Abstract
With the advent of modern multi-detector heterodyne instruments that can result in observations generating thousands of spectra per minute it is no longer feasible to reduce these data as individual spectra. We describe the automated data reduction procedure used to generate baselined data cubes from heterodyne data obtained at the James Clerk Maxwell Telescope. The system can automatically detect baseline regions in spectra and automatically determine regridding parameters, all without input from a user. Additionally it can detect and remove spectra suffering from transient interference effects or anomalous baselines. The pipeline is written as a set of recipes using the ORAC-DR pipeline environment with the algorithmic code using Starlink software packages and infrastructure. The algorithms presented here can be applied to other heterodyne array instruments and have been applied to data from historical JCMT heterodyne instrumentation.
Highlights
As heterodyne receivers have progressed from single-detector instruments (Padman et al 1992; Davies et al 1992; Cunningham et al 1992) to small focal-plane arrays (Graf et al 2003; Schuster et al 2004) to 16-element arrays such as HARP at the James Clerk Maxwell Telescope (JCMT; Buckle et al 2009), and beyond (Kloosterman et al 2012; Hurtado et al 2014), and correlators have improved such that we can obtain spectra at 10 Hz with 8192 channels, data rates have increased substantially such that it is common place to take a short observation resulting in thousands
Self-flat-fielding is limited to data whose signal-to-noise ratio (S/N) of the total flux in each detector permits relative sensitivities to better than about 5 per cent
To ensure that as many of these historical data as possible are made available to the community in a usable format, we have developed an extension to the SMURF package called GSD2ACSIS, which converts the legacy data to the newer Auto-Correlation Spectral Imaging System (ACSIS) data format
Summary
As heterodyne receivers have progressed from single-detector instruments (Padman et al 1992; Davies et al 1992; Cunningham et al 1992) to small focal-plane arrays (Graf et al 2003; Schuster et al 2004) to 16-element arrays such as HARP at the James Clerk Maxwell Telescope (JCMT; Buckle et al 2009), and beyond (Kloosterman et al 2012; Hurtado et al 2014), and correlators have improved such that we can obtain spectra at 10 Hz with 8192 channels, data rates have increased substantially such that it is common place to take a short observation resulting in thousands. The ACSIS online data reduction system (Lightfoot et al 2000; Hovey et al 2000), delivered to the JCMT in 2005, aimed to deal with the data-rate issues by providing a real-time pipeline that co-added the calibrated spectra, with optional baselining, into a data cube with two spatial axes and one spectral axis. This strategy was forced on us given the computer resources available when ACSIS was being designed and developed and was known to have risks associated with it. Deployed in different environments: a basic version to provide neartime feedback at the telescope during observing, a comprehensive version at the observer’s home institution for the advanced reduction and a version at an archive centre that can process the result of a user query, possibly retrieving and combining observations from different projects
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