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The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques

The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques
The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques

The primary goals of the STRong lensing Insights into the Dark Energy Survey (STRIDES) collaboration are to measure the dark energy equation of state parameter and the free streaming length of dark matter. To this aim, STRIDES is discovering strongly lensed quasars in the imaging data of the Dark Energy Survey and following them up to measure time delays, high resolution imaging, and spectroscopy sufficient to construct accurate lens models. In this paper, we first present forecasts for STRIDES. Then, we describe the STRIDES classification scheme, and give an overview of the Fall 2016 follow-up campaign. We continue by detailing the results of two selection methods, the outlier selection technique and a morphological algorithm, and presenting lens models of a system that could possibly be a lensed quasar in an unusual configuration. We conclude with the summary statistics of the Fall 2016 campaign. Including searches presented in companion papers (Anguita et al.; Ostrovski et al.), STRIDES followed up 117 targets identifying 7 new strongly lensed systems, and 7 nearly identical quasars, which could be confirmed as lenses by the detection of the lens galaxy. 76 candidates were rejected and 27 remain otherwise inconclusive, for a success rate in the range of 6-35 per cent. This rate is comparable to that of previous searches like SDSS Quasar Lens Search even though the parent data set of STRIDES is purely photometric and our selection of candidates cannot rely on spectroscopic information.

Catalogues, Gravitational lensing: strong, Methods: statistical
0035-8711
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Treu, T.
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Agnello, A.
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Treu, T., Agnello, A., Baumer, M. A., Birrer, S., Buckley-Geer, E. J., Courbin, F., Kim, Y. J., Lin, H., Marshall, P. J., Nord, B., Schechter, P. L., Sivakumar, P. R., Abramson, L. E., Anguita, T., Apostolovski, Y., Auger, M. W., Chan, J. H.H., Chen, G. C.F., Collett, T. E., Fassnacht, C. D., Hsueh, J. W., Lemon, C., McMahon, R. G., Motta, V., Ostrovski, F., Rojas, K., Rusu, C. E., Williams, P., Frieman, J., Meylan, G., Suyu, S. H., Abbott, T. M.C., Abdalla, F. B., Allam, S., Annis, J., Avila, S., Banerji, M., Brooks, D., Rosell, A. Carnero, Carrasco Kind, M., Carretero, J., Castander, F. J., D'Andrea, C. B., da Costa, L. N., De Vicente, J., Doel, P., Eifler, T. F., Flaugher, B., Fosalba, P., García-Bellido, J., Goldstein, D. A., Gruen, D., Gruendl, R. A., Gutierrez, G., Hartley, W. G., Hollowood, D., Honscheid, K., James, D. J., Kuehn, K., Kuropatkin, N., Lima, M., Maia, M. A.G., Martini, P., Menanteau, F., Miquel, R., Plazas, A. A., Romer, A. K., Sanchez, E., Scarpine, V., Schindler, R., Schubnell, M., Sevilla-Noarbe, I., Smith, M., Smith, R. C., Soares-Santos, M., Sobreira, F., Suchyta, E., Swanson, M. E.C., Tarle, G., Thomas, D., Tucker, D. L. and Walker, A. R. (2018) The STRong lensing Insights into the Dark Energy Survey (STRIDES) 2016 follow-up campaign - I. Overview and classification of candidates selected by two techniques. Monthly Notices of the Royal Astronomical Society, 481 (1), 1041-1054. (doi:10.1093/MNRAS/STY2329).

