Ke-Yin Chen

ORCID: 0000-0003-0712-2847
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Research Areas
  • Astrophysics and Cosmic Phenomena
  • Radio Astronomy Observations and Technology
  • Computational Physics and Python Applications

Guangzhou University
2022

In this work, the support vector machine (SVM) method is adopted to separate BL Lacertae objects (BL Lacs) and flat spectrum radio quasars (FSRQs) in plots of photon index against flux, αph∼logF, those variability index, αph∼logVI logVI∼logF. Then, we used dividing lines distinguish Lacs from FSRQs blazar candidates uncertain types Fermi/LAT catalogue. Our main conclusions are: 1. We by αph=−0.123logF+1.170 αph∼logF plot, αph=−0.161logVI+2.594 plot logVI=0.792logF+9.203 logVI∼logF plot. 2....

10.3390/universe8080436 article EN cc-by Universe 2022-08-22
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