publication . Article . Preprint . 2018

DES Science Portal: II- Creating Science-Ready Catalogs

Rafe Schindler; Eric Suchyta; K. Honscheid; E. Buckley-Geer; Felipe Menanteau; Felipe Menanteau; R. L. C. Ogando; Diego Capozzi; S. E. Kuhlmann; J. Gschwend; ...
Open Access
  • Published: 01 Jul 2018
Abstract
Comment: The second paper of the series about the DES Science Portal, submitted to the Astronomy & Computing journal. It shows the infrastructure to create science-ready catalogs from DES photometric data and ancillary maps. This is the version accepted by the journal
Persistent Identifiers
Subjects
free text keywords: Astronomical databases, Catalogs, Surveys—methods, Data analysis, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], RCUK, STFC, Astronomy and Astrophysics, Computer Science Applications, Astrophysics - Instrumentation and Methods for Astrophysics, Large Synoptic Survey Telescope, Data science, Computer science, Data management, business.industry, business, Data products, Relational database, Software, Astronomical survey
Funded by
EC| COSMICDAWN
Project
COSMICDAWN
Understanding the Origin of Cosmic Structure
  • Funder: European Commission (EC)
  • Project Code: 306478
  • Funding stream: FP7 | SP2 | ERC
,
NSF| Collaborative Research: The Dark Energy Survey Data Management Operations
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1138766
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
,
EC| TESTDE
Project
TESTDE
Testing the Dark Energy Paradigm and Measuring Neutrino Mass with the Dark Energy Survey
  • Funder: European Commission (EC)
  • Project Code: 291329
  • Funding stream: FP7 | SP2 | ERC
,
EC| COGS
Project
COGS
Capitalizing on Gravitational Shear
  • Funder: European Commission (EC)
  • Project Code: 240672
  • Funding stream: FP7 | SP2 | ERC
51 references, page 1 of 4

Arnouts, S., Moscardini, L., Vanzella, E., et al., 2002. Measuring the redshift evolution of clustering: the Hubble Deep Field South. MNRAS 329, 355-366. doi:10.1046/j.1365-8711.2002.04988.x, arXiv:astro-ph/0109453.

Arnouts, S., Vandame, B., Benoist, C., et al., 2001. ESO imaging survey. Deep public survey: Multi-color optical data for the Chandra Deep Field South. A&A 379, 740-754. doi:10.1051/0004-6361:20011341, arXiv:astro-ph/0103071. [OpenAIRE]

Bernyk, M., Croton, D.J., Tonini, C., Hodkinson, L., Hassan, A.H., Garel, T., Duffy, A.R., Mutch, S.J., Poole, G.B., Hegarty, S., 2016. The Theoretical Astrophysical Observatory: Cloud-based Mock Galaxy Catalogs. ApJS 223, 9. doi:10.3847/0067-0049/223/1/9, arXiv:1403.5270.

Bertin, E., Arnouts, S., 1996. SExtractor: Software for source extraction. A&AS 117, 393-404. doi:10.1051/aas:1996164. [OpenAIRE]

Bruzual, G., Charlot, S., 2003. Stellar population synthesis at the resolution of 2003. MNRAS 344, 1000-1028. doi:10.1046/j.1365-8711.2003. 06897.x, arXiv:astro-ph/0309134.

Capak, P., Aussel, H., Ajiki, M., et al., 2007. The First Release COSMOS Optical and Near-IR Data and Catalog. ApJS 172, 99-116. doi:10.1086/519081, arXiv:0704.2430.

Carlstrom, J.E., Ade, P.A.R., Aird, K.A., et al., 2011. The 10 Meter South Pole Telescope. PASP 123, 568-581. doi:10.1086/659879, arXiv:0907.4445.

Carrasco Kind, M., Brunner, R., 2014. MLZ: Machine Learning for photo-Z. Astrophysics Source Code Library. arXiv:1403.003.

