The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of D...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
J. Guy [verfasserIn] S. Bailey [verfasserIn] A. Kremin [verfasserIn] Shadab Alam [verfasserIn] D. M. Alexander [verfasserIn] C. Allende Prieto [verfasserIn] S. BenZvi [verfasserIn] A. S. Bolton [verfasserIn] D. Brooks [verfasserIn] E. Chaussidon [verfasserIn] A. P. Cooper [verfasserIn] K. Dawson [verfasserIn] A. de la Macorra [verfasserIn] A. Dey [verfasserIn] Biprateep Dey [verfasserIn] G. Dhungana [verfasserIn] D. J. Eisenstein [verfasserIn] A. Font-Ribera [verfasserIn] J. E. Forero-Romero [verfasserIn] E. Gaztañaga [verfasserIn] S. Gontcho A Gontcho [verfasserIn] D. Green [verfasserIn] K. Honscheid [verfasserIn] M. Ishak [verfasserIn] R. Kehoe [verfasserIn] D. Kirkby [verfasserIn] T. Kisner [verfasserIn] Sergey E. Koposov [verfasserIn] Ting-Wen Lan [verfasserIn] M. Landriau [verfasserIn] L. Le Guillou [verfasserIn] Michael E. Levi [verfasserIn] C. Magneville [verfasserIn] Christopher J. Manser [verfasserIn] P. Martini [verfasserIn] Aaron M. Meisner [verfasserIn] R. Miquel [verfasserIn] J. Moustakas [verfasserIn] Adam D. Myers [verfasserIn] Jeffrey A. Newman [verfasserIn] Jundan Nie [verfasserIn] N. Palanque-Delabrouille [verfasserIn] W. J. Percival [verfasserIn] C. Poppett [verfasserIn] F. Prada [verfasserIn] A. Raichoor [verfasserIn] C. Ravoux [verfasserIn] A. J. Ross [verfasserIn] E. F. Schlafly [verfasserIn] D. Schlegel [verfasserIn] M. Schubnell [verfasserIn] Ray M. Sharples [verfasserIn] Gregory Tarlé [verfasserIn] B. A. Weaver [verfasserIn] Christophe Yéche [verfasserIn] Rongpu Zhou [verfasserIn] Zhimin Zhou [verfasserIn] H. Zou [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2023 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: The Astronomical Journal - IOP Publishing, 2022, 165(2023), 4, p 144 |
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| Übergeordnetes Werk: |
volume:165 ; year:2023 ; number:4, p 144 |
| Links: |
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| DOI / URN: |
10.3847/1538-3881/acb212 |
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| Katalog-ID: |
DOAJ089159780 |
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| 520 | |a We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. | ||
| 650 | 4 | |a Galaxy spectroscopy | |
| 650 | 4 | |a High-redshift galaxies | |
| 650 | 4 | |a Redshift surveys | |
| 653 | 0 | |a Astronomy | |
| 700 | 0 | |a S. Bailey |e verfasserin |4 aut | |
| 700 | 0 | |a A. Kremin |e verfasserin |4 aut | |
| 700 | 0 | |a Shadab Alam |e verfasserin |4 aut | |
| 700 | 0 | |a D. M. Alexander |e verfasserin |4 aut | |
| 700 | 0 | |a C. Allende Prieto |e verfasserin |4 aut | |
| 700 | 0 | |a S. BenZvi |e verfasserin |4 aut | |
| 700 | 0 | |a A. S. Bolton |e verfasserin |4 aut | |
| 700 | 0 | |a D. Brooks |e verfasserin |4 aut | |
| 700 | 0 | |a E. Chaussidon |e verfasserin |4 aut | |
| 700 | 0 | |a A. P. Cooper |e verfasserin |4 aut | |
| 700 | 0 | |a K. Dawson |e verfasserin |4 aut | |
| 700 | 0 | |a A. de la Macorra |e verfasserin |4 aut | |
| 700 | 0 | |a A. Dey |e verfasserin |4 aut | |
| 700 | 0 | |a Biprateep Dey |e verfasserin |4 aut | |
| 700 | 0 | |a G. Dhungana |e verfasserin |4 aut | |
| 700 | 0 | |a D. J. Eisenstein |e verfasserin |4 aut | |
| 700 | 0 | |a A. Font-Ribera |e verfasserin |4 aut | |
| 700 | 0 | |a J. E. Forero-Romero |e verfasserin |4 aut | |
| 700 | 0 | |a E. Gaztañaga |e verfasserin |4 aut | |
| 700 | 0 | |a S. Gontcho A Gontcho |e verfasserin |4 aut | |
| 700 | 0 | |a D. Green |e verfasserin |4 aut | |
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| 700 | 0 | |a M. Ishak |e verfasserin |4 aut | |
| 700 | 0 | |a R. Kehoe |e verfasserin |4 aut | |
| 700 | 0 | |a D. Kirkby |e verfasserin |4 aut | |
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| 700 | 0 | |a Christopher J. Manser |e verfasserin |4 aut | |
| 700 | 0 | |a P. Martini |e verfasserin |4 aut | |
| 700 | 0 | |a Aaron M. Meisner |e verfasserin |4 aut | |
