brazil
13.SLAC Natl Accelerator Lab, Menlo Pk, CA 94025 USA
14.UCL, Dept Phys & Astron, Gower Sheet, London WC1E 6B1, England
15.Swiss Fed Inst Technol, Dept Phys, Wolfgang Pauli Str 16, CH-8093 Zurich, Switzerland
16.Fermilab Natl Accelerator Lab, POB 500, Batavia, IL 60510 USA
17.Ohio State Univ, Ctr Cosmol & Astroparticle Phys, Columbus, OH 43210 USA
18.Ohio State Univ, Dept Phys, Columbus, OH 43210 USA
19.ARC Ctr Excellence All Sky Astrophys CAASTRO, Sydney, NSW, Australia
20.Univ Queensland, Sch Math & Phys, Brisbane, Qld 4072, Australia
21.Swinburne Univ Technol, Ctr Astrophys & Supercomp, Hawthorn, Vic 3122, Australia
22.Univ Sydney, Sch Phys A28, Sydney Inst Astron, Sydney, NSW 2006, Australia
23.Australian Astron Observ, N Ryde, NSW 2113, Australia
24.Australian Natl Univ, Res Sch Astron & Astrophys, Canberra, ACT 2601, Australia
25.Chinese Acad Sci, Purple Mt Observ, Nanjing 210008, Jiangsu, Peoples R China
26.Natl Opt Astron Observ, Cerro Tololo Interamer Observ, Casilla 603, La Serena, Chile
27.LSST, 933 North Cherry Ave, Tucson, AZ 85721 USA
28.Osserv Astron Torino, INAF, Via Osservatorio 20, I-10025 Pino Torinese, Italy
29.Univ Illinois, Dept Astron, 1002 W Green St, Urbana, IL 61801 USA
30.Natl Ctr Supercomp Applicat, 1205 West Clark St, Urbana, IL 61801 USA
31.Texas A&M Univ, George P & Cynthia Woods Mitchell Inst Fundamenta, College Stn, TX 77843 USA
32.Texas A&M Univ, Dept Phys & Astron, College Stn, TX 77843 USA
33.IIT Hyderabad, Dept Phys, Kandi 502285, Telangana, India
34.CALTECH, Dept Phys, Pasadena, CA 91125 USA
35.CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA
36.Univ Michigan, Dept Astron, Ann Arbor, MI 48109 USA
37.Univ Michigan, Dept Phys, Ann Arbor, MI 48109 USA
38.Univ Autonoma Madrid, CSIC, Inst Fis Teor, E-28049 Madrid, Spain
39.Univ Calif Berkeley, Dept Astron, 501 Campbell Hall, Berkeley, CA 94720 USA
40.Lawrence Berkeley Natl Lab, 1 Cyclotron Rd, Berkeley, CA 94720 USA
41.Univ Washington, Astron Dept, Box 351580, Seattle, WA 98195 USA
42.Santa Cruz Inst Particle Phys, Santa Cruz, CA 95064 USA
43.Argonne Natl Lab, 9700 South Cass Ave, Lemont, IL 60439 USA
44.Univ Sao Paulo, Inst Fis, Dept Fis Matemat, CP 66318, BR-05314970 Sao Paulo, SP, Brazil
45.Princeton Univ, Dept Astrophys Sci, Peyton Hall, Princeton, NJ 08544 USA
46.Univ Portsmouth, Inst Cosmol & Gravitat, Portsmouth PO1 3FX, Hants, England
47.Brookhaven Natl Lab, Bldg 510, Upton, NY 11973 USA
48.Univ Southampton, Sch Phys & Astron, Southampton SO17 1BJ, Hants, England
49.Univ Estadual Campinas, Inst Fis Gleb Wataghin, BR-13083859 Campinas, SP, Brazil
50.Oak Ridge Natl Lab, Comp Sci & Math Div, Oak Ridge, TN 37831 USA
51.Excellence Cluster Univ, Boltzmannstr 2, D-85748 Garching, Germany
52.Max Planck Inst Extraterr Phys, Giessenbachstr, D-85748 Garching, Germany
Recommended Citation
GB/T 7714
Gatti, M.,Vielzeuf, P.,Davis, C.,et al. Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization[J]. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,2018,477(2):1651-1669.
APA Gatti, M..,Vielzeuf, P..,Davis, C..,Cawthon, R..,Rau, M. M..,...&Wolf, R. C..(2018).Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization.MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY,477(2),1651-1669.
MLA Gatti, M.,et al."Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization".MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 477.2(2018):1651-1669.
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