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Tim Jenness
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SCUBA-2 is the largest submillimetre array camera in the world and was commissioned on the James Clerk Maxwell Telescope (JCMT) with two arrays towards the end of 2009. A period of shared-risks observing was then completed and the full planned complement of 8 arrays, 4 at 850 microns and 4 at 450 microns, are now installed and ready to be commissioned. SCUBA-2 has 10,240 bolometers, corresponding to a data rate of 8 MB/s when sampled at the nominal rate of 200 Hz. The pipeline produces useful maps in near real time at the telescope and often publication quality maps in the JCMT Science Archive (JSA) hosted at the Canadian Astronomy Data Centre (CADC).
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The second Gaia data release is based on 22 months of mission data with an average of 0.9 billion individual CCD observations per day. A data volume of this size and granularity requires a robust and reliable but still flexible system to achieve the demanding accuracy and precision constraints that Gaia is capable of delivering. The internal Gaia photometric system was initialised using an iterative process that is solely based on Gaia data. A set of calibrations was derived for the entire Gaia DR2 baseline and then used to produce the final mean source photometry. The photometric catalogue contains 2.5 billion sources comprised of three different grades depending on the availability of colour information and the procedure used to calibrate them: 1.5 billion gold, 144 million silver, and 0.9 billion bronze. These figures reflect the results of the photometric processing; the content of the data release will be different due to the validation and data quality filters applied during the catalogue preparation. The photometric processing pipeline, PhotPipe, implements all the processing and calibration workflows in terms of Map/Reduce jobs based on the Hadoop platform. This is the first example of a processing system for a large astrophysical survey project to make use of these technologies. The improvements in the generation of the integrated G-band fluxes, in the attitude modelling, in the cross-matching, and and in the identification of spurious detections led to a much cleaner input stream for the photometric processing. This, combined with the improvements in the definition of the internal photometric system and calibration flow, produced high-quality photometry. Hadoop proved to be an excellent platform choice for the implementation of PhotPipe in terms of overall performance, scalability, downtime, and manpower required for operations and maintenance.
The Gaia DR2 sample of short-timescale variable candidates results from the investigation of the first 22 months of Gaia photometry for a subsample of sources at the Gaia faint end. For this exercise, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, high-frequency search by means of least-squares periodograms, and empirical selection based on the investigation of specific sources seen through the Gaia eyes (e.g. known variables or visually identified objects with peculiar features in their light curves). The progressive definition and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few preliminary candidates, performed at the Flemish Mercator telescope (Canary Islands, Spain) between August and November 2017. We publish a list of 3,018 short-timescale variable candidates, spread throughout the sky, with a false-positive rate up to 10-20% in the Magellanic Clouds, and a more significant but justifiable contamination from longer-period variables between 19% and 50%, depending on the area of the sky. Although its completeness is limited to about 0.05%, this first sample of Gaia short-timescale variables recovers some very interesting known short-period variables, such as post-common envelope binaries or cataclysmic variables, and brings to light some fascinating, newly discovered variable sources. In the perspective of future Gaia data releases, several improvements of the short-timescale variability processing are considered, by enhancing the existing variogram and period-search algorithms or by classifying the identified candidates. Nonetheless, the encouraging outcome of our Gaia DR2 analysis demonstrates the power of this mission for such fast-variability studies, and opens great perspectives for this domain of astrophysics.