| 700 | 0 | |a R. Miquel |e verfasserin |4 aut | |
| 700 | 0 | |a J. Moustakas |e verfasserin |4 aut | |
| 700 | 0 | |a Adam D. Myers |e verfasserin |4 aut | |
| 700 | 0 | |a Jeffrey A. Newman |e verfasserin |4 aut | |
| 700 | 0 | |a Jundan Nie |e verfasserin |4 aut | |
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| 700 | 0 | |a D. Schlegel |e verfasserin |4 aut | |
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| 700 | 0 | |a Zhimin Zhou |e verfasserin |4 aut | |
| 700 | 0 | |a H. Zou |e verfasserin |4 aut | |
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10.3847/1538-3881/acb212 doi (DE-627)DOAJ089159780 (DE-599)DOAJ5a5d1a71e2eb4fc38171584b263936ba DE-627 ger DE-627 rakwb eng QB1-991 J. Guy verfasserin aut The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. Galaxy spectroscopy High-redshift galaxies Redshift surveys Astronomy S. Bailey verfasserin aut A. Kremin verfasserin aut Shadab Alam verfasserin aut D. M. Alexander verfasserin aut C. Allende Prieto verfasserin aut S. BenZvi verfasserin aut A. S. Bolton verfasserin aut D. Brooks verfasserin aut E. Chaussidon verfasserin aut A. P. Cooper verfasserin aut K. Dawson verfasserin aut A. de la Macorra verfasserin aut A. Dey verfasserin aut Biprateep Dey verfasserin aut G. Dhungana verfasserin aut D. J. Eisenstein verfasserin aut A. Font-Ribera verfasserin aut J. E. Forero-Romero verfasserin aut E. Gaztañaga verfasserin aut S. Gontcho A Gontcho verfasserin aut D. Green verfasserin aut K. Honscheid verfasserin aut M. Ishak verfasserin aut R. Kehoe verfasserin aut D. Kirkby verfasserin aut T. Kisner verfasserin aut Sergey E. Koposov verfasserin aut Ting-Wen Lan verfasserin aut M. Landriau verfasserin aut L. Le Guillou verfasserin aut Michael E. Levi verfasserin aut C. Magneville verfasserin aut Christopher J. Manser verfasserin aut P. Martini verfasserin aut Aaron M. Meisner verfasserin aut R. Miquel verfasserin aut J. Moustakas verfasserin aut Adam D. Myers verfasserin aut Jeffrey A. Newman verfasserin aut Jundan Nie verfasserin aut N. Palanque-Delabrouille verfasserin aut W. J. Percival verfasserin aut C. Poppett verfasserin aut F. Prada verfasserin aut A. Raichoor verfasserin aut C. Ravoux verfasserin aut A. J. Ross verfasserin aut E. F. Schlafly verfasserin aut D. Schlegel verfasserin aut M. Schubnell verfasserin aut Ray M. Sharples verfasserin aut Gregory Tarlé verfasserin aut B. A. Weaver verfasserin aut Christophe Yéche verfasserin aut Rongpu Zhou verfasserin aut Zhimin Zhou verfasserin aut H. Zou verfasserin aut In The Astronomical Journal IOP Publishing, 2022 165(2023), 4, p 144 (DE-627)312175647 (DE-600)2003104-X 15383881 nnns volume:165 year:2023 number:4, p 144 https://doi.org/10.3847/1538-3881/acb212 kostenfrei https://doaj.org/article/5a5d1a71e2eb4fc38171584b263936ba kostenfrei https://doi.org/10.3847/1538-3881/acb212 kostenfrei https://doaj.org/toc/1538-3881 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2129 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 165 2023 4, p 144 |
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10.3847/1538-3881/acb212 doi (DE-627)DOAJ089159780 (DE-599)DOAJ5a5d1a71e2eb4fc38171584b263936ba DE-627 ger DE-627 rakwb eng QB1-991 J. Guy verfasserin aut The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. Galaxy spectroscopy High-redshift galaxies Redshift surveys Astronomy S. Bailey verfasserin aut A. Kremin verfasserin aut Shadab Alam verfasserin aut D. M. Alexander verfasserin aut C. Allende Prieto verfasserin aut S. BenZvi verfasserin aut A. S. Bolton verfasserin aut D. Brooks verfasserin aut E. Chaussidon verfasserin aut A. P. Cooper verfasserin aut K. Dawson verfasserin aut A. de la Macorra verfasserin aut A. Dey verfasserin aut Biprateep Dey verfasserin aut G. Dhungana verfasserin aut D. J. Eisenstein verfasserin aut A. Font-Ribera verfasserin aut J. E. Forero-Romero verfasserin aut E. Gaztañaga verfasserin aut S. Gontcho A Gontcho verfasserin aut D. Green verfasserin aut