SpecPro: An Interactive IDL Program for Viewing and Analyzing Astronomical Spectra

Creators: Masters, D.; Capak, P.

Abstract

We present an interactive IDL program for viewing and analyzing astronomical spectra in the context of modern imaging surveys. SpecPro's interactive design lets the user simultaneously view spectroscopic, photometric, and imaging data, allowing for rapid object classification and redshift determination. The spectroscopic redshift can be determined with automated cross-correlation against a variety of spectral templates or by manually overlaying common emission and absorption features on the 1-D and 2-D spectra. Stamp images and the spectral energy distribution (SED) of a source can be displayed with the interface, with the positions of prominent photometric features indicated on the SED plot. Results can easily be saved to file from within the interface. In this article we briefly discuss key interface features and provide an overview of the data formats required by the program.

Additional Information

© 2011 The Astronomical Society of the Pacific. Received 2011 February 8; accepted 2011 March 7; published 2011 April 13. The authors would like to thank Yuko Kakazu, Hai Fu, Lin Yan, and Nick Scoville from the California Institute of Astronomy for their helpful comments and suggestions during the development of the software. In addition, we would like to acknowledge and thank Mara Salvato of the Max Planck Institute for Plasma Physics and Francesca Civano of the Harvard-Smithsonian Center for Astronomy for providing useful feedback on early versions of the code. We also thank Bahram Mobasher of the University of California, Riverside, for carefully reading a draft of this article and making suggestions that significantly improved its content. SpecPro makes use of IDL code written and maintained by others. We thank Wayne Landsman at NASA Goddard Space Flight Center for his work maintaining the IDL Astronomy User's Library. We also thank the authors of code we have used for our implementation of automated cross-correlation, including David Schlegel, Doug Finkbeiner, Michael Cooper, and John Johnson. We thank Craig Markwardt, whose MPFIT least-squares fitting package is integral to the cross-correlation functionality. Finally, we thank an anonymous referee for carefully reading this article and providing very constructive feedback, both in terms of content and with regard to the online distribution of the software. This work was supported in part by a visiting Graduate Student Fellowship at the Caltech Infrared Processing and Analysis Center (IPAC).

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