Classification of New X-Ray Counterparts for Fermi Unassociated Gamma-Ray Sources Using the Swift X-Ray Telescope

被引:22
|
作者
Kaur, Amanpreet [1 ]
Falcone, Abraham D. [1 ]
Stroh, Michael D. [2 ]
Kennea, Jamie A. [1 ]
Ferrara, Elizabeth C. [3 ,4 ]
机构
[1] Penn State Univ, 525 Davey Lab, University Pk, PA 16802 USA
[2] Northwestern Univ, CIREA, Evanston, IL 60208 USA
[3] NASA, Goddard Space Flight Ctr, Code 916, Greenbelt, MD 20771 USA
[4] Univ Maryland, Dept Astron, College Pk, MD 20742 USA
来源
ASTROPHYSICAL JOURNAL | 2019年 / 887卷 / 01期
关键词
SKY;
D O I
10.3847/1538-4357/ab4ceb
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Approximately one-third of the gamma-ray sources in the third Fermi-LAT catalog are unidentified or unassociated with objects at other wavelengths. Observations with the X-Ray Telescope on the Neil Gehrels Swift Observatory (Swift-XRT) have yielded possible counterparts in similar to 30% of these source regions. The objective of this work is to identify the nature of these possible counterparts, utilizing their gamma-ray properties coupled with the Swift derived X-ray properties. The majority of the known sources in the Fermi catalogs are blazars, which constitute the bulk of the extragalactic gamma-ray source population. The galactic population on the other hand is dominated by pulsars. Overall, these two categories constitute the majority of all gamma-ray objects. Blazars and pulsars occupy different parameter space when X-ray fluxes are compared with various gamma-ray properties. In this work, we utilize the X-ray observations performed with the Swift-XRT for the unknown Fermi sources and compare their X-ray and gamma-ray properties to differentiate between the two source classes. We employ two machine-learning algorithms, decision tree and random forest (RF) classifier, to our high signal-to-noise ratio sample of 217 sources, each of which corresponds to Fermi unassociated regions. The accuracy scores for both methods were found to be 97% and 99%, respectively. The RF classifier, which is based on the application of a multitude of decision trees, associated a probability value (P-bzr) for each source to be a blazar. This yielded 173 blazar candidates from this source sample, with P-bzr >= 90% for each of these sources, and 134 of these possible blazar source associations had P-bzr >= 99%. The results yielded 13 sources with P-bzr <= 10%, which we deemed as reasonable candidates for pulsars, seven of which result with P-bzr <= 1%. There were 31 sources that exhibited intermediate probabilities and were termed ambiguous due to their unclear characterization as a pulsar or a blazar.
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页数:11
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