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Register a new userThe Wide Field Spectrograph (WiFeS): Performance and Data Reduction
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This paper describes the on-telescope performance of the Wide Field Spectrograph (WiFeS). The design characteristics of this instrument, at the Research School of Astronomy and Astrophysics (RSAA) of the Australian National University (ANU) and mounted on the ANU 2.3m telescope at the Siding Spring Observatory has been already described in an earlier paper (Dopita et al. 2007). Here we describe the throughput, resolution and stability of the instrument, and describe some minor issues which have been encountered. We also give a description of the data reduction pipeline, and show some preliminary results.
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We have recently commissioned a novel infrared ($0.9-1.7$ $mu$m) integral field spectrograph (IFS) called the Wide Integral Field Infrared Spectrograph (WIFIS). WIFIS is a unique instrument that offers a very large field-of-view (50$^{primeprime}$ x 20$^{primeprime}$) on the 2.3-meter Bok telescope at Kitt Peak, USA for seeing-limited observations at moderate spectral resolving power. The measured spatial sampling scale is $sim1times1^{primeprime}$ and its spectral resolving power is $Rsim2,500$ and $3,000$ in the $zJ$ ($0.9-1.35$ $mu$m) and $H_{short}$ ($1.5-1.7$ $mu$m) modes, respectively. WIFISs corresponding etendue is larger than existing near-infrared (NIR) IFSes, which are mostly designed to work with adaptive optics systems and therefore have very narrow fields. For this reason, this instrument is specifically suited for studying very extended objects in the near-infrared such as supernovae remnants, galactic star forming regions, and nearby galaxies, which are not easily accessible by other NIR IFSes. This enables scientific programs that were not originally possible, such as detailed surveys of a large number of nearby galaxies or a full accounting of nucleosynthetic yields of Milky Way supernova remnants. WIFIS is also designed to be easily adaptable to be used with larger telescopes. In this paper, we report on the overall performance characteristics of the instrument, which were measured during our commissioning runs in the second half of 2017. We present measurements of spectral resolving power, image quality, instrumental background, and overall efficiency and sensitivity of WIFIS and compare them with our design expectations. Finally, we present a few example observations that demonstrate WIFISs full capability to carry out infrared imaging spectroscopy of extended objects, which is enabled by our custom data reduction pipeline.
OSIRIS is a near-infrared (1.0--2.4 $mu$m) integral field spectrograph operating behind the adaptive optics system at Keck Observatory, and is one of the first lenslet-based integral field spectrographs. Since its commissioning in 2005, it has been a productive instrument, producing nearly half the laser guide star adaptive optics (LGS AO) papers on Keck. The complexity of its raw data format necessitated a custom data reduction pipeline (DRP) delivered with the instrument in order to iteratively assign flux in overlapping spectra to the proper spatial and spectral locations in a data cube. Other than bug fixes and updates required for hardware upgrades, the bulk of the DRP has not been updated since initial instrument commissioning. We report on the first major comprehensive characterization of the DRP using on-sky and calibration data. We also detail improvements to the DRP including characterization of the flux assignment algorithm; exploration of spatial rippling in the reduced data cubes; and improvements to several calibration files, including the rectification matrix, the bad pixel mask, and the wavelength solution. We present lessons learned from over a decade of OSIRIS data reduction that are relevant to the next generation of integral field spectrograph hardware and data reduction software design.
A fully autonomous data reduction pipeline has been developed for FRODOSpec, an optical fibre-fed integral field spectrograph currently in use at the Liverpool Telescope. This paper details the process required for the reduction of data taken using an integral field spectrograph and presents an overview of the computational methods implemented to create the pipeline. Analysis of errors and possible future enhancements are also discussed.
We present the data reduction pipeline for CHARIS, a high-contrast integral-field spectrograph for the Subaru Telescope. The pipeline constructs a ramp from the raw reads using the measured nonlinear pixel response, and reconstructs the data cube using one of three extraction algorithms: aperture photometry, optimal extraction, or $chi^2$ fitting. We measure and apply both a detector flatfield and a lenslet flatfield and reconstruct the wavelength- and position-dependent lenslet point-spread function (PSF) from images taken with a tunable laser. We use these measured PSFs to implement a $chi^2$-based extraction of the data cube, with typical residuals of ~5% due to imperfect models of the undersampled lenslet PSFs. The full two-dimensional residual of the $chi^2$ extraction allows us to model and remove correlated read noise, dramatically improving CHARIS performance. The $chi^2$ extraction produces a data cube that has been deconvolved with the line-spread function, and never performs any interpolations of either the data or the individual lenslet spectra. The extracted data cube also includes uncertainties for each spatial and spectral measurement. CHARIS software is parallelized, written in Python and Cython, and freely available on github with a separate documentation page. Astrometric and spectrophotometric calibrations of the data cubes and PSF subtraction will be treated in a forthcoming paper.
We describe the new spectroscopic data reduction pipeline for the multi-object MMT/Magellan Infrared Spectrograph. The pipeline is implemented in idl as a stand-alone package and is publicly available in both stable and developme
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