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As current- and next-generation astronomical instruments come online, they will generate an unprecedented deluge of data. Analyzing these data in real time presents unique conceptual and computational challenges, and their long-term storage and archiving is scientifically essential for generating reliable, reproducible results. We present here the real-time processing (RTP) system for the Hydrogen Epoch of Reionization Array (HERA), a radio interferometer endeavoring to provide the first detection of the highly redshifted 21 cm signal from Cosmic Dawn and the Epoch of Reionization by an interferometer. The RTP system consists of analysis routines run on raw data shortly after they are acquired, such as calibration and detection of radio-frequency interference (RFI) events. RTP works closely with the Librarian, the HERA data storage and transfer manager which automatically ingests data and transfers copies to other clusters for post-processing analysis. Both the RTP system and the Librarian are public and open source software, which allows for them to be modified for use in other scientific collaborations. When fully constructed, HERA is projected to generate over 50 terabytes (TB) of data each night, and the RTP system enables the successful scientific analysis of these data.
A major challenge in modern radio astronomy is dealing with the massive data volumes generated by wide-bandwidth receivers. Such massive data rates are often too great for a single device to cope, and so processing must be split across multiple devic
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Most planetary radar applications require recording of complex voltages at sampling rates of up to 20 MHz. I describe the design and implementation of a sampling system that has been installed at the Arecibo Observatory, Goldstone Solar System Radar,
Modern advances in space technology have enabled the capture and recording of unprecedented volumes of data. In the field of solar physics this is most readily apparent with the advent of the Solar Dynamics Observatory (SDO), which returns in excess
At the Canadian Astronomy Data Centre, we have combined our cloud computing system, CANFAR, with the worlds most advanced machine learning software, Skytree, to create the worlds first cloud computing system for data mining in astronomy. CANFAR provi