3 citations · 5 across the 9 of their papers we have counts for
9 papers
A NuSTAR Reflection-Spectroscopy Survey of Cygnus X-1
Kshitij Duraphe, Kartik Mandar, Chooda Khanal +1
Relativistic-reflection measurements of Cygnus X-1 disagree on the extent of disk truncation and commonly infer supersolar iron abundances. We analyze a selected sample of 26 archi…
NICER Perspective on TeV Blazar Mrk~421: X-ray Variability and Particle Acceleration
Sangeetha Kizhakkekalam, Gopal Bhatta, Navaneeth P K +1
Mrk~421 is one of the most fascinating blazars, widely studied across the electromagnetic spectrum using observations at various wavebands, from radio to the TeV gamma ray bands. W…
Transitional Spectral Behavior in Blazar OJ 287: A Comprehensive Multi-Epoch SED Study
Navaneeth P K, Gopal Bhatta, Sangeetha Kizhakkekalam
We present a comprehensive multi-wavelength investigation of BL Lac object OJ 287 using Swift and Fermi observatories spanning 2008-2025. The source exhibits significant flux varia…
State-Dependent X-ray Variability in Cygnus X-1: A 12-Year NuSTAR Timing Study of Accretion Flow Geometry
Kshitij Duraphe, Kartik Mandar, Chooda Khanal +6
We present a comprehensive timing analysis of the black hole X-ray binary Cygnus X-1 using 26 NuSTAR observations spanning 2012-2024, providing the most detailed characterization t…
Deterministic and Stochastic Study of the X-ray Emission from the TeV Blazar Mrk~421
Radim Pánis, Gopal Bhatta, Tek P. Adhikari +6
We present a comprehensive timing analysis of X-ray data from the {\it XMM-Newton} satellite, examining 50 light curves covering 17 years of observations of the blazar Mrk~421. Thi…
Optical intraday variability analysis for the BL Lacertae object 1ES 1426+42.8
X. Chang, D. R. Xiong, T. F. Yi +4
The observation data of blazar 1ES 1426 + 42.8 were obtained using the 1.02 m optical telescope of Yunnan Observatories during to . Intraday variability (IDV) is detec…
Gamma Ray AGNs: Estimating Redshifts and Blazar Classification using traditional Neural Networks with smart initialization and self-supervised learning
Sarvesh Gharat, Abhimanyu Borthakur, Gopal Bhatta
Redshift estimation and the classification of gamma-ray AGNs represent crucial challenges in the field of gamma-ray astronomy. Recent efforts have been made to tackle these problem…
Gamma-ray Blazar Classification using Machine Learning with Advanced Weight Initialization and Self-Supervised Learning Techniques
Gopal Bhatta, Sarvesh Gharat, Abhimanyu Borthakur +1
Machine learning has emerged as a powerful tool in the field of gamma-ray astrophysics. The algorithms can distinguish between different source types, such as blazars and pulsars,…
Estimation of redshift and associated uncertainty of Fermi/LAT extra-galactic sources with Deep Learning
Sarvesh Gharat, Abhimanyu Borthakur, Gopal Bhatta
With the advancement of technology, machine learning-based analytical methods have pervaded nearly every discipline in modern studies. Particularly, a number of methods have been e…