AR_final file_2018-19

Explorer/Proportional Counter Array data during the 2004, 2008 and 2011 outbursts. This suggests the possibility of this phenomenon being related to the elliptical binary orbit of the Be/X-ray pul- sar. There are ∼ 225 known X-ray pulsars, among them only ∼ 9 transient X-ray binary pulsars in- cluding 4U 0115+63, show milliHertz oscillations. These type of oscillations are observed from other X-ray binary sources like black hole and neutron star binaries. The quasi-periodicity timescale is in- dependent of the accretor and depends on accretion and physical parameters of the binary system that are distinct from other smaller-timescale QPOs ob- served from this and other binary systems. Evolution of magnetars Vikram Soni, Dipankar Bhattacharya and col- laborators have examined the evolution of magne- tars in a model where an ultra-strong magnetic field is generated in the core of a massive neutron star due to a spin-alignment phase transition, which eventually emerges at the surface aided by ambipo- lar diffusion. A characteristic dependence of the ra- tio of spin-down luminosity and X-ray luminosity on the spin period of the neutron star is predicted, which can be used to verify this model once a large sample of magnetars can be studied. Study on temporal and spectral be- haviour of 3C 279 Blazars are a special class of active galactic nu- clei (AGN) with powerful relativistic jets of plasma pointing close to the line of sight of the observer. This close pointing of the jet towards the observer results in extreme properties in the blazar emis- sion, viz. rapid variability, non-thermal emission extending from radio to GeV energy, highly po- larized emission in the optical and radio bands of spectrum, typical double humped spectral en- ergy distribution shape, etc. Based on the pres- ence/absence of strong emission line features in their optical spectrum, blazars are classified into flat spectrum radio quasars (FSRQs) and BL Lacs. Zahir Shah , V. Jithesh , Sunder Sahayanathan, Ranjeev Misra , and Naseer Iqbal Bhat have car- ried out a detailed investigation of the temporal and spectral behaviour of the recent January, 2018 flaring event from FSRQ 3C 279 by using the multi- wavelength observations from Swift-XRT, Swift- UVOT and Fermi-LAT. Based on the temporal analysis of the γ -ray light curve, they found a lag of ∼ 1 d between the low energy (0.1–3 GeV) and high energy (3–5 GeV) γ -ray emission. Additionally, they found that the γ -ray light curve shows asym- metric behaviour with slow rise-fast decay in the en- ergy band 0.1–3 GeV and fast rise–slow decay in the 3–500 GeV band. They interpret the asymmetry as a result of a shift in the Compton spectral peak, which is supported by correlation studies between the flux and the parameters of the log-parabola fit to the source spectra in the energy range 0.1–500 GeV. Also the flux correlates well with the peak spectral energy, and the log-parabola fit parame- ters show a harder spectrum with large curvature at high flux states. During January 27 - 28, 2018, significant enhancement in the very high-energy γ - ray emission (VHE) was also detected from 3C 279 by the HESS. However, Fermi γ -ray light curve did not show substantial flux enhancement during the VHE flaring period. Interestingly, they found the hardest γ -ray spectrum with large curvature to be synchronous with VHE flare. Their study of the spectral behaviour of the source suggests that the γ -ray emission is most likely to be associated with the Compton up-scattering of IR photons from the dusty environment. Moreover, based on the spec- tral energy distribution (SED) fit parameters, they showed that the increase in bulk Lorentz factor of emission region is a dominant cause for the flux enhancement. (See Figure 13). Statistical study of simulated flux dis- tributions Zahir Shah , Ranjeev Misra and Atreyee Sinha have carried out a detailed statistical study of simu- lated flux distributions. There is considerable long- term observational evidence that the high energy light curves of blazars follow a log-normal flux dis- tribution. Based on the simulation, they quantita- tively identify the minimum number of flux points needed in the distribution in order to reject the nor- ( 77 )