Testing LSST dither strategies for survey uniformity and large-scale structure systematics

Autores
Awan, Humna; Gawiser, Eric; Kurczynski, Peter; Jones, R. Lynne; Zhan, Hu; Padilla, Nelson D.; Muñoz Arancibia, Alejandra M.; Orsi, Álvaro; Cora, Sofía Alejandra; Yoachim, Peter
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets (called dithers) on the r-band coadded 5σ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitudes as large as the radius of the LSST field of view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season assignments. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for LSS studies. We calculate the bias in galaxy counts caused by the observing strategy accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We find that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias that are smaller than the minimum statistical floor for a galaxy catalog as deep as r < 27.5. A few of these strategies bring the uncertainties close to the statistical floor for r < 25.7 after the first year of survey.
Facultad de Ciencias Astronómicas y Geofísicas
Instituto de Astrofísica de La Plata
Materia
Ciencias Astronómicas
Física
dark energy
large-scale structure of universe
surveys
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/85923
Acceder
id SEDICI_f8eb65c7c3267d5f0182968a8e956360
oai_identifier_str oai:sedici.unlp.edu.ar:10915/85923
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Testing LSST dither strategies for survey uniformity and large-scale structure systematicsAwan, HumnaGawiser, EricKurczynski, PeterJones, R. LynneZhan, HuPadilla, Nelson D.Muñoz Arancibia, Alejandra M.Orsi, ÁlvaroCora, Sofía AlejandraYoachim, PeterCiencias AstronómicasFísicadark energylarge-scale structure of universesurveysThe Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets (called dithers) on the r-band coadded 5σ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitudes as large as the radius of the LSST field of view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season assignments. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for LSS studies. We calculate the bias in galaxy counts caused by the observing strategy accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We find that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias that are smaller than the minimum statistical floor for a galaxy catalog as deep as r < 27.5. A few of these strategies bring the uncertainties close to the statistical floor for r < 25.7 after the first year of survey.Facultad de Ciencias Astronómicas y GeofísicasInstituto de Astrofísica de La Plata2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/85923enginfo:eu-repo/semantics/altIdentifier/issn/0004-637Xinfo:eu-repo/semantics/altIdentifier/doi/10.3847/0004-637X/829/1/50info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:16:44Zoai:sedici.unlp.edu.ar:10915/85923Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:16:44.655SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Testing LSST dither strategies for survey uniformity and large-scale structure systematics
title Testing LSST dither strategies for survey uniformity and large-scale structure systematics
spellingShingle Testing LSST dither strategies for survey uniformity and large-scale structure systematics
Awan, Humna
Ciencias Astronómicas
Física
dark energy
large-scale structure of universe
surveys
title_short Testing LSST dither strategies for survey uniformity and large-scale structure systematics
title_full Testing LSST dither strategies for survey uniformity and large-scale structure systematics
title_fullStr Testing LSST dither strategies for survey uniformity and large-scale structure systematics
title_full_unstemmed Testing LSST dither strategies for survey uniformity and large-scale structure systematics
title_sort Testing LSST dither strategies for survey uniformity and large-scale structure systematics
dc.creator.none.fl_str_mv Awan, Humna
Gawiser, Eric
Kurczynski, Peter
Jones, R. Lynne
Zhan, Hu
Padilla, Nelson D.
Muñoz Arancibia, Alejandra M.
Orsi, Álvaro
Cora, Sofía Alejandra
Yoachim, Peter
author Awan, Humna
author_facet Awan, Humna
Gawiser, Eric
Kurczynski, Peter
Jones, R. Lynne
Zhan, Hu
Padilla, Nelson D.
Muñoz Arancibia, Alejandra M.
Orsi, Álvaro
Cora, Sofía Alejandra
Yoachim, Peter
author_role author
author2 Gawiser, Eric
Kurczynski, Peter
Jones, R. Lynne
Zhan, Hu
Padilla, Nelson D.
Muñoz Arancibia, Alejandra M.
Orsi, Álvaro
Cora, Sofía Alejandra
Yoachim, Peter
author2_role author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Astronómicas
Física
dark energy
large-scale structure of universe
surveys
topic Ciencias Astronómicas
Física
dark energy
large-scale structure of universe
surveys
dc.description.none.fl_txt_mv The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets (called dithers) on the r-band coadded 5σ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitudes as large as the radius of the LSST field of view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season assignments. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for LSS studies. We calculate the bias in galaxy counts caused by the observing strategy accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We find that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias that are smaller than the minimum statistical floor for a galaxy catalog as deep as r < 27.5. A few of these strategies bring the uncertainties close to the statistical floor for r < 25.7 after the first year of survey.
Facultad de Ciencias Astronómicas y Geofísicas
Instituto de Astrofísica de La Plata
description The Large Synoptic Survey Telescope (LSST) will survey the southern sky from 2022-2032 with unprecedented detail. Since the observing strategy can lead to artifacts in the data, we investigate the effects of telescope-pointing offsets (called dithers) on the r-band coadded 5σ depth yielded after the 10-year survey. We analyze this survey depth for several geometric patterns of dithers (e.g., random, hexagonal lattice, spiral) with amplitudes as large as the radius of the LSST field of view, implemented on different timescales (per season, per night, per visit). Our results illustrate that per night and per visit dither assignments are more effective than per season assignments. Also, we find that some dither geometries (e.g., hexagonal lattice) are particularly sensitive to the timescale on which the dithers are implemented, while others like random dithers perform well on all timescales. We then model the propagation of depth variations to artificial fluctuations in galaxy counts, which are a systematic for LSS studies. We calculate the bias in galaxy counts caused by the observing strategy accounting for photometric calibration uncertainties, dust extinction, and magnitude cuts; uncertainties in this bias limit our ability to account for structure induced by the observing strategy. We find that after 10 years of the LSST survey, the best dither strategies lead to uncertainties in this bias that are smaller than the minimum statistical floor for a galaxy catalog as deep as r < 27.5. A few of these strategies bring the uncertainties close to the statistical floor for r < 25.7 after the first year of survey.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/85923
url http://sedici.unlp.edu.ar/handle/10915/85923
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0004-637X
info:eu-repo/semantics/altIdentifier/doi/10.3847/0004-637X/829/1/50
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844616040006287360
score 13.070432

Publicaciones similares