Carrasco Kind, M., Brunner, R.J., 2013. TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests. MNRAS 432, 1483-1501. doi:10.1093/mnras/stt574, arXiv:1303.7269.

Chang, C., Busha, M.T., Wechsler, R., et al., 2015. Modeling the Transfer Function for the Dark Energy Survey. ApJ 801, 73. doi:10.1088/0004-637X/ 801/2/73, arXiv:1411.0032. [OpenAIRE]

Comparat, J., Delubac, T., Jouvel, S., et al., 2016. SDSS-IV eBOSS emissionline galaxy pilot survey. A&A 592, A121. doi:10.1051/0004-6361/ 201527377, arXiv:1509.05045. [OpenAIRE]

de Jong, J.T.A., Kuijken, K., Applegate, D., et al., 2013. The Kilo-Degree Survey. The Messenger 154, 44-46.

De Vicente, J., Sánchez, E., Sevilla-Noarbe, I., 2016. DNF - Galaxy photometric redshift by Directional Neighbourhood Fitting. MNRAS 459, 3078-3088. doi:10.1093/mnras/stw857, arXiv:1511.07623.

Desai, S., Armstrong, R., Mohr, J.J., et al., 2012. The Blanco Cosmology Survey: Data Acquisition, Processing, Calibration, Quality Diagnostics, and Data Release. ApJ 757, 83. doi:10.1088/0004-637X/757/1/83, arXiv:1204.1210.

Drlica-Wagner, A., Sevilla-Noarbe, I., Rykoff, E.S., Gruendl, R.A., Yanny, B., Tucker, D.L., Hoyle, B., Carnero Rosell, A., Bernstein, G.M., Bechtol, K., Becker, M.R., Benoit-Levy, A., Bertin, E., Carrasco Kind, M., Davis, Smith, M., Smith, R.C., Soares-Santos, M., Sobreira, F., Suchyta, E., Tarle, G., Vikram, V., Walker, A.R., Wechsler, R.H., Zuntz, J., 2017. Dark Energy Survey Year 1 Results: Photometric Data Set for Cosmology. ArXiv e-prints arXiv:1708.01531.

51 references, page 1 of 4
Abstract
Comment: The second paper of the series about the DES Science Portal, submitted to the Astronomy & Computing journal. It shows the infrastructure to create science-ready catalogs from DES photometric data and ancillary maps. This is the version accepted by the journal
Persistent Identifiers
Subjects
free text keywords: Astronomical databases, Catalogs, Surveys—methods, Data analysis, [PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], RCUK, STFC, Astronomy and Astrophysics, Computer Science Applications, Astrophysics - Instrumentation and Methods for Astrophysics, Large Synoptic Survey Telescope, Data science, Computer science, Data management, business.industry, business, Data products, Relational database, Software, Astronomical survey
Funded by
EC| COSMICDAWN
Project
COSMICDAWN
Understanding the Origin of Cosmic Structure
  • Funder: European Commission (EC)
  • Project Code: 306478
  • Funding stream: FP7 | SP2 | ERC
,
NSF| Collaborative Research: The Dark Energy Survey Data Management Operations
Project
  • Funder: National Science Foundation (NSF)
  • Project Code: 1138766
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Astronomical Sciences
,
EC| TESTDE
Project
TESTDE
Testing the Dark Energy Paradigm and Measuring Neutrino Mass with the Dark Energy Survey
  • Funder: European Commission (EC)
  • Project Code: 291329
  • Funding stream: FP7 | SP2 | ERC
,
EC| COGS
Project
COGS
Capitalizing on Gravitational Shear
  • Funder: European Commission (EC)
  • Project Code: 240672
  • Funding stream: FP7 | SP2 | ERC
51 references, page 1 of 4

Arnouts, S., Moscardini, L., Vanzella, E., et al., 2002. Measuring the redshift evolution of clustering: the Hubble Deep Field South. MNRAS 329, 355-366. doi:10.1046/j.1365-8711.2002.04988.x, arXiv:astro-ph/0109453.

