Big Data in Astronomy
Scientific Data Processing for Advanced Radio Telescopes
- 1st Edition - June 13, 2020
- Editors: Linghe Kong, Tian Huang, Yongxin Zhu, Shenghua Yu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 1 9 0 8 4 - 5
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 1 9 0 8 5 - 2
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 ast… Read more
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Request a sales quoteBig 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.
- Bridges the gap between radio astronomy and computer science
- Includes coverage of the observation lifecycle as well as data collection, processing and analysis
- Presents state-of-the-art research and techniques in big data related to radio astronomy
- Utilizes real-world examples, such as Square Kilometer Array (SKA) and Five-hundred-meter Aperture Spherical radio Telescope (FAST)
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
- No. of pages: 438
- Language: English
- Edition: 1
- Published: June 13, 2020
- Imprint: Elsevier
- Paperback ISBN: 9780128190845
- eBook ISBN: 9780128190852
LK
Linghe Kong
TH
Tian Huang
YZ
Yongxin Zhu
SY