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Big Data in Astronomy
Scientific Data Processing for Advanced Radio Telescopes
Presents insights into big data processing related architectures, designs and models for astronomical applications, bridging the gap between data science and astronomical research
Linghe Kong (Edited by), Tian Huang (Edited by), Yongxin Zhu (Edited by), Shenghua Yu (Edited by)
9780128190845, Elsevier Science
Paperback, published 16 June 2020
438 pages, Approx. 120 illustrations
23.4 x 19 x 2.8 cm, 0.88 kg
Big Data in Radio Astronomy: Scientific Data Processing for Advanced Radio Telescopes provides the latest research developments in big data methods and techniques for radio astronomy. Providing examples from such projects as the Square Kilometer Array (SKA), the world’s largest radio telescope that generates over an Exabyte of data every day, the book offers solutions for coping with the challenges and opportunities presented by the exponential growth of astronomical data. Presenting state-of-the-art results and research, this book is a timely reference for both practitioners and researchers working in radio astronomy, as well as students looking for a basic understanding of big data in astronomy.
Part A: Fundamentals Chapter 1: Introduction of Radio Astronomy Chapter 2: Fundamentals of Big Data in Radio Astronomy Part B: Big Data Processing Chapter 3: Pre-processing Pipeline on FPGA Chapter 4: Real-time stream processing in radio astronomy Chapter 5: Digitization, Channelization and Packeting Chapter 6: Processing Data of Correlation on GPU Chapter 7: Data Calibration for single dish radio telescope Chapter 8: Imaging Algorithm Optimization for Scale-out Processing Part C: Computing Technologies Chapter 9: Execution Framework Technology Chapter 10: Application Design For Execution Framework Chapter 11: Heterogeneous Computing Platform for Backend Computing Tasks Chapter 12: High Performance Computing for Astronomical Big Data Chapter 13: Spark and Dask Performance Analysis Based on ARL Image Library Chapter 14: Applications of Artificial Intelligence in Astrnomical Big Data Part D: Future Developments Chapter 15: Mapping the Universe with 21cm Observations
Subject Areas: Enterprise software [UFL], Information technology: general issues [UB], Space science [TTD], Earth sciences [RB], Astronomical observation: observatories, equipment & methods [PGG], Theoretical & mathematical astronomy [PGC], Astronomy, space & time [PG]