Arnouts, S., Vandame, B., Benoist, C., et al., 2001. ESO imaging survey. Deep public survey: Multi-color optical data for the Chandra Deep Field South. A&A 379, 740-754. doi:10.1051/0004-6361:20011341, arXiv:astro-ph/0103071. [OpenAIRE]

Bernyk, M., Croton, D.J., Tonini, C., Hodkinson, L., Hassan, A.H., Garel, T., Duffy, A.R., Mutch, S.J., Poole, G.B., Hegarty, S., 2016. The Theoretical Astrophysical Observatory: Cloud-based Mock Galaxy Catalogs. ApJS 223, 9. doi:10.3847/0067-0049/223/1/9, arXiv:1403.5270.

Bertin, E., Arnouts, S., 1996. SExtractor: Software for source extraction. A&AS 117, 393-404. doi:10.1051/aas:1996164. [OpenAIRE]

Bruzual, G., Charlot, S., 2003. Stellar population synthesis at the resolution of 2003. MNRAS 344, 1000-1028. doi:10.1046/j.1365-8711.2003. 06897.x, arXiv:astro-ph/0309134.

Capak, P., Aussel, H., Ajiki, M., et al., 2007. The First Release COSMOS Optical and Near-IR Data and Catalog. ApJS 172, 99-116. doi:10.1086/519081, arXiv:0704.2430.

Carlstrom, J.E., Ade, P.A.R., Aird, K.A., et al., 2011. The 10 Meter South Pole Telescope. PASP 123, 568-581. doi:10.1086/659879, arXiv:0907.4445.

Carrasco Kind, M., Brunner, R., 2014. MLZ: Machine Learning for photo-Z. Astrophysics Source Code Library. arXiv:1403.003.

Carrasco Kind, M., Brunner, R.J., 2013. TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests. MNRAS 432, 1483-1501. doi:10.1093/mnras/stt574, arXiv:1303.7269.

Chang, C., Busha, M.T., Wechsler, R., et al., 2015. Modeling the Transfer Function for the Dark Energy Survey. ApJ 801, 73. doi:10.1088/0004-637X/ 801/2/73, arXiv:1411.0032. [OpenAIRE]

Comparat, J., Delubac, T., Jouvel, S., et al., 2016. SDSS-IV eBOSS emissionline galaxy pilot survey. A&A 592, A121. doi:10.1051/0004-6361/ 201527377, arXiv:1509.05045. [OpenAIRE]

de Jong, J.T.A., Kuijken, K., Applegate, D., et al., 2013. The Kilo-Degree Survey. The Messenger 154, 44-46.

De Vicente, J., Sánchez, E., Sevilla-Noarbe, I., 2016. DNF - Galaxy photometric redshift by Directional Neighbourhood Fitting. MNRAS 459, 3078-3088. doi:10.1093/mnras/stw857, arXiv:1511.07623.

Desai, S., Armstrong, R., Mohr, J.J., et al., 2012. The Blanco Cosmology Survey: Data Acquisition, Processing, Calibration, Quality Diagnostics, and Data Release. ApJ 757, 83. doi:10.1088/0004-637X/757/1/83, arXiv:1204.1210.

Drlica-Wagner, A., Sevilla-Noarbe, I., Rykoff, E.S., Gruendl, R.A., Yanny, B., Tucker, D.L., Hoyle, B., Carnero Rosell, A., Bernstein, G.M., Bechtol, K., Becker, M.R., Benoit-Levy, A., Bertin, E., Carrasco Kind, M., Davis, Smith, M., Smith, R.C., Soares-Santos, M., Sobreira, F., Suchyta, E., Tarle, G., Vikram, V., Walker, A.R., Wechsler, R.H., Zuntz, J., 2017. Dark Energy Survey Year 1 Results: Photometric Data Set for Cosmology. ArXiv e-prints arXiv:1708.01531.

51 references, page 1 of 4
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