| Project/Area Number |
11640241
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Astronomy
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| Research Institution | NATIONAL ASTRONOMICAL OBSERVATORY |
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Principal Investigator |
ICHIKAWA Shin-ichi National Astronomical Observatory, Associate Professor, 天文学データ解析計算センター, 助教授 (80211738)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHIDA Michitoshi National Astronomical Observatory, Research Associate, 岡山天体物理観測所, 助手 (90270446)
TOMITA Akihiko Wakayama University, Associate Professor, 教育学部, 助教授 (20294291)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | Optical / IR Astronomy / Data Analysis / Astronomical Image Processing / IRAF / CCD Data |
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| Research Abstract |
We studied high performance data analysis for large format astronomical data. We tried to find methods and enviroments suitable to quick extraction of astronomical information from raw image data.
We performed experiments of the first stage analysis, i.e. reduction process, which spends a lot of time with large amount of I/O.We use IRAF as the reduction software which is the most popular data reduction/analysis package in the Optical/IR astronomy. We found that the configuration and settings of magnetic disks, the efficiency and number of I/O buses, and quantity of main memory are critical factors for the process speed. These results will be a guideline of the system configuration for high performance data reduction.
We also examined several problems in the analysis of the data of Hubble Space telescope (HST), Sloan Digital Sky Survey (SDSS), Okayama Astrophyisical Observatory 188cm telescope, and Subaru Telescope. We investigate the combination with data arhcive systems, image browsers, and astronomical database, which promote data analysis. We discussed with many astronomers and reserchers of other fields on the future of data analysis.
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