K. Honscheid verfasserin aut M. Ishak verfasserin aut R. Kehoe verfasserin aut D. Kirkby verfasserin aut T. Kisner verfasserin aut Sergey E. Koposov verfasserin aut Ting-Wen Lan verfasserin aut M. Landriau verfasserin aut L. Le Guillou verfasserin aut Michael E. Levi verfasserin aut C. Magneville verfasserin aut Christopher J. Manser verfasserin aut P. Martini verfasserin aut Aaron M. Meisner verfasserin aut R. Miquel verfasserin aut J. Moustakas verfasserin aut Adam D. Myers verfasserin aut Jeffrey A. Newman verfasserin aut Jundan Nie verfasserin aut N. Palanque-Delabrouille verfasserin aut W. J. Percival verfasserin aut C. Poppett verfasserin aut F. Prada verfasserin aut A. Raichoor verfasserin aut C. Ravoux verfasserin aut A. J. Ross verfasserin aut E. F. Schlafly verfasserin aut D. Schlegel verfasserin aut M. Schubnell verfasserin aut Ray M. Sharples verfasserin aut Gregory Tarlé verfasserin aut B. A. Weaver verfasserin aut Christophe Yéche verfasserin aut Rongpu Zhou verfasserin aut Zhimin Zhou verfasserin aut H. Zou verfasserin aut In The Astronomical Journal IOP Publishing, 2022 165(2023), 4, p 144 (DE-627)312175647 (DE-600)2003104-X 15383881 nnns volume:165 year:2023 number:4, p 144 https://doi.org/10.3847/1538-3881/acb212 kostenfrei https://doaj.org/article/5a5d1a71e2eb4fc38171584b263936ba kostenfrei https://doi.org/10.3847/1538-3881/acb212 kostenfrei https://doaj.org/toc/1538-3881 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2006 GBV_ILN_2014 GBV_ILN_2088 GBV_ILN_2110 GBV_ILN_2129 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 165 2023 4, p 144 |
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J. Guy @@aut@@ S. Bailey @@aut@@ A. Kremin @@aut@@ Shadab Alam @@aut@@ D. M. Alexander @@aut@@ C. Allende Prieto @@aut@@ S. BenZvi @@aut@@ A. S. Bolton @@aut@@ D. Brooks @@aut@@ E. Chaussidon @@aut@@ A. P. Cooper @@aut@@ K. Dawson @@aut@@ A. de la Macorra @@aut@@ A. Dey @@aut@@ Biprateep Dey @@aut@@ G. Dhungana @@aut@@ D. J. Eisenstein @@aut@@ A. Font-Ribera @@aut@@ J. E. Forero-Romero @@aut@@ E. Gaztañaga @@aut@@ S. Gontcho A Gontcho @@aut@@ D. Green @@aut@@ K. Honscheid @@aut@@ M. Ishak @@aut@@ R. Kehoe @@aut@@ D. Kirkby @@aut@@ T. Kisner @@aut@@ Sergey E. Koposov @@aut@@ Ting-Wen Lan @@aut@@ M. Landriau @@aut@@ L. Le Guillou @@aut@@ Michael E. Levi @@aut@@ C. Magneville @@aut@@ Christopher J. Manser @@aut@@ P. Martini @@aut@@ Aaron M. Meisner @@aut@@ R. Miquel @@aut@@ J. Moustakas @@aut@@ Adam D. Myers @@aut@@ Jeffrey A. Newman @@aut@@ Jundan Nie @@aut@@ N. Palanque-Delabrouille @@aut@@ W. J. Percival @@aut@@ C. Poppett @@aut@@ F. Prada @@aut@@ A. Raichoor @@aut@@ C. Ravoux @@aut@@ A. J. Ross @@aut@@ E. F. Schlafly @@aut@@ D. Schlegel @@aut@@ M. Schubnell @@aut@@ Ray M. Sharples @@aut@@ Gregory Tarlé @@aut@@ B. A. Weaver @@aut@@ Christophe Yéche @@aut@@ Rongpu Zhou @@aut@@ Zhimin Zhou @@aut@@ H. Zou @@aut@@ |
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Q - Science |
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J. Guy |
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J. Guy misc QB1-991 misc Galaxy spectroscopy misc High-redshift galaxies misc Redshift surveys misc Astronomy The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument |
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QB1-991 The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument Galaxy spectroscopy High-redshift galaxies Redshift surveys |
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misc QB1-991 misc Galaxy spectroscopy misc High-redshift galaxies misc Redshift surveys misc Astronomy |
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The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument |
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The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument |
