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Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method

Fuente: arXiv
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Hauptverfasser: Campos, A., Yin, B., Dodelson, S., Amon, A., Alarcon, A., Sánchez, C., Bernstein, G. M., Giannini, G., Myles, J., Samuroff, S., Alves, O., Andrade-Oliveira, F., Bechtol, K., Becker, M. R., Blazek, J., Camacho, H., Rosell, A. Carnero, Kind, M. Carrasco, Cawthon, R., Chang, C., Chen, R., Choi, A., Cordero, J., Davis, C., DeRose, J., Diehl, H. T., Doux, C., Drlica-Wagner, A., Eckert, K., Eifler, T. F., Elvin-Poole, J., Everett, S., Fang, X., Ferté, A., Friedrich, O., Gatti, M., Gruen, D., Gruendl, R. A., Harrison, I., Hartley, W. G., Herner, K., Huang, H., Huff, E. M., Jarvis, M., Krause, E., Kuropatkin, N., Leget, P. -F., MacCrann, N., McCullough, J., Navarro-Alsina, A., Pandey, S., Prat, J., Raveri, M., Rollins, R. P., Roodman, A., Rosenfeld, R., Ross, A. J., Rykoff, E. S., Sanchez, J., Secco, L. F., Sevilla-Noarbe, I., Sheldon, E., Shin, T., Troxel, M. A., Tutusaus, I., Varga, T. N., Wechsler, R. H., Yanny, B., Zhang, Y., Zuntz, J., Aguena, M., Annis, J., Bacon, D., Bocquet, S., Brooks, D., Burke, D. L., Carretero, J., Castander, F. J., Costanzi, M., da Costa, L. N., De Vicente, J., Doel, P., Ferrero, I., Flaugher, B., Frieman, J., García-Bellido, J., Gaztanaga, E., Gutierrez, G., Hinton, S. R., Hollowood, D. L., Honscheid, K., James, D. J., Kuehn, K., Lima, M., Lin, H., Marshall, J. L., Mena-Fernández, J., Menanteau, F., Miquel, R., Ogando, R. L. C., Paterno, M., Pereira, M. E. S., Pieres, A., Malagón, A. A. Plazas, Porredon, A., Sanchez, E., Cid, D. Sanchez, Smith, M., Suchyta, E., Swanson, M. E. C., Tarle, G., To, C., Vikram, V., Weaverdyck, N.
Format: Preprint
Veröffentlicht: 2024
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Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
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author Campos, A.
Yin, B.
Dodelson, S.
Amon, A.
Alarcon, A.
Sánchez, C.
Bernstein, G. M.
Giannini, G.
Myles, J.
Samuroff, S.
Alves, O.
Andrade-Oliveira, F.
Bechtol, K.
Becker, M. R.
Blazek, J.
Camacho, H.
Rosell, A. Carnero
Kind, M. Carrasco
Cawthon, R.
Chang, C.
Chen, R.
Choi, A.
Cordero, J.
Davis, C.
DeRose, J.
Diehl, H. T.
Doux, C.
Drlica-Wagner, A.
Eckert, K.
Eifler, T. F.
Elvin-Poole, J.
Everett, S.
Fang, X.
Ferté, A.
Friedrich, O.
Gatti, M.
Gruen, D.
Gruendl, R. A.
Harrison, I.
Hartley, W. G.
Herner, K.
Huang, H.
Huff, E. M.
Jarvis, M.
Krause, E.
Kuropatkin, N.
Leget, P. -F.
MacCrann, N.
McCullough, J.
Navarro-Alsina, A.
Pandey, S.
Prat, J.
Raveri, M.
Rollins, R. P.
Roodman, A.
Rosenfeld, R.
Ross, A. J.
Rykoff, E. S.
Sanchez, J.
Secco, L. F.
Sevilla-Noarbe, I.
Sheldon, E.
Shin, T.
Troxel, M. A.
Tutusaus, I.
Varga, T. N.
Wechsler, R. H.
Yanny, B.
Zhang, Y.
Zuntz, J.
Aguena, M.
Annis, J.
Bacon, D.
Bocquet, S.
Brooks, D.
Burke, D. L.
Carretero, J.
Castander, F. J.
Costanzi, M.
da Costa, L. N.
De Vicente, J.
Doel, P.
Ferrero, I.
Flaugher, B.
Frieman, J.
García-Bellido, J.
Gaztanaga, E.
Gutierrez, G.
Hinton, S. R.
Hollowood, D. L.
Honscheid, K.
James, D. J.
Kuehn, K.
Lima, M.
Lin, H.
Marshall, J. L.
Mena-Fernández, J.
Menanteau, F.
Miquel, R.
Ogando, R. L. C.
Paterno, M.
Pereira, M. E. S.
Pieres, A.
Malagón, A. A. Plazas
Porredon, A.
Sanchez, E.
Cid, D. Sanchez
Smith, M.
Suchyta, E.
Swanson, M. E. C.
Tarle, G.
To, C.
Vikram, V.
Weaverdyck, N.
author_facet Campos, A.
Yin, B.
Dodelson, S.
Amon, A.
Alarcon, A.
Sánchez, C.
Bernstein, G. M.
Giannini, G.
Myles, J.
Samuroff, S.
