A Simple but Powerful Method to Reduce Background Noise in Celestial Gamma-Ray Images

被引：2

作者：

Kh., H. Hedayati ^{[1
]}

Soor, M. ^{[1
]}

Akhondi, F. ^{[1
]}

机构：

[1] KN Toosi Univ Technol, Dept Phys, POB 15875-4416, Tehran, Iran

来源：

ASTROPHYSICAL JOURNAL | 2024年 / 968卷 / 01期

关键词：

ALGORITHM; DBSCAN;

D O I：

10.3847/1538-4357/ad49a4

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

Reducing background noise is essential for clear data analysis and signal detection. In this study, we introduce a novel denoising algorithm tailored for gamma-ray astronomical data, utilizing local density sampling techniques. The proposed algorithm preferentially amplifies regions of high local density, which are indicative of potential sources, while diminishing the influence of low-density areas. This selective enhancement significantly bolsters the performance of clustering algorithms in pinpointing point sources, effectively minimizing the interference of high-density noise that could be mistaken for genuine sources. We have implemented this algorithm on Fermi Large Area Telescope data, and our results showcase a marked advancement in the clustering algorithm's capacity to discard false sources.

引用

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