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J. Guy S. Bailey A. Kremin Shadab Alam D. M. Alexander C. Allende Prieto S. BenZvi A. S. Bolton D. Brooks E. Chaussidon A. P. Cooper K. Dawson A. de la Macorra A. Dey Biprateep Dey G. Dhungana D. J. Eisenstein A. Font-Ribera J. E. Forero-Romero E. Gaztañaga S. Gontcho A Gontcho D. Green K. Honscheid M. Ishak R. Kehoe D. Kirkby T. Kisner Sergey E. Koposov Ting-Wen Lan M. Landriau L. Le Guillou Michael E. Levi C. Magneville Christopher J. Manser P. Martini Aaron M. Meisner R. Miquel J. Moustakas Adam D. Myers Jeffrey A. Newman Jundan Nie N. Palanque-Delabrouille W. J. Percival C. Poppett F. Prada A. Raichoor C. Ravoux A. J. Ross E. F. Schlafly D. Schlegel M. Schubnell Ray M. Sharples Gregory Tarlé B. A. Weaver Christophe Yéche Rongpu Zhou Zhimin Zhou H. Zou |
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verfasserin |
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spectroscopic data processing pipeline for the dark energy spectroscopic instrument |
| callnumber |
QB1-991 |
| title_auth |
The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument |
| abstract |
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. |
| abstractGer |
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. |
| abstract_unstemmed |
We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4 m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the universe with the baryon acoustic oscillation technique and the growth rate of structure with redshift space distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near-UV to near-infrared (3600–9800 Å) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline’s algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project’s requirements for redshift performance, with high efficiency and a purity greater than 99% for all target classes. |
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| container_issue |
4, p 144 |
| title_short |
The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument |
| url |
https://doi.org/10.3847/1538-3881/acb212 https://doaj.org/article/5a5d1a71e2eb4fc38171584b263936ba https://doaj.org/toc/1538-3881 |
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S. Bailey A. Kremin Shadab Alam D. M. Alexander C. Allende Prieto S. BenZvi A. S. Bolton D. Brooks E. Chaussidon A. P. Cooper K. Dawson A. de la Macorra A. Dey Biprateep Dey G. Dhungana D. J. Eisenstein A. Font-Ribera J. E. Forero-Romero E. Gaztañaga S. Gontcho A Gontcho D. Green K. Honscheid M. Ishak R. Kehoe D. Kirkby T. Kisner Sergey E. Koposov Ting-Wen Lan M. Landriau L. Le Guillou Michael E. Levi C. Magneville Christopher J. Manser P. Martini Aaron M. Meisner R. Miquel J. Moustakas Adam D. Myers Jeffrey A. Newman Jundan Nie N. Palanque-Delabrouille W. J. Percival C. Poppett F. Prada A. Raichoor C. Ravoux A. J. Ross E. F. Schlafly D. Schlegel M. Schubnell Ray M. Sharples Gregory Tarlé B. A. Weaver Christophe Yéche Rongpu Zhou Zhimin Zhou H. Zou |
| author2Str |
S. Bailey A. Kremin Shadab Alam D. M. Alexander C. Allende Prieto S. BenZvi A. S. Bolton D. Brooks E. Chaussidon A. P. Cooper K. Dawson A. de la Macorra A. Dey Biprateep Dey G. Dhungana D. J. Eisenstein A. Font-Ribera J. E. Forero-Romero E. Gaztañaga S. Gontcho A Gontcho D. Green K. Honscheid M. Ishak R. Kehoe D. Kirkby T. Kisner Sergey E. Koposov Ting-Wen Lan M. Landriau L. Le Guillou Michael E. Levi C. Magneville Christopher J. Manser P. Martini Aaron M. Meisner R. Miquel J. Moustakas Adam D. Myers Jeffrey A. Newman Jundan Nie N. Palanque-Delabrouille W. J. Percival C. Poppett F. Prada A. Raichoor C. Ravoux A. J. Ross E. F. Schlafly D. Schlegel M. Schubnell Ray M. Sharples Gregory Tarlé B. A. Weaver Christophe Yéche Rongpu Zhou Zhimin Zhou H. Zou |
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312175647 |
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QB - Astronomy |
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| doi_str |
10.3847/1538-3881/acb212 |
| callnumber-a |
QB1-991 |
| up_date |
2024-07-03T21:36:14.771Z |
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1803595362885173248 |
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| score |
7.3982077 |