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Register a new userThe Herschel Data Processing System - HIPE and Pipelines - Up and Running Since the Start of the Mission
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The Herschel Space Observatory is the fourth cornerstone mission in the ESA science programme and performs photometry and spectroscopy in the 55 - 672 micron range. The development of the Herschel Data Processing System started in 2002 to support the data analysis for Instrument Level Tests. The Herschel Data Processing System was used for the pre-flight characterisation of the instruments, and during various ground segment test campaigns. Following the successful launch of Herschel 14th of May 2009 the Herschel Data Processing System demonstrated its maturity when the first PACS preview observation of M51 was processed within 30 minutes of reception of the first science data after launch. Also the first HIFI observations on DR21 were successfully reduced to high quality spectra, followed by SPIRE observations on M66 and M74. A fast turn-around cycle between data retrieval and the production of science-ready products was demonstrated during the Herschel Science Demonstration Phase Initial Results Workshop held 7 months after launch, which is a clear proof that the system has reached a good level of maturity. We will summarise the scope, the management and development methodology of the Herschel Data Processing system, present some key software elements and give an overview about the current status and future development milestones.
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The Herschel Interactive Processing Environment (HIPE) was developed by the European Space Agency (ESA) in collaboration with NASA and the Herschel Instrument Control Centres to provide the astronomical community a complete environment to process and analyze the data gathered by the Herschel Space Observatory. One of the most important components of HIPE is the plotting system (named PlotXY) that we present here. With PlotXY it is possible to produce easily high quality publication ready 2D plots. It provides a long list of features, with fully configurable components, and interactive zooming. The entire code of HIPE is written in Java and is open source released under the GNU Lesser General Public License version 3. A new version of PlotXY is being developed to be independent from the HIPE code base; it is available to the software development community for the inclusion in other projects at the URL http://code.google.com/p/jplot2d/.
The Large Observatory for X-ray Timing (LOFT) is one of the five mission candidates that were considered by ESA for an M3 mission (with a launch opportunity in 2022 - 2024). LOFT features two instruments: the Large Area Detector (LAD) and the Wide Field Monitor (WFM). The LAD is a 10 m 2 -class instrument with approximately 15 times the collecting area of the largest timing mission so far (RXTE) for the first time combined with CCD-class spectral resolution. The WFM will continuously monitor the sky and recognise changes in source states, detect transient and bursting phenomena and will allow the mission to respond to this. Observing the brightest X-ray sources with the effective area of the LAD leads to enormous data rates that need to be processed on several levels, filtered and compressed in real-time already on board. The WFM data processing on the other hand puts rather low constraints on the data rate but requires algorithms to find the photon interaction location on the detector and then to deconvolve the detector image in order to obtain the sky coordinates of observed transient sources. In the following, we want to give an overview of the data handling concepts that were developed during the study phase.
GWAC will have been built an integrated FOV of 5,000 $degree^2$ and have already built 1,800 square $degree^2$. The limit magnitude of a 10-second exposure image in the moonless night is 16R. In each observation night, GWAC produces about 0.7TB of raw data, and the data processing pipeline generates millions of single frame alerts. We describe the GWAC Data Processing and Management System (GPMS), including hardware architecture, database, detection-filtering-validation of transient candidates, data archiving, and user interfaces for the check of transient and the monitor of the system. GPMS combines general technology and software in astronomy and computer field, and use some advanced technologies such as deep learning. Practical results show that GPMS can fully meet the scientific data processing requirement of GWAC. It can online accomplish the detection, filtering and validation of millions of transient candidates, and feedback the final results to the astronomer in real-time. During the observation from October of 2018 to December of 2019, we have already found 102 transients.
The HIFI data processing pipeline was developed to systematically process diagnostic, calibration and astronomical observations taken with the HIFI science instrumentas part of the Herschel mission. The HIFI pipeline processed data from all HIFI observing modes within the Herschel automated processing environment, as well as, within an interactive environment. A common software framework was developed to best support the use cases required by the instrument teams and by the general astronomers. The HIFI pipeline was built on top of that and was designed with a high degree of modularity. This modular design provided the necessary flexibility and extensibility to deal with the complexity of batch-processing eighteen different observing modes, to support the astronomers in the interactive analysis and to cope with adjustments necessary to improve the pipeline and the quality of the end-products. This approach to the software development and data processing effort was arrived at by coalescing the lessons learned from similar research based projects with the understanding that a degree of foresight was required given the overall length of the project. In this article, both the successes and challenges of the HIFI software development process are presented. To support future similar projects and retain experience gained lessons learned are extracted.
The Large Synoptic Survey Telescope (LSST) is an ambitious astronomical survey with a similarly ambitious Data Management component. Data Management for LSST includes processing on both nightly and yearly cadences to generate transient alerts, deep catalogs of the static sky, and forced photometry light-curves for billions of objects at hundreds of epochs, spanning at least a decade. The algorithms running in these pipelines are individually sophisticated and interact in subtle ways. This paper provides an overview of those pipelines, focusing more on those interactions than the details of any individual algorithm.
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