Data Pipelines for the TRES Echelle Spectrograph

Abstract

The TRES Spectrograph

Design Strategy

To maintain accuracy, we fit a two-dimensional (order and pixel) dispersion function to each spectrum and maintain that function in the header through further processing using formats developed in IRAF for dealing with multi-order echelle data. Using IRAF made it possible to adapt and re-use tasks written to process data from other SAO spectrographs such as FAST (Tokarz& Roll 1997) , Hectospec (Mink et al 2005; (Mink et al 2007) and Hectochelle, as well as IRAF tasks written at NOAO (Valdes 1992), which process images and extract multiple-order Echelle spectra. For portability, all code is written in IRAF CL or SPP.

Data Structure

Each night's raw data resides in a directory designated by [rawdir]/yyyy/yyyy.mmdd, with filenames beginning with a three-digit sequence number, followed by an object name or calibration type (BIAS, DARK, FLAT, or COMP). These filenames are kept through all processing.

Corresponding processed data is in a directory [procdir]/yyyy/yyyy.mmdd. When composite files, such as sums and medians, are created, they are automatically given sequence numbers beyond those used for observed data.

Data Processing

First, the standard IRAF ccdproc task is used to remove the bias levels from the overscan region of the chip and trim that region from the image file. Then the two amplifiers are corrected to the same gain and merged into a single image. Bad pixels are fixed in that merged and trimmed image because they can only be discovered in images combined to remove the many bright spots caused in each image by radiation from the anti-reflection coating on the dewar window. Each image is then corrected by the aperture flattening image to minimize fringing and pixel to pixel variation. If a median image is requested, it is made next, before particle hits and cosmic rays are removed from a group of similar images by a locally-written task which intercompares them. At this point a sum of all of the similar images may be made and added to the processing list along with a requested median file. Then a model of the scattered light is fit to the background of each image, with the spectrum or spectra masked out, and subtracted.

For ThAr wavelength calibration and flat field lamps, one spectrum is then extracted from each image. For object plus sky images, two spectra are extracted. Thorium Argon (ThAr) wavelength calibration spectra are compared to a reference spectrum, and a wavelength to pixel mapping is fit for each one. For each object or sky spectrum, wavelength solutions are found by combining the closest or most recent ThAr solutions. If the simultaneous sky spectrum is going to be removed from the object spectrum, it is first rebinned to the same wavelength solution as the object spectrum, and then corrected for fiber throughput before being subtracted.

Processing Data

Initalization

Quick Look

Quick Look with Cosmic Ray Removal

Figure 1. Processed flat field and ThAr images

Setting Up and Processing a Full Night's Data

btres processes and takes the median of all bias images (those with BIAS as the object name), plotting a histogram of the combined image as an instrument check.

If dark field images are taken, dtres makes a median of all of them and plots a histogram of the combined image as an instrument check.

Images of flat field spectra (with FLAT as the object name) are used to create extraction functions, aperture flattening masks, scattered light masks, and throughput ratios. ftres is run on lists of short-exposure images from each fiber for each observation configuration, creating the necessary masks and functions.

Figure 2. Single order of extracted flat field and ThAr spectra

Thorium Argon spectra (with COMP as the object name) are processed using ttres, which reads a list of raw ThAr spectrum images taken with the same fiber size and binning and extracts them to dispersion-corrected multi-order echelle spectra. Each extracted spectrum (see figure 1) is cross-correlated to a reference spectrum in pixel space using rvsao.xcsao (Kurtz & Mink 2998) The resulting pixel shift is added to the line positions in the reference spectrum database file which is then refit to the lines identified in the ThAr spectrum.

Object spectra are then processed by the trsproc task which runs otres on each list of similar object observations read from the list file created by \textbf{trsgroup}.

Figure 3. Raw stellar spectrum and one order of extracted spectrum

Acknowledgements

Bibliography

• Kurtz, M. J., & Mink, D. J. 1998, PASP, 110, 934.
• Mink, D. J., Wyatt, W. F., Caldwell, N., Conroy, M. A., Furesz, G., & Tokarz, S. P. 2007, in Astronomical Data Analysis Software and Systems XVI, edited by R. A. Shaw, F. Hill, & D. J. Bell, vol. 376 of Astronomical Society of the Pacific Conference Series, 249
• Mink, D. J., Wyatt, W. F., Roll, J. B., Tokarz, S. P., Conroy, M. A., Caldwell, N., Kurtz, M., Geller, M. J., & et al. 2005, in Astronomical Data Analysis Software and Systems XIV, edited by P. Shopbell, M. Britton, & R. Ebert, vol. 347 of Astronomical Society of the Pacific Conference Series, 228
• Szentgyorgyi, A. H., & Fur´esz, G. 2007, in Revista Mexicana de Astronomia y Astrofisica Conference Series, edited by S. Kurtz, vol. 28 of Revista Mexicana de Astronomia y Astrofisica Conference Series, 129
• Tokarz, S. P., & Roll, J. 1997, in Astronomical Data Analysis Software and Systems VI, edited by G. Hunt & H. Payne, vol. 125 of Astronomical Society of the Pacific Conference Series, 140
• Valdes, F. 1992, in Astronomical Data Analysis Software and Systems I, edited by D. M. Worrall, C. Biemesderfer, & J. Barnes, vol. 25 of Astronomical Society of the Pacific Conference Series, 417

Use this Reference:
Douglas J. Mink, 2011, in Astronomical Data Analysis Software and Systems XX, ASP Conference Series, Vol. xxx, Edited by I. Evans, A. Accomazzi, D. Mink, and A. Rots, San Francisco: Astronomical Society of the Pacific, p. xxx