| 摘要(英) |
Studies of asteroids have become more and more important since they are believed to help astronomical scientists to know the early evolution of the solar system. While the number of asteroids detected has grown numerously in recent years due to the significant improvement of photometry techniques, the detection of faint asteroids are still hard to achieve. In 2014, a method called Synthetic Tracking was brought up, which greatly enhances the performance of faint asteroids detection. Since it requires large-scale of workloads and costs plenty of time, we propose a new computing architecture to increase the performance.
Combining Synthetic Tracking with FIND algorithm in DAOPHOT software tool, our architecture shift-and-add simulated astronomical images to enhance signals of faint asteroids and detect their accurate velocities and locations. The system is established on distributed platform with GPU equipped, which largely speed up the performance of image processing.
Result shows that the accuracy of velocity detected is very high with 10-2 pixel per frame; the error of location is 2 pixels in average. For performance, the shift-and-add process saves 88% of time with GPU; the FIND algorithm saves 81% of time with help of Apache Spark. The total performance is enhanced 77% in average. |
| 參考文獻 |
[1] NASA JPL Center for Near Earth Object Studies. Available: https://cneos.jpl.nasa.gov/
[2] Shao, M. et al., “Finding Very Small Near-Earth Asteroids Using Synthetic Tracking”, The Astrophysical Journal, 782:1(10pp), February 2014
[3] Zhai, C. et al., “Detection of A Faint Fast-Moving Near-Earth Asteroid Using the Synthetic Tracking Technique”, The Astrophysical Journal, 792:60(14pp), September 2014
[4] Harding, L. K. et al., “CHIMERA: a wide-field, multi-colour, high-speed photometer at the prime focus of the Hale telescope”, Monthly Notices of the Royal Astronomical Society, Vol. 457, Issue 3, pp. 3036-3049, April 2016
[5] Zhai, C. et al., “Synthetic Tracking Using ZTF Deep Drilling Data Sets”, The Astronomical Society of the Pacific, 132:064502 (8pp), June 2020
[6] Stetson, P. B., “DAOPHOT: A COMPUTER PROGRAM FOR CROWDED-FIELD”, The Astronomical Society of the Pacific, Vol. 99, 191-222, March 1987
[7] Pérez, R. H. et al. (2016) “Improving Performance of DAOPHOT-FIND by Using GPU Architecture.”, ISUM 2015: High Performance Computer Applications, 240-249, Mexico City, Mexico, March 2015
[8] Apache Hadoop Official Website. Available: https://hadoop.apache.org/.
[9] Apache Spark Official Website. Available: http://spark.apache.org/
[10] Ester, M. et al., “A density-based algorithm for discovering clusters in large spatial databases with noise”, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), AAAI Press. pp. 226–231., August 1996 |
[Endnote RIS 格式]
[相關文章]
[文章引用]
[完整記錄]
[館藏目錄]
[檢視]
plurk
funp
live
udn
HD
myshare
netvibes
friend
youpush
delicious
baidu
Google bookmarks
del.icio.us
hemidemi
facebook
twitter
google
reddit