主要内容:
早就想做一下这个的，但是不知道检测随机性的方法是否很复杂一直没做，终于有人做了。还想把将要看到的伽玛暴的时间或者的空间位置作为随机数发生器，不知道会不会将来有人做。
精彩摘抄:
文章信息:
-
- · arXiv e-print (arXiv:0806.3932)
- · References in the Article
- · Also-Read Articles (Reads History)
- ·
- · Translate This Page
| Title: |
| Testing the Randomness in the Sky-Distribution of Gamma-Ray Bursts |
| Authors: |
| Vavrek, R.; Balázs, L. G.; Mészáros, A.; Horváth, I.; Bagoly, Z. |
| Publication: |
| eprint arXiv:0806.3932 |
| Publication Date: |
| 06/2008 |
| Origin: |
| ARXIV |
| Keywords: |
| Astrophysics |
| Comment: |
| 17 pages, 4 figures, accepted for publication in MNRAS |
| Bibliographic Code: |
| 2008arXiv0806.3932V |
Abstract
We studied the complete randomness of the angular distribution of gamma-ray bursts (GRBs) detected by BATSE. Since GRBs seem to be a mixture of objects of different physical nature we divided the BATSE sample into 5 subsamples (short1, short2, intermediate, long1, long2) based on their durations and peak fluxes and studied the angular distributions separately. We used three methods, Voronoi tesselation, minimal spanning tree and multifractal spectra to search for non-randomness in the subsamples. To investigate the eventual non-randomness in the subsamples we defined 13 test-variables (9 from the Voronoi tesselation, 3 from the minimal spanning tree and one from the multifractal spectrum). Assuming that the point patterns obtained from the BATSE subsamples are fully random we made Monte Carlo simulations taking into account the BATSE's sky-exposure function. The MC simulations enabled us to test the null hypothesis i.e. that the angular distributions are fully random. We tested the randomness by binomial test and introducing squared Euclidean distances in the parameter space of the test-variables. We concluded that the short1, short2 groups deviate significantly (99.90%, 99.98%) from the fully randomness in the distribution of the squared Euclidean distances but it is not the case at the long samples. At the intermediate group the squared Euclidean distances also give significant deviation (98.51%).
没有评论:
发表评论