DES science portal: Computing photometric redshifts
Abstract
We report that a significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo-zs) has been consolidated as the standard strategy to bypass the high production costs and incompleteness of spectroscopic redshift samples. Training-based photo-z methods require the preparation of a high-quality list of spectroscopic redshifts, which needs to be constantly updated. The photo-z training, validation, and estimation must be performed in a consistent and reproducible way in order to accomplish the scientific requirements. To meet this purpose, we developed an integrated web-based data interface that not only provides the framework to carry out the above steps in a systematic way, enabling the ease testing and comparison of different algorithms, but also addresses the processing requirements by parallelizing the calculation in a transparent way for the user. This framework called the Science Portal (hereafter Portal) was developed in the context the Dark Energy Survey (DES) to facilitate scientific analysis. In this paper, we show how the Portal can provide a reliable environment to access vast datasets, provide validation algorithms and metrics, even in the case of multiple photo-zs methods. It is possible to maintain the provenance between themore »
- Authors:
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- Publication Date:
- Research Org.:
- Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), High Energy Physics (HEP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
- Contributing Org.:
- DES; DES Collaboration
- OSTI Identifier:
- 1362048
- Alternate Identifier(s):
- OSTI ID: 1479703; OSTI ID: 1637158
- Report Number(s):
- arXiv:1708.05643; DES-2016-0175; FERMILAB-PUB-17-043
Journal ID: ISSN 2213-1337; 1654411
- Grant/Contract Number:
- AC02-07CH11359; AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Astronomy and Computing
- Additional Journal Information:
- Journal Volume: 25; Journal Issue: C; Journal ID: ISSN 2213-1337
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 79 ASTRONOMY AND ASTROPHYSICS; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; Astronomical databases: catalogs, surveys; Methods: data analysis; Galaxies: distances and redshifts, statistics
Citation Formats
Gschwend, J., Rossel, A. C., Ogando, R. L. C., Neto, A. F., Maia, M. A. G., da Costa, L. N., Lima, M., Pellegrini, P., Campisano, R., Singulani, C., Adean, C., Benoist, C., Aguena, M., Carrasco Kind, M., Davis, T. M., de Vicente, J., Hartley, W. G., Hoyle, B., Palmese, A., Sadeh, I., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Asorey, J., Brooks, D., Calcino, J., Carollo, D., Castander, F. J., D’Andrea, C. B., Desai, S., Evrard, A. E., Fosalba, P., Frieman, J., García-Bellido, J., Glazebrook, K., Gerdes, D. W., Gruendl, R. A., Gutierrez, G., Hinton, S., Hollowood, D. L., Honscheid, K., Hoormann, J. K., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lewis, G., Lidman, C., Lin, H., Macaulay, E., Marshall, J., Melchior, P., Miquel, R., Möller, A., Plazas, A. A., Sanchez, E., Santiago, B., Scarpine, V., Schindler, R. H., Sevilla-Noarbe, I., Smith, M., Sobreira, F., Sommer, N. E., Suchyta, E., Swanson, M. E. C., Tarle, G., Tucker, B. E., Tucker, D. L., Uddin, S., and Walker, A. R. DES science portal: Computing photometric redshifts. United States: N. p., 2018.
Web. doi:10.1016/j.ascom.2018.08.008.
Gschwend, J., Rossel, A. C., Ogando, R. L. C., Neto, A. F., Maia, M. A. G., da Costa, L. N., Lima, M., Pellegrini, P., Campisano, R., Singulani, C., Adean, C., Benoist, C., Aguena, M., Carrasco Kind, M., Davis, T. M., de Vicente, J., Hartley, W. G., Hoyle, B., Palmese, A., Sadeh, I., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Asorey, J., Brooks, D., Calcino, J., Carollo, D., Castander, F. J., D’Andrea, C. B., Desai, S., Evrard, A. E., Fosalba, P., Frieman, J., García-Bellido, J., Glazebrook, K., Gerdes, D. W., Gruendl, R. A., Gutierrez, G., Hinton, S., Hollowood, D. L., Honscheid, K., Hoormann, J. K., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lewis, G., Lidman, C., Lin, H., Macaulay, E., Marshall, J., Melchior, P., Miquel, R., Möller, A., Plazas, A. A., Sanchez, E., Santiago, B., Scarpine, V., Schindler, R. H., Sevilla-Noarbe, I., Smith, M., Sobreira, F., Sommer, N. E., Suchyta, E., Swanson, M. E. C., Tarle, G., Tucker, B. E., Tucker, D. L., Uddin, S., & Walker, A. R. DES science portal: Computing photometric redshifts. United States. https://doi.org/10.1016/j.ascom.2018.08.008
Gschwend, J., Rossel, A. C., Ogando, R. L. C., Neto, A. F., Maia, M. A. G., da Costa, L. N., Lima, M., Pellegrini, P., Campisano, R., Singulani, C., Adean, C., Benoist, C., Aguena, M., Carrasco Kind, M., Davis, T. M., de Vicente, J., Hartley, W. G., Hoyle, B., Palmese, A., Sadeh, I., Abbott, T. M. C., Abdalla, F. B., Allam, S., Annis, J., Asorey, J., Brooks, D., Calcino, J., Carollo, D., Castander, F. J., D’Andrea, C. B., Desai, S., Evrard, A. E., Fosalba, P., Frieman, J., García-Bellido, J., Glazebrook, K., Gerdes, D. W., Gruendl, R. A., Gutierrez, G., Hinton, S., Hollowood, D. L., Honscheid, K., Hoormann, J. K., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lewis, G., Lidman, C., Lin, H., Macaulay, E., Marshall, J., Melchior, P., Miquel, R., Möller, A., Plazas, A. A., Sanchez, E., Santiago, B., Scarpine, V., Schindler, R. H., Sevilla-Noarbe, I., Smith, M., Sobreira, F., Sommer, N. E., Suchyta, E., Swanson, M. E. C., Tarle, G., Tucker, B. E., Tucker, D. L., Uddin, S., and Walker, A. R. Mon .