Alves, O.
Andrade-Oliveira, F.
Bechtol, K.
Becker, M. R.
Blazek, J.
Camacho, H.
Rosell, A. Carnero
Kind, M. Carrasco
Cawthon, R.
Chang, C.
Chen, R.
Choi, A.
Cordero, J.
Davis, C.
DeRose, J.
Diehl, H. T.
Doux, C.
Drlica-Wagner, A.
Eckert, K.
Eifler, T. F.
Elvin-Poole, J.
Everett, S.
Fang, X.
Ferté, A.
Friedrich, O.
Gatti, M.
Gruen, D.
Gruendl, R. A.
Harrison, I.
Hartley, W. G.
Herner, K.
Huang, H.
Huff, E. M.
Jarvis, M.
Krause, E.
Kuropatkin, N.
Leget, P. -F.
MacCrann, N.
McCullough, J.
Navarro-Alsina, A.
Pandey, S.
Prat, J.
Raveri, M.
Rollins, R. P.
Roodman, A.
Rosenfeld, R.
Ross, A. J.
Rykoff, E. S.
Sanchez, J.
Secco, L. F.
Sevilla-Noarbe, I.
Sheldon, E.
Shin, T.
Troxel, M. A.
Tutusaus, I.
Varga, T. N.
Wechsler, R. H.
Yanny, B.
Zhang, Y.
Zuntz, J.
Aguena, M.
Annis, J.
Bacon, D.
Bocquet, S.
Brooks, D.
Burke, D. L.
Carretero, J.
Castander, F. J.
Costanzi, M.
da Costa, L. N.
De Vicente, J.
Doel, P.
Ferrero, I.
Flaugher, B.
Frieman, J.
García-Bellido, J.
Gaztanaga, E.
Gutierrez, G.
Hinton, S. R.
Hollowood, D. L.
Honscheid, K.
James, D. J.
Kuehn, K.
Lima, M.
Lin, H.
Marshall, J. L.
Mena-Fernández, J.
Menanteau, F.
Miquel, R.
Ogando, R. L. C.
Paterno, M.
Pereira, M. E. S.
Pieres, A.
Malagón, A. A. Plazas
Porredon, A.
Sanchez, E.
Cid, D. Sanchez
Smith, M.
Suchyta, E.
Swanson, M. E. C.
Tarle, G.
To, C.
Vikram, V.
Weaverdyck, N.
contents Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.
format Preprint
id arxiv_https___arxiv_org_abs_2408_00922
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method
Campos, A.
Yin, B.
Dodelson, S.
Amon, A.
Alarcon, A.
Sánchez, C.
Bernstein, G. M.
Giannini, G.
Myles, J.
Samuroff, S.
Alves, O.
Andrade-Oliveira, F.
Bechtol, K.
Becker, M. R.
Blazek, J.
Camacho, H.
Rosell, A. Carnero
Kind, M. Carrasco
Cawthon, R.
Chang, C.
Chen, R.
Choi, A.
Cordero, J.
Davis, C.
DeRose, J.
Diehl, H. T.
Doux, C.
Drlica-Wagner, A.
Eckert, K.
Eifler, T. F.
Elvin-Poole, J.
Everett, S.
Fang, X.
Ferté, A.
Friedrich, O.
Gatti, M.
Gruen, D.
Gruendl, R. A.
Harrison, I.
Hartley, W. G.
Herner, K.
Huang, H.
Huff, E. M.
Jarvis, M.
Krause, E.
Kuropatkin, N.
Leget, P. -F.
MacCrann, N.
McCullough, J.
Navarro-Alsina, A.
Pandey, S.
Prat, J.
Raveri, M.
Rollins, R. P.
Roodman, A.
Rosenfeld, R.
Ross, A. J.
Rykoff, E. S.
Sanchez, J.
Secco, L. F.
Sevilla-Noarbe, I.
Sheldon, E.
Shin, T.
Troxel, M. A.
Tutusaus, I.
Varga, T. N.
Wechsler, R. H.
Yanny, B.
Zhang, Y.
Zuntz, J.
Aguena, M.
Annis, J.
Bacon, D.
Bocquet, S.
Brooks, D.
Burke, D. L.
Carretero, J.
Castander, F. J.
Costanzi, M.
da Costa, L. N.
De Vicente, J.
Doel, P.
Ferrero, I.
Flaugher, B.
Frieman, J.
García-Bellido, J.
Gaztanaga, E.
Gutierrez, G.
Hinton, S. R.
Hollowood, D. L.
Honscheid, K.
James, D. J.
Kuehn, K.
Lima, M.
Lin, H.
Marshall, J. L.
Mena-Fernández, J.
Menanteau, F.
Miquel, R.
Ogando, R. L. C.
Paterno, M.
Pereira, M. E. S.
Pieres, A.
Malagón, A. A. Plazas
Porredon, A.
Sanchez, E.
Cid, D. Sanchez
Smith, M.
Suchyta, E.
Swanson, M. E. C.
Tarle, G.
To, C.
Vikram, V.
Weaverdyck, N.
Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.
title Enhancing weak lensing redshift distribution characterization by optimizing the Dark Energy Survey Self-Organizing Map Photo-z method
topic Cosmology and Nongalactic Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2408.00922

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