Solar X-ray Monitor (XSM) instrument of Indias Chandrayaan-2 lunar mission carries out broadband spectroscopy of the Sun in soft X-rays. XSM, with its unique features such as low background, high time cadence, and high spectral resolution, provides the opportunity to characterize transient and quiescent X-ray emission from the Sun even during low activity periods. It records the X-ray spectrum at one-second cadence, and the data recorded on-board are downloaded at regular intervals along with that of other payloads. During ground pre-processing, the XSM data is segregated, and the level-0 data is made available for higher levels of processing at the Payload Operations Center (POC). XSM Data Analysis Software (XSMDAS) is developed to carry out the processing of the level-0 data to higher levels and to generate calibrated light curves and spectra for user-defined binning parameters such that it is suitable for further scientific analysis. A front-end for the XSMDAS named XSM Quick Look Display (XSMQLD) is also developed to facilitate a first look at the data without applying calibration. XSM Data Management-Monitoring System (XSMDMS) is designed to carry out automated data processing at the POC and to maintain an SQLite database with relevant information on the data sets and an internal web application for monitoring data quality and instrument health. All XSM raw and calibrated data products are in FITS format, organized into day-wise files, and the data archive follows Planetary Data System-4 (PDS4) standards. The XSM data will be made available after a lock-in period along with the XSM Data Analysis Software from ISRO Science Data Archive (ISDA) at Indian Space Science Data Center(ISSDC). Here we discuss the design and implementation of all components of the software for the XSM data processing and the contents of the XSM data archive.
Performing ground-based submillimetre observations is a difficult task as the measurements are subject to absorption and emission from water vapour in the Earths atmosphere and time variation in weather and instrument stability. Removing these features and other artifacts from the data is a vital process which affects the characteristics of the recovered astronomical structure we seek to study. In this paper, we explore two data reduction methods for data taken with the Submillimetre Common-User Bolometer Array-2 (SCUBA-2) at the James Clerk Maxwell Telescope (JCMT). The JCMT Legacy Reduction 1 (JCMT LR1) and The Gould Belt Legacy Survey Legacy Release 1 (GBS LR1) reduction both use the same software, Starlink, but differ in their choice of data reduction parameters. We find that the JCMT LR1 reduction is suitable for determining whether or not compact emission is present in a given region and the GBS LR1 reduction is tuned in a robust way to uncover more extended emission, which better serves more in-depth physical analyses of star-forming regions. Using the GBS LR1 method, we find that compact sources are recovered well, even at a peak brightness of only 3 times the noise, whereas the reconstruction of larger objects requires much care when drawing boundaries around the expected astronomical signal in the data reduction process. Incorrect boundaries can lead to false structure identification or it can cause structure to be missed. In the JCMT LR1 reduction, the extent of the true structure of objects larger than a point source is never fully recovered.
The Gaia Data Release 2 contains the 1st release of radial velocities complementing the kinematic data of a sample of about 7 million relatively bright, late-type stars. Aims: This paper provides a detailed description of the Gaia spectroscopic data processing pipeline, and of the approach adopted to derive the radial velocities presented in DR2. Methods: The pipeline must perform four main tasks: (i) clean and reduce the spectra observed with the Radial Velocity Spectrometer (RVS); (ii) calibrate the RVS instrument, including wavelength, straylight, line-spread function, bias non-uniformity, and photometric zeropoint; (iii) extract the radial velocities; and (iv) verify the accuracy and precision of the results. The radial velocity of a star is obtained through a fit of the RVS spectrum relative to an appropriate synthetic template spectrum. An additional task of the spectroscopic pipeline was to provide 1st-order estimates of the stellar atmospheric parameters required to select such template spectra. We describe the pipeline features and present the detailed calibration algorithms and software solutions we used to produce the radial velocities published in DR2. Results: The spectroscopic processing pipeline produced median radial velocities for Gaia stars with narrow-band near-IR magnitude Grvs < 12 (i.e. brighter than V~13). Stars identified as double-lined spectroscopic binaries were removed from the pipeline, while variable stars, single-lined, and non-detected double-lined spectroscopic binaries were treated as single stars. The scatter in radial velocity among different observations of a same star, also published in DR2, provides information about radial velocity variability. For the hottest (Teff > 7000 K) and coolest (Teff < 3500 K) stars, the accuracy and precision of the stellar parameter estimates are not sufficient to allow selection of appropriate templates. [Abridged]
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