Lajos G. Balazs

Estimation of the Redshifts for Long Gamma‐Ray Bursts

It is known that the soft tail of gamma‐ray bursts’ spectra show excesses from the exact power‐law dependence. In this article we show that this departure can be detected in the peak flux ratios of different BATSE DISCSC energy channels. This effect allows us to estimate the redshifts of bright long gamma‐ray bursts given in the BATSE Catalog. For the 8 gamma‐ray bursts, which have both BATSE DISCSC data and measured optical spectroscopic redshifts, the correlation between the true and estimated redshifts is remarkable, and the average error is Δz ≈ 0.5. The method is similar to the photometric redshift estimation of galaxies in the optical range, hence we call it “gamma photometric redshift estimation”. These redshifts for the remaining 857 long bright gamma‐ray bursts are are up to z ≃ (4 – 7). For the the faint long bursts — which should be up to z ≃ 20 — the redshifts hardly can be determined unambiguously from this method.

THE AKARI FIS CATALOGUE OF YSOS AND EXTRAGALACTIC OBJECTS

The point sources in the Bright Source Catalogue of the AKARI Far-Infrared Surveyor (FIS) were classified based on their FIR and mid-IR fluxes and colours into young stellar object (YSO) and extragalactic source types using Quadratic Discriminant Analysis method (QDA) and Support Vector Machines (SVM). The reliability of the selection of YSO candidates is high, and the number of known YSO candidates were increased significantly, that we demonstrate in the case of the nearby open cluster IC348. Our results show that we can separate galactic and extragalactic AKARI point sources in the multidimensional space of FIR fluxes and colours with high reliability, however, differentiating among the extragalactic sub-types needs further information.

Spectral classification and variation of Fermi GRBs

The Fermi GBM catalog contains general physical quantities of the observed objects and also estimated parameters (peak energy, spectral indices, intensity) from four fitted spectral models (Band, smoothly broken power law, Comptonized, power law) for the peak flux and the fluence. We studied the nature of the errors of the peak flux, the fluence, and duration parameters. We have found a linear correlation between the logarithm of the measured quantities and their error bars. We interpret our results as an indication that the peak flux, fluence and duration follow a Poissonic distribution.

Cosmology and the subclasses of the gamma-ray bursts

Several statistical studies done also by the authors of this contribution show that there are three subclasses of gamma-ray bursts. They can be called as short, intermediate and long ones, because they can be separated with respect to their durations. The short and intermediate bursts are distributed anisotropically on the sky. This behavior is highly remarkable, and can have a cardinal impact on the cosmology. The subject of this contribution is a survey of this topic.

An Observational Evidence for the Difference Between the Short and Long Gamma‐Ray Bursts

The intrinsic fluence and duration distributions of gamma‐ray bursts are well represented by log‐normal distributions. This allows a bivariate log‐normal distribution fit to be made to the BATSE short and long bursts separately. A statistically significant difference between the long and short groups is found. We argue that the effect is probably real. Applying the Cramer’s theorem these results lead to some predictions for models of long and short bursts.

Testing the intrinsic randomness in the angular distributions of gamma-ray bursts

The counts-in-cells and the two-point angular correlation function method are used to test the randomness in the angular distributions of both the all gamma-ray bursts collected in the BATSE Catalog, and also their three subclasses (“short,” “intermediate,” “long”). The methods eliminate the non-zero sky-exposure function of BATSE instrument. Both tests suggest intrinsic non-randomness for the intermediate subclass; for the remaining three cases we use only the correlation function method. The confidence levels are between 95% and 99.9%. Separating the GRBs into two parts (“dim half” and “bright half,” respectively) we obtain the result that the “dim” half shows a non-randomness at the 99.3% confidence level from the counts-in-cells test.

Importance of the High Energy Channel for the Gamma-Ray Burst Data

Extensive data bases on Gamma-Ray Burst (GRB) properties such as the BATSE 3B catalog (Meegan et al. 1996) contain a wealth of statistical information. The nine entries of the 3B database for each GRB consist of two durations, T 50, T 90, which contain 50% and 90% of the burst energy, respectively; four fluences (time-integrated energy fluxes) F1, F2, F3, F4, defined over different energy channels; and three measures of the peak flux (each summed over the four energy channels), measured over three different resolution timescales (64 ms, 256 ms and 1024 ms). Thus the initial number of variables is n = 9. There is, of course, some incompleteness in the catalog. There are 625 GRBs having all 9 non-zero quantities, and only they are considered here.