GRB 131231A was detected by the Large Area Telescope onboard Fermi Space Gamma-ray Telescope. The high energy gamma-ray ($> 100$ MeV) afterglow emission spectrum is $F_ u propto u^{-0.54pm0.15}$ in the first $sim 1300$ s after the trigger and the mo
st energetic photon has an energy $sim 62$ GeV arriving at $tsim 520$ s. With reasonable parameters of the GRB outflow as well as the density of the circum-burst medium, the synchrotron radiation of electrons or protons accelerated at an external forward shock have difficulty accounting for the data. The synchrotron self-Compton radiation of the forward shock-accelerated electrons, instead, can account for both the spectrum and temporal behavior of the GeV afterglow emission. We also show that the prospect for detecting GRB 131231A$-$like GRBs with Cherenkov Telescope Array (CTA) is promising.
The durations (T90) of 315 GRBs detected with Fermi/GBM (8-1000 keV) by 2011 September are calculated using the Bayesian Block method. We compare the T90 distributions between this sample and those derived from previous/current GRB missions. We show
that the T90 distribution of this GRB sample is bimodal, with a statistical significance level being comparable to those derived from the BeppoSAX/GRBM sample and the Swift/BAT sample, but lower than that derived from the CGRO/BATSE sample. The short-to-long GRB number ratio is also much lower than that derived from the BATSE sample, i.e., 1:6.5 vs 1:3. We measure T90