FERMI Large Area Telescope and multi-wavelength observations of the flaring activity of PKS 1510-089 between 2008 september and 2009 june
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Citations
Parameter estimation in astronomy through application of the likelihood ratio. [satellite data analysis techniques
Kinematics of Parsec-scale Jets of Gamma-Ray Blazars at 43 GHz within the VLBA-BU-BLAZAR Program
The Structure and Emission Model of the Relativistic Jet in the Quasar 3C 279 Inferred from Radio to High-energy γ-Ray Observations in 2008-2010
Very Rapid High-Amplitude Gamma-ray Variability in Luminous Blazar PKS 1510-089 Studied with Fermi-LAT
Very Rapid High-amplitude Gamma-Ray Variability in Luminous Blazar PKS?1510?089 Studied with Fermi-LAT
References
Maps of Dust Infrared Emission for Use in Estimation of Reddening and Cosmic Microwave Background Radiation Foregrounds
Maps of Dust IR Emission for Use in Estimation of Reddening and CMBR Foregrounds
The relationship between infrared, optical, and ultraviolet extinction
Five-year wilkinson microwave anisotropy probe observations: cosmological interpretation
Five-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Cosmological Interpretation
Related Papers (5)
The Large Area Telescope on the Fermi Gamma-ray Space Telescope Mission
Probing the Inner Jet of the Quasar PKS 1510?089 with Multi-Waveband Monitoring During Strong Gamma-Ray Activity
Frequently Asked Questions (12)
Q2. What could be the cause of the lags in the light curve?
temporal lags could be related to the internal source photon absorption, to the cooling time of the radiating particles, or to inhomogeneities in the emitting region.
Q3. What is the UV peak in a quasar?
The UV peak, as in many quasars, is likely due to the BBB that usually is understood as thermal emission from the accretiondisk surrounding the BH.
Q4. What is the best-fit parameter for the LP model?
Due to the nonderivable character of the BPL law, the authors used also the loglikelihood profile method to determine the best-fit parameter for this model.
Q5. Why is the -ray luminosity smaller than other distant FSRQs?
Due to the low redshift of the source, the bolometric isotropic γ -ray luminosity is also smaller compared to other distant FSRQs observed by Fermi.
Q6. How is the source size calculated without beaming effects?
without beaming effects, the source size estimated from the observed variability timescale (Rrad = cΔt/(1 + z)) makes the source opaque to the photon–photon pair production process, provided that γ -ray and X-ray photons are produced cospatially.
Q7. How did the authors analyze the XRT data?
The authors analyzed XRT (Burrows et al. 2005; Gehrels et al. 2004) data using the xrtpipeline tool provided by the HEADAS v6.7 software package, for data observed in photon counting mode.
Q8. What is the correlation coefficient of the UV and ray fluxes?
The correlation coefficient of the logarithms of the UV and γ -ray fluxes, obtained through the Monte Carlo method described in Section 2.2.1, is r = 0.2 with a 95% confidence interval of 0.05 r 0.34.
Q9. What is the correlation coefficient of the optical and ray fluxes?
The correlation coefficient of the logarithm of the optical and γ -ray fluxes, evaluated through the Monte Carlo method described in Section 2.2.1, is r = 0.42 with a 95% confidence interval 0.36 r 0.46, higher than that found for the UV band.
Q10. Why do the authors prefer to present light curves in terms of F?
The authors prefer to present light curves in terms of νF (ν) to make easier the comparison between the various bands and the SED changes.
Q11. What is the way to compare the flux and photon index?
The plot of the flux in 0.3–10.0 keV range versus the photon index (see Figure 8) is compatible with a harder when brighter trend.
Q12. How is the MW SED compared to the fast variability estimate?
In this regard, the authors note that since the authors are describing flare-averaged states, with integration times of the order of a few weeks, the discrepancy with the fast variability estimate is not problematic.