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Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization

Author(s): Gatti, M; Vielzeuf, P; Davis, C; Cawthon, R; Rau, MM; et al

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dc.contributor.authorGatti, M-
dc.contributor.authorVielzeuf, P-
dc.contributor.authorDavis, C-
dc.contributor.authorCawthon, R-
dc.contributor.authorRau, MM-
dc.contributor.authorDeRose, J-
dc.contributor.authorDe Vicente, J-
dc.contributor.authorAlarcon, A-
dc.contributor.authorRozo, E-
dc.contributor.authorGaztanaga, E-
dc.contributor.authorHoyle, B-
dc.contributor.authorMiquel, R-
dc.contributor.authorBernstein, GM-
dc.contributor.authorBonnett, C-
dc.contributor.authorRosell, A Carnero-
dc.contributor.authorCastander, FJ-
dc.contributor.authorChang, C-
dc.contributor.authorda Costa, LN-
dc.contributor.authorGruen, D-
dc.contributor.authorGschwend, J-
dc.contributor.authorHartley, WG-
dc.contributor.authorLin, H-
dc.contributor.authorMacCrann, N-
dc.contributor.authorMaia, MAG-
dc.contributor.authorOgando, RLC-
dc.contributor.authorRoodman, A-
dc.contributor.authorSevilla-Noarbe, I-
dc.contributor.authorTroxel, MA-
dc.contributor.authorWechsler, RH-
dc.contributor.authorAsorey, J-
dc.contributor.authorDavis, TM-
dc.contributor.authorGlazebrook, K-
dc.contributor.authorHinton, SR-
dc.contributor.authorLewis, G-
dc.contributor.authorLidman, C-
dc.contributor.authorMacaulay, E-
dc.contributor.authorMoeller, A-
dc.contributor.authorO Neill, CR-
dc.contributor.authorSommer, NE-
dc.contributor.authorUddin, SA-
dc.contributor.authorYuan, F-
dc.contributor.authorZhang, B-
dc.contributor.authorAbbott, TMC-
dc.contributor.authorAllam, S-
dc.contributor.authorAnnis, J-
dc.contributor.authorBechtol, K-
dc.contributor.authorBrooks, D-
dc.contributor.authorBurke, DL-
dc.contributor.authorCarollo, D-
dc.contributor.authorKind, M Carrasco-
dc.contributor.authorCarretero, J-
dc.contributor.authorCunha, CE-
dc.contributor.authorD Andrea, CB-
dc.contributor.authorDepoy, DL-
dc.contributor.authorDesai, S-
dc.contributor.authorEifler, TF-
dc.contributor.authorEvrard, AE-
dc.contributor.authorFlaugher, B-
dc.contributor.authorFosalba, P-
dc.contributor.authorFrieman, J-
dc.contributor.authorGarcia-Bellido, J-
dc.contributor.authorGerdes, DW-
dc.contributor.authorGoldstein, DA-
dc.contributor.authorGruendl, RA-
dc.contributor.authorGutierrez, G-
dc.contributor.authorHonscheid, K-
dc.contributor.authorHoormann, JK-
dc.contributor.authorJain, B-
dc.contributor.authorJames, DJ-
dc.contributor.authorJarvis, M-
dc.contributor.authorJeltema, T-
dc.contributor.authorJohnson, MWG-
dc.contributor.authorJohnson, MD-
dc.contributor.authorKrause, E-
dc.contributor.authorKuehn, K-
dc.contributor.authorKuhlmann, S-
dc.contributor.authorKuropatkin, N-
dc.contributor.authorLi, TS-
dc.contributor.authorLima, M-
dc.contributor.authorMarshall, JL-
dc.contributor.authorMelchior, Peter M-
dc.contributor.authorMenanteau, F-
dc.contributor.authorNichol, RC-
dc.contributor.authorNord, B-
dc.contributor.authorPlazas, AA-
dc.contributor.authorReil, K-
dc.contributor.authorRykoff, ES-
