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The Tianlai project is a 21cm intensity mapping experiment aimed at detecting dark energy by measuring the baryon acoustic oscillation (BAO) features in the large scale structure power spectrum. This experiment provides an opportunity to test the data processing methods for cosmological 21cm signal extraction, which is still a great challenge in current radio astronomy research. The 21cm signal is much weaker than the foregrounds and easily affected by the imperfections in the instrumental responses. Furthermore, processing the large volumes of interferometer data poses a practical challenge. We have developed a data processing pipeline software called {tt tlpipe} to process the drift scan survey data from the Tianlai experiment. It performs offline data processing tasks such as radio frequency interference (RFI) flagging, array calibration, binning, and map-making, etc. It also includes utility functions needed for the data analysis, such as data selection, transformation, visualization and others. A number of new algorithms are implemented, for example the eigenvector decomposition method for array calibration and the Tikhonov regularization for $m$-mode analysis. In this paper we describe the design and implementation of the {tt tlpipe} and illustrate its functions with some analysis of real data. Finally, we outline directions for future development of this publicly code.
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{Context}. The HIFI instrument on the Herschel Space Observatory performed over 9100 astronomical observations, almost 900 of which were calibration observations in the course of the nearly four-year Herschel mission. The data from each observation had to be converted from raw telemetry into calibrated products and were included in the Herschel Science Archive. {Aims}. The HIFI pipeline was designed to provide robust conversion from raw telemetry into calibrated data throughout all phases of the HIFI missions. Pre-launch laboratory testing was supported as were routine mission operations. {Methods}. A modular software design allowed components to be easily added, removed, amended and/or extended as the understanding of the HIFI data developed during and after mission operations. {Results}. The HIFI pipeline processed data from all HIFI observing modes within the Herschel automated processing environment as well as within an interactive environment. The same software can be used by the general astronomical community to reprocess any standard HIFI observation. The pipeline also recorded the consistency of processing results and provided automated quality reports. Many pipeline modules were in use since the HIFI pre-launch instrument level testing. {Conclusions}. Processing in steps facilitated data analysis to discover and address instrument artefacts and uncertainties. The availability of the same pipeline components from pre-launch throughout the mission made for well-understood, tested, and stable processing. A smooth transition from one phase to the next significantly enhanced processing reliability and robustness.
Processing of raw data from modern astronomical instruments is nowadays often carried out using dedicated software, so-called pipelines which are largely run in automated operation. In this paper we describe the data reduction pipeline of the Multi Unit Spectroscopic Explorer (MUSE) integral field spectrograph operated at ESOs Paranal observatory. This spectrograph is a complex machine: it records data of 1152 separate spatial elements on detectors in its 24 integral field units. Efficiently handling such data requires sophisticated software, a high degree of automation and parallelization. We describe the algorithms of all processing steps that operate on calibrations and science data in detail, and explain how the raw science data gets transformed into calibrated datacubes. We finally check the quality of selected procedures and output data products, and demonstrate that the pipeline provides datacubes ready for scientific analysis.
We describe the processing of the PHANGS-ALMA survey and present the PHANGS-ALMA pipeline, a public software package that processes calibrated interferometric and total power data into science-ready data products. PHANGS-ALMA is a large, high-resolution survey of CO J=2-1 emission from nearby galaxies. The observations combine ALMAs main 12-m array, the 7-m array, and total power observations and use mosaics of dozens to hundreds of individual pointings. We describe the processing of the u-v data, imaging and deconvolution, linear mosaicking, combining interferometer and total power data, noise estimation, masking, data product creation, and quality assurance. Our pipeline has a general design and can also be applied to VLA and ALMA observations of other spectral lines and continuum emission. We highlight our recipe for deconvolution of complex spectral line observations, which combines multiscale clean, single scale clean, and automatic mask generation in a way that appears robust and effective. We also emphasize our two-track approach to masking and data product creation. We construct one set of broadly masked data products, which have high completeness but significant contamination by noise, and another set of strictly masked data products, which have high confidence but exclude faint, low signal-to-noise emission. Our quality assurance tests, supported by simulations, demonstrate that 12-m+7-m deconvolved data recover a total flux that is significantly closer to the total power flux than the 7-m deconvolved data alone. In the appendices, we measure the stability of the ALMA total power calibration in PHANGS--ALMA and test the performance of popular short-spacing correction algorithms.
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 Chinese Spectral RadioHeliograph (CSRH) is a synthetic aperture radio interferometer built in Inner Mongolia, China. As a solar-dedicated interferometric array, CSRH is capable of producing high quality radio images at frequency range from 400 MHz to 15 GHz with high temporal, spatial, and spectral resolution.To implement high cadence imaging at wide-band and obtain more than 2 order higher multiple frequencies, the implementation of the data processing system for CSRH is a great challenge. It is urgent to build a pipeline for processing massive data of CSRH generated every day. In this paper, we develop a high performance distributed data processing pipeline (DDPP) built on the OpenCluster infrastructure for processing CSRH observational data including data storage, archiving, preprocessing, image reconstruction, deconvolution, and real-time monitoring. We comprehensively elaborate the system architecture of the pipeline and the implementation of each subsystem. The DDPP is automatic, robust, scalable and manageable. The processing performance under multi computers parallel and GPU hybrid system meets the requirements of CSRH data processing. The study presents an valuable reference for other radio telescopes especially aperture synthesis telescopes, and also gives an valuable contribution to the current and/or future data intensive astronomical observations.
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