Fully Automated Reduction of Longslit Spectroscopy with the Low Resolution Imaging Spectrometer at the Keck Observatory
Autor: | Daniel A. Perley |
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Rok vydání: | 2019 |
Předmět: |
Time delay and integration
010504 meteorology & atmospheric sciences Low resolution Imaging spectrometer Polarimetry FOS: Physical sciences Astronomy and Astrophysics 01 natural sciences law.invention Reduction (complexity) Telescope Space and Planetary Science law Observatory 0103 physical sciences Environmental science Astrophysics - Instrumentation and Methods for Astrophysics Spectroscopy Instrumentation and Methods for Astrophysics (astro-ph.IM) 010303 astronomy & astrophysics QC QB 0105 earth and related environmental sciences Remote sensing |
Zdroj: | Publications of the Astronomical Society of the Pacific. 131:084503 |
ISSN: | 1538-3873 0004-6280 |
Popis: | I present and summarize a software package ("LPipe") for completely automated, end-to-end reduction of both bright and faint sources with the Low-Resolution Imaging Spectrometer (LRIS) at Keck Observatory. It supports all gratings, grisms, and dichroics, and also reduces imaging observations, although it does not include multislit or polarimetric reduction capabilities at present. It is suitable for on-the-fly quicklook reductions at the telescope, for large-scale reductions of archival data-sets, and (in many cases) for science-quality post-run reductions of PI data. To demonstrate its capabilities the pipeline is run in fully-automated mode on all LRIS longslit data in the Keck Observatory Archive acquired during the 12-month period between August 2016 and July 2017. The reduced spectra (of 675 single-object targets, totaling ~200 hours of on-source integration time in each camera), and the pipeline itself, are made publicly available to the community. Comment: Accepted to PASP. The demonstration archive of reduced spectra and validation plots is available at http://www.astro.ljmu.ac.uk/~aridperl/lris/archive/. The pipeline is available at http://www.astro.ljmu.ac.uk/~aridperl/lris/ |
Databáze: | OpenAIRE |
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