dc.contributor.authorSako, M-
dc.contributor.authorSanchez, E-
dc.contributor.authorScarpine, V-
dc.contributor.authorSchubnell, M-
dc.contributor.authorSheldon, E-
dc.contributor.authorSmith, M-
dc.contributor.authorSmith, RC-
dc.contributor.authorSoares-Santos, M-
dc.contributor.authorSobreira, F-
dc.contributor.authorSuchyta, E-
dc.contributor.authorSwanson, MEC-
dc.contributor.authorTarle, G-
dc.contributor.authorThomas, D-
dc.contributor.authorTucker, BE-
dc.contributor.authorTucker, DL-
dc.contributor.authorVikram, V-
dc.contributor.authorWalker, AR-
dc.contributor.authorWeller, J-
dc.contributor.authorWester, W-
dc.contributor.authorWolf, RC-
dc.date.accessioned2022-01-25T15:01:37Z-
dc.date.available2022-01-25T15:01:37Z-
dc.date.issued2018-06en_US
dc.identifier.citationGatti, M, Vielzeuf, P, Davis, C, Cawthon, R, Rau, MM, DeRose, J, De Vicente, J, Alarcon, A, Rozo, E, Gaztanaga, E, Hoyle, B, Miquel, R, Bernstein, GM, Bonnett, C, Rosell, A Carnero, Castander, FJ, Chang, C, da Costa, LN, Gruen, D, Gschwend, J, Hartley, WG, Lin, H, MacCrann, N, Maia, MAG, Ogando, RLC, Roodman, A, Sevilla-Noarbe, I, Troxel, MA, Wechsler, RH, Asorey, J, Davis, TM, Glazebrook, K, Hinton, SR, Lewis, G, Lidman, C, Macaulay, E, Moeller, A, O Neill, CR, Sommer, NE, Uddin, SA, Yuan, F, Zhang, B, Abbott, TMC, Allam, S, Annis, J, Bechtol, K, Brooks, D, Burke, DL, Carollo, D, Kind, M Carrasco, Carretero, J, Cunha, CE, D Andrea, CB, Depoy, DL, Desai, S, Eifler, TF, Evrard, AE, Flaugher, B, Fosalba, P, Frieman, J, Garcia-Bellido, J, Gerdes, DW, Goldstein, DA, Gruendl, RA, Gutierrez, G, Honscheid, K, Hoormann, JK, Jain, B, James, DJ, Jarvis, M, Jeltema, T, Johnson, MWG, Johnson, MD, Krause, E, Kuehn, K, Kuhlmann, S, Kuropatkin, N, Li, TS, Lima, M, Marshall, JL, Melchior, P, Menanteau, F, Nichol, RC, Nord, B, Plazas, AA, Reil, K, Rykoff, ES, Sako, M, Sanchez, E, Scarpine, V, Schubnell, M, Sheldon, E, Smith, M, Smith, RC, Soares-Santos, M, Sobreira, F, Suchyta, E, Swanson, MEC, Tarle, G, Thomas, D, Tucker, BE, Tucker, DL, Vikram, V, Walker, AR, Weller, J, Wester, W, Wolf, RC. (2018). Dark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterization. MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, 477 (1651 - 1669. doi:10.1093/mnras/sty466en_US
dc.identifier.issn0035-8711-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr16m33357-
dc.description.abstractWe 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.en_US
dc.format.extent1664 - 1682en_US
dc.language.isoen_USen_US
dc.relationhttps://ui.adsabs.harvard.edu/abs/2018MNRAS.477.1664G/abstracten_US
dc.relation.ispartofMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETYen_US
dc.rightsFinal published version. Article is made available in OAR by the publisher's permission or policy.en_US
dc.titleDark Energy Survey Year 1 results: cross-correlation redshifts - methods and systematics characterizationen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1093/mnras/sty466-
dc.date.eissued2018-02-22en_US
dc.identifier.eissn1365-2966-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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