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Title Big data in astronomy : scientific data processing for advanced radio telescopes / edited by Linghe Kong, Tian Huang, Yongxin Zhu, Shenghua Yu
Published Amsterdam, Netherlands : Elsevier, [2020]
©2020

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Description 1 online resource (xv, 422 pages) : illustrations
Contents Intro -- Big Data in Astronomy: Scientific Data Processing for Advanced Radio Telescopes -- Copyright -- Contents -- Contributors -- Preface -- Acknowledgments -- Part A: Fundamentals -- Chapter 1: Introduction to radio astronomy -- 1. The history of astronomy -- 1.1. Ancient astronomy -- 1.2. Astronomy from the mid-16th century to the mid-19th century -- 1.3. Astronomy since the mid-19th century -- 2. What is radio astronomy -- 2.1. How does radio astronomy occur -- 2.2. The radio stars, quasars, and black holes -- 2.2.1. The strongest radio source, Cygnus A, in the sky
2.2.2. The discovery of cliff allergens and radio galaxies -- 2.2.3. Nonthermal radiation -- 2.2.4. Synchronous radiation -- 2.2.5. Synchrotron radiation pattern -- 2.2.6. Connect nonthermal radiation and cosmic rays -- 2.2.7. Astrophysics of cosmic rays -- 2.2.8. Discovery of quasars -- 2.3. The radio astronomy instrument: Radio telescope -- 2.4. Some achievements of radio astronomy -- 2.5. Astronomical research nowadays -- 3. Advanced radio telescope -- 3.1. The square kilometer array (SKA) -- 3.2. Fast -- 4. The challenge of radio astronomy -- 4.1. System noise
4.2. Antennas and collecting area -- 4.3. Data transmission -- 5. The development tendency of radio astronomy -- 5.1. Mid-frequency aperture arrays -- 5.2. Entering a near future -- References -- Chapter 2: Fundamentals of big data in radio astronomy -- 1. Big data and astronomy -- 1.1. Background of big data -- 1.2. Definitions and features of big data -- 1.3. Development of big data -- 1.4. Big data in astronomy -- 1.5. Statistical challenges in astronomy -- 2. Increasing data volumes of telescopes -- 2.1. Sloan digital sky survey -- 2.2. Visible and infrared survey telescope for astronomy
2.3. Large synoptic survey telescope -- 2.4. Thirty meter telescope -- 3. Existing methods for the value chain of big data -- 3.1. Data generation -- 3.2. Data acquisition -- 3.3. Data storage -- 3.4. Data analysis -- 3.4.1. Traditional data analysis methods -- 3.4.2. Big data analytic methods -- 3.4.3. Architecture for big data analysis -- 4. Current statistical methods for astronomical data analysis -- 4.1. Nonparametric statistics -- 4.2. Data smoothing -- 4.3. Multivariate clustering and classification -- 4.4. Nondetections and truncation -- 4.5. Spatial point processes
5. Platforms for big data processing -- 5.1. Horizontal scaling platforms -- 5.2. Vertical scaling platforms -- 5.2.1. High performance computing (HPC) clusters -- 5.2.2. Multicore CPU -- 5.2.3. Graphics processing unit (GPU) -- 5.2.4. Field programmable gate arrays (FPGA) -- References -- Part B: Big data processing -- Chapter 3: Preprocessing pipeline on FPGA -- 1. FPGA interface for ADC -- 1.1. ADC interleaving -- 1.2. Bit alignment -- 1.3. Stream deserialization -- 2. FIR filtering -- 2.1. Leakage -- 2.2. Scalloping loss -- 2.3. Polyphase filter -- 3. Time-frequency domain transposing -- 3.1. Real-valued FFT
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (viewed August 30, 2021)
Subject Radio astronomy -- Data processing
Big data.
Big data
Form Electronic book
Author Kong, Linghe (Computer scientist) editor
Huang, Tian (Computer scientist) editor
Zhu, Yongxin (Computer scientist) editor
Yu, Shenghua, editor
ISBN 9780128190852
012819085X