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Titlebook: Data-Intensive Radio Astronomy; Bringing Astrophysic Eleni Vardoulaki,Marta Dembska,Matthias Hoeft Book 2024 The Editor(s) (if applicable)

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樓主: Defect
21#
發(fā)表于 2025-3-25 07:19:51 | 只看該作者
22#
發(fā)表于 2025-3-25 08:55:54 | 只看該作者
nd give a short introduction to radio astronomy. Additionally, we present current and upcoming radio observatories around the world and their specifications. Finally, we introduce the concept of data-intensive radio astronomy and of the data lifecycle.
23#
發(fā)表于 2025-3-25 15:28:08 | 只看該作者
24#
發(fā)表于 2025-3-25 17:06:55 | 只看該作者
25#
發(fā)表于 2025-3-25 23:14:19 | 只看該作者
Friedrich H. Bruns,Hans Reinauerrsatility to learn complex representations and shapes of radio signals. We highlight how dimensionality reduction, anomaly detection and uncertainty estimation based on machine learning controls the quality, robustness and understanding of AI-derived radio astronomical results.
26#
發(fā)表于 2025-3-26 00:30:54 | 只看該作者
27#
發(fā)表于 2025-3-26 05:09:08 | 只看該作者
28#
發(fā)表于 2025-3-26 11:34:47 | 只看該作者
Computing Infrastructureproducibility. Finally, we conclude by providing an overview on how some recent yet widely adopted cloud-native technologies, as last-generation container orchestrators, can converge together with HPC-specific ones towards higher-level, unified frameworks.
29#
發(fā)表于 2025-3-26 14:21:35 | 只看該作者
Other Types of Source Extraction and Identificationg facilities like the Square Kilometer Array. In this chapter we discuss the commonly used extraction methods of other information like spectral lines (only if within the bandwidth), polarisation (if emission is polarised), and time domain properties (if the source has time variation, e.g. in case of pulsars or fast radio bursts).
30#
發(fā)表于 2025-3-26 19:56:56 | 只看該作者
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