Record type: Article

Abstract

The primary goals of the STRong lensing Insights into the Dark Energy Survey (STRIDES) collaboration are to measure the dark energy equation of state parameter and the free streaming length of dark matter. To this aim, STRIDES is discovering strongly lensed quasars in the imaging data of the Dark Energy Survey and following them up to measure time delays, high resolution imaging, and spectroscopy sufficient to construct accurate lens models. In this paper, we first present forecasts for STRIDES. Then, we describe the STRIDES classification scheme, and give an overview of the Fall 2016 follow-up campaign. We continue by detailing the results of two selection methods, the outlier selection technique and a morphological algorithm, and presenting lens models of a system that could possibly be a lensed quasar in an unusual configuration. We conclude with the summary statistics of the Fall 2016 campaign. Including searches presented in companion papers (Anguita et al.; Ostrovski et al.), STRIDES followed up 117 targets identifying 7 new strongly lensed systems, and 7 nearly identical quasars, which could be confirmed as lenses by the detection of the lens galaxy. 76 candidates were rejected and 27 remain otherwise inconclusive, for a success rate in the range of 6-35 per cent. This rate is comparable to that of previous searches like SDSS Quasar Lens Search even though the parent data set of STRIDES is purely photometric and our selection of candidates cannot rely on spectroscopic information.

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Accepted/In Press date: 22 August 2018
e-pub ahead of print date: 24 August 2018
Published date: 21 November 2018
Keywords: Catalogues, Gravitational lensing: strong, Methods: statistical

Identifiers

Local EPrints ID: 426575
URI: https://eprints.soton.ac.uk/id/eprint/426575
ISSN: 0035-8711
PURE UUID: 5050e459-f0af-4121-ad30-e485527c6311
ORCID for M. Smith: ORCID iD orcid.org/0000-0002-3321-1432

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Date deposited: 30 Nov 2018 17:30
Last modified: 17 May 2019 00:30

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Contributors

Author: T. Treu
Author: A. Agnello
Author: M. A. Baumer
Author: S. Birrer
Author: E. J. Buckley-Geer
Author: F. Courbin
Author: Y. J. Kim
Author: H. Lin
Author: P. J. Marshall
Author: B. Nord
Author: P. L. Schechter
Author: P. R. Sivakumar
Author: L. E. Abramson
Author: T. Anguita
Author: Y. Apostolovski
Author: M. W. Auger
Author: J. H.H. Chan
Author: G. C.F. Chen
Author: T. E. Collett
Author: C. D. Fassnacht
Author: J. W. Hsueh
Author: C. Lemon
Author: R. G. McMahon
Author: V. Motta
Author: F. Ostrovski
Author: K. Rojas
Author: C. E. Rusu
Author: P. Williams
Author: J. Frieman
Author: G. Meylan
Author: S. H. Suyu
Author: T. M.C. Abbott
Author: F. B. Abdalla
Author: S. Allam
Author: J. Annis
Author: S. Avila
Author: M. Banerji
Author: D. Brooks
Author: A. Carnero Rosell
Author: M. Carrasco Kind
Author: J. Carretero
Author: F. J. Castander
Author: C. B. D'Andrea
Author: L. N. da Costa
Author: J. De Vicente
Author: P. Doel
Author: T. F. Eifler
Author: B. Flaugher
Author: P. Fosalba
Author: J. García-Bellido
Author: D. A. Goldstein
Author: D. Gruen
Author: R. A. Gruendl
Author: G. Gutierrez
Author: W. G. Hartley
Author: D. Hollowood
Author: K. Honscheid
Author: D. J. James
Author: K. Kuehn
Author: N. Kuropatkin
Author: M. Lima
Author: M. A.G. Maia
Author: P. Martini
Author: F. Menanteau
Author: R. Miquel
Author: A. A. Plazas
Author: A. K. Romer
Author: E. Sanchez
Author: V. Scarpine
Author: R. Schindler
Author: M. Schubnell
Author: I. Sevilla-Noarbe
Author: M. Smith ORCID iD
Author: R. C. Smith
Author: M. Soares-Santos
Author: F. Sobreira
Author: E. Suchyta
Author: M. E.C. Swanson
Author: G. Tarle
Author: D. Thomas
Author: D. L. Tucker
Author: A. R. Walker

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