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تسجيل مستخدم جديدConstruction of the Variability -> Luminosity Estimator
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Daniel E. Reichart
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We present a possible Cepheid-like luminosity estimator for the long-duration gamma-ray bursts based on the variability of their light curves.
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We present a possible Cepheid-like luminosity estimator for the long-duration gamma-ray bursts based on the variability of their light curves. We also present a preliminary application of this luminosity estimator to 907 long-duration bursts from the BATSE catalog.
The relationship between variability, luminosity and redshift in the South Galactic Pole QSO sample is examined in an effort to disentangle the effects of luminosity and redshift in the amplitude of the optical variations. The anticorrelation between
variability and luminosity found by other authors is confirmed. Our analysis also supports claims that variability increases with redshift, most likely due to an anticorrelation between variability and wavelength. In particular, our parametric fits show that the QSO variability-wavelength relation is consistent with that observed in low-luminosity nearby active galactic nuclei. The results are used to constrain Poissonian-type models. We find that if QSO variability results from a random superposition of pulses, then the individual events must have B-band energies between $sim 10^{50}$ and a few times $10^{51}$ erg and time-scales of $sim 2$ yr. Generalized Poissonian models in which the pulse energy and lifetime scale with luminosity are also discussed.
From a sample of 32 GRBs with known redshift (Guidorzi et al. 2005) and then a sample of 551 BATSE GRBs with derived pseudo-redshift (Guidorzi 2005), the time variability/peak luminosity correlation (V vs. L) found by Reichart et al. (2001) was teste
d. For both samples the correlation is still found but less relevant due to a much higher spread of the data. Assuming a straight line in the logL-logV plane (logL = m logV + b), as done by Reichart et al., the slope was found lower than that derived by Reichart et al.: m = 1.3_{-0.4}^{+0.8} (Guidorzi et al. 2005), m = 0.85 +- 0.02 (Guidorzi 2005), to be compared with m = 3.3^{+1.1}_{-0.9} (Reichart et al. 2001). Reichart & Nysewander (2005) attribute the different slope to the fact we do not take into account in the fit the variance of the sample, and demonstrate that, using the method by Reichart (2001), the data set of Guidorzi et al. (2005) in logL-logV plane is still well described with slope m = 3.4^{+0.9}_{-0.6}. Here we compare the results of two methods accounting for the variance of the sample, that implemented by Reichart (2001) and that by DAgostini (2005). We demonstrate that the method by Reichart (2001) provides an inconsistent estimate of the slope when the sample variance is comparable with the interval of values covered by the variability. We also show that, using the DAgostini method, the slope is consistent with that derived by us earlier and inconsistent with that derived by Reichart & Nysewander (2005). Finally we discuss the implications on the interpretations and show that our results are in agreement with the peak energy/variability correlation found by Lloyd-Ronning & Ramirez-Ruiz (2002) and the peak energy/peak luminosity correlation (Yonetoku et al. 2004; Ghirlanda et al. 2005) [abridged].
We present a possible Cepheid-like luminosity estimator for the long gamma-ray bursts based on the variability of their light curves. To construct the luminosity estimator, we use CGRO/BATSE data for 13 bursts, Wind/KONUS data for 5 bursts, Ulysses/G
RB data for 1 burst, and NEAR/XGRS data for 1 burst. Spectroscopic redshifts, peak fluxes, and high resolution light curves are available for 11 of these bursts; partial information is available for the remaining 9 bursts. We find that the isotropic-equivalent luminosities L of these bursts positively correlate with a rigorously-constructed measure V of the variability of their light curves. We fit a model to these data that accommodates both intrinsic scatter (statistical variance) and extrinsic scatter (sample variance). If one excludes GRB 980425 from the fit on the grounds that its association with SN 1998bw at a redshift of z = 0.0085 is not secure, the luminosity estimator spans approx. 2.5 orders of magnitude in L, and the slope of the correlation between L and V is positive with a probability of 1 - 1.4 x 10^-4 (3.8 sigma). Although GRB 980425 is excluded from this fit, its L and V values are consistent with the fitted model, which suggests that GRB 980425 may well be associated with SN 1998bw, and that GRB 980425 and the cosmological bursts may share a common physical origin. If one includes GRB 980425 in the fit, the luminosity estimator spans approx. 6.3 orders of magnitude in L, and the slope of the correlation is positive with a probability of 1 - 9.3 x 10^-7 (4.9 sigma). Independently of whether or not GRB 980425 should be included in the fit, its light curve is unique in that it is much less variable than the other approx. 17 light curves in our sample for which the signal-to-noise is reasonably good.
Low Luminosity Active Galactic Nuclei (LLAGNs) are contaminated by the light of their host galaxies, thus they cannot be detected by the usual colour techniques. For this reason their evolution in cosmic time is poorly known. Variability is a propert
y shared by virtually all active galactic nuclei, and it was adopted as a criterion to select them using multi epoch surveys. Here we report on two variability surveys in different sky areas, the Selected Area 57 and the Chandra Deep Field South.
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