"DES science portal: Computing photometric redshifts". United States. https://doi.org/10.1016/j.ascom.2018.08.008. https://www.osti.gov/servlets/purl/1362048.
@article{osti_1362048,
title = {DES science portal: Computing photometric redshifts},
author = {Gschwend, J. and Rossel, A. C. and Ogando, R. L. C. and Neto, A. F. and Maia, M. A. G. and da Costa, L. N. and Lima, M. and Pellegrini, P. and Campisano, R. and Singulani, C. and Adean, C. and Benoist, C. and Aguena, M. and Carrasco Kind, M. and Davis, T. M. and de Vicente, J. and Hartley, W. G. and Hoyle, B. and Palmese, A. and Sadeh, I. and Abbott, T. M. C. and Abdalla, F. B. and Allam, S. and Annis, J. and Asorey, J. and Brooks, D. and Calcino, J. and Carollo, D. and Castander, F. J. and D’Andrea, C. B. and Desai, S. and Evrard, A. E. and Fosalba, P. and Frieman, J. and García-Bellido, J. and Glazebrook, K. and Gerdes, D. W. and Gruendl, R. A. and Gutierrez, G. and Hinton, S. and Hollowood, D. L. and Honscheid, K. and Hoormann, J. K. and James, D. J. and Kuehn, K. and Kuropatkin, N. and Lahav, O. and Lewis, G. and Lidman, C. and Lin, H. and Macaulay, E. and Marshall, J. and Melchior, P. and Miquel, R. and Möller, A. and Plazas, A. A. and Sanchez, E. and Santiago, B. and Scarpine, V. and Schindler, R. H. and Sevilla-Noarbe, I. and Smith, M. and Sobreira, F. and Sommer, N. E. and Suchyta, E. and Swanson, M. E. C. and Tarle, G. and Tucker, B. E. and Tucker, D. L. and Uddin, S. and Walker, A. R.},
abstractNote = {We report that a significant challenge facing photometric surveys for cosmological purposes is the need to produce reliable redshift estimates. The estimation of photometric redshifts (photo-zs) has been consolidated as the standard strategy to bypass the high production costs and incompleteness of spectroscopic redshift samples. Training-based photo-z methods require the preparation of a high-quality list of spectroscopic redshifts, which needs to be constantly updated. The photo-z training, validation, and estimation must be performed in a consistent and reproducible way in order to accomplish the scientific requirements. To meet this purpose, we developed an integrated web-based data interface that not only provides the framework to carry out the above steps in a systematic way, enabling the ease testing and comparison of different algorithms, but also addresses the processing requirements by parallelizing the calculation in a transparent way for the user. This framework called the Science Portal (hereafter Portal) was developed in the context the Dark Energy Survey (DES) to facilitate scientific analysis. In this paper, we show how the Portal can provide a reliable environment to access vast datasets, provide validation algorithms and metrics, even in the case of multiple photo-zs methods. It is possible to maintain the provenance between the steps of a chain of workflows while ensuring reproducibility of the results. We illustrate how the Portal can be used to provide photo-z estimates using the DES first year (Y1A1) data. Finally, while the DES collaboration is still developing techniques to obtain more precise photo-zs, having a structured framework like the one presented here is critical for the systematic vetting of DES algorithmic improvements and the consistent production of photo-zs in future DES releases.},
doi = {10.1016/j.ascom.2018.08.008},
journal = {Astronomy and Computing},
number = C,
volume = 25,
place = {United States},
year = {Mon Sep 10 00:00:00 EDT 2018},
month = {Mon Sep 10 00:00:00 EDT 2018}
}
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DNF – Galaxy photometric redshift by Directional Neighbourhood Fitting
journal, April 2016
- De Vicente, J.; Sánchez, E.; Sevilla-Noarbe, I.
- Monthly Notices of the Royal Astronomical Society, Vol. 459, Issue 3