Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userTesting the gamma-ray burst variability/peak luminosity correlation on a Swift homogeneous sample
116
0
0.0
(
0
)
Authors
D. Rizzuto
Ask ChatGPT about the research
No Arabic abstract
We test the gamma-ray burst correlation between temporal variability and peak luminosity of the $gamma$-ray profile on a homogeneous sample of 36 Swift/BAT GRBs with firm redshift determination. This is the first time that this correlation can be tested on a homogeneous data sample. The correlation is confirmed, as long as the 6 GRBs with low luminosity (<5x10^{50} erg s^{-1} in the rest-frame 100-1000 keV energy band) are ignored. We confirm that the considerable scatter of the correlation already known is not due to the combination of data from different instruments with different energy bands, but it is intrinsic to the correlation itself. Thanks to the unprecedented sensitivity of Swift/BAT, the variability/peak luminosity correlation is tested on low-luminosity GRBs. Our results show that these GRBs are definite outliers.
rate research
Read More
Using a sample of 14 BeppoSAX and 74 Swift GRBs with measured redshift we tested the correlation between the intrinsic peak energy of the time-integrated spectrum, E_p,i, the isotropic-equivalent peak luminosity, L_p,iso, and the duration of the most intense parts of the GRB computed as T_0.45 (Firmani correlation). For 41 out of 88 GRBs we could estimate all of the three required properties. Apart from 980425, which appears to be a definite outlier and notoriously peculiar in many respects, we used 40 GRBs to fit the correlation with the maximum likelihood method discussed by DAgostini, suitable to account for the extrinsic scatter in addition to the intrinsic uncertainties affecting every single GRB. We confirm the correlation. However, unlike the results by Firmani et al., we found that the correlation does have a logarithmic scatter comparable with that of the E_p,i-E_iso (Amati) correlation. We also find that the slope of the product L_p,iso T_0.45 is equal to ~0.5, which is consistent with the hypothesis that the E_p,i-L_p,iso-T_0.45 correlation is equivalent to the E_p,i-E_iso correlation (slope ~0.5). We conclude that, based on presently available data, there is no clear evidence that the E_p,i-L_p,iso-T_0.45 correlation is different (both in terms of slope and dispersion) from the E_p,i-E_iso correlation.
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 tested. 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].
Owing to narrow energy band of textit{Swift}/BAT, several urgent issues are required to pay more attentions but unsolved so far. We systematically study the properties of a refined sample of 283 textit{Swift}/BAT gamma-ray bursts with well-measured spectral peak energy ($E_{text p}$) at a high confidence level larger than 3$sigma$. It is interestingly found that duration ($T_{90}$) distribution of textit{Swift} bursts still exhibits an evident bimodality with a more reliable boundary of $T_{90}simeq$1.06 s instead of 2 s for previously contaminated samples including bursts without well-peaked spectra, which is very close to $sim$1.27 s and $sim$0.8 s suggested by some authors for Fermi/GBM and textit{Swift}/BAT catalogs, respectively. The textit{Swift}/BAT short and long bursts have comparable mean $E_{text p}$ values of $87^{+112}_{-49}$ and $85^{+101}_{-46}$ keV in each, similar to what found for both types of BATSE bursts, which manifests the traditional short-hard/long-soft scheme may not be tenable for the certain energy window of a detector. In statistics, we also investigate the consistency of distinct methods for the $E_{text p}$ estimates and find that Bayesian approach and BAND function can always give consistent evaluations. In contrast, the frequently-used cut-off power-law model matches two other methods for lower $E_{text p}$ and will overestimate the $E_{text p}$ more than 70% as $E_{text p}>$100 keV. Peak energies of X-ray flashes, X-ray rich bursts and classical gamma-ray bursts could have an evolutionary consequence from thermal-dominated to non-thermal-dominated radiation mechanisms. Finally, we find that the $E_{text p}$ and the observed fluence ($S_{gamma}$) in the observer frame are correlated as $E_psimeq [S_{gamma}/(10^{-5} erg cm^{-2})]^{0.28}times 117.5^{+44.7}_{-32.4}$ keV proposed to be an useful indicator of GRB peak energies.
We present a carefully selected sub-sample of Swift Long Gamma-ray Bursts (GRBs), that is complete in redshift. The sample is constructed by considering only bursts with favorable observing conditions for ground-based follow-up searches, that are bright in the 15-150 keV Swift/BAT band, i.e. with 1-s peak photon fluxes in excess to 2.6 ph s^-1 cm^-2. The sample is composed by 58 bursts, 52 of them with redshift for a completeness level of 90%, while another two have a redshift constraint, reaching a completeness level of 95%. For only three bursts we have no constraint on the redshift. The high level of redshift completeness allows us for the first time to constrain the GRB luminosity function and its evolution with cosmic times in a unbiased way. We find that strong evolution in luminosity (d_l=2.3pm 0.6) or in density (d_d=1.7pm 0.5) is required in order to account for the observations. The derived redshift distribution in the two scenarios are consistent with each other, in spite of their different intrinsic redshift distribution. This calls for other indicators to distinguish among different evolution models. Complete samples are at the base of any population studies. In future works we will use this unique sample of Swift bright GRBs to study the properties of the population of long GRBs.
To date, the Burst Alert Telescope (BAT) onboard Swift has detected ~ 1000 gamma-ray bursts (GRBs), of which ~ 360 GRBs have redshift measurements, ranging from z = 0.03 to z = 9.38. We present the analyses of the BAT-detected GRBs for the past ~ 11 years up through GRB151027B. We report summaries of both the temporal and spectral analyses of the GRB characteristics using event data (i.e., data for each photon within approximately 250 s before and 950 s after the BAT trigger time), and discuss the instrumental sensitivity and selection effects of GRB detections. We also explore the GRB properties with redshift when possible. The result summaries and data products are available at http://swift.gsfc.nasa.gov/results/batgrbcat/index.html . In addition, we perform searches for GRB emissions before or after the event data using the BAT survey data. We estimate the false detection rate to be only one false detection in this sample. There are 15 ultra-long GRBs (~ 2% of the BAT GRBs) in this search with confirmed emission beyond ~ 1000 s of event data, and only two GRBs (GRB100316D and GRB101024A) with detections in the survey data prior to the starting of event data. (Some figures shown here are in lower resolution due to the size limit on arXiv. The full resolution version can be found at http://swift.gsfc.nasa.gov/results/batgrbcat/3rdBATcatalog.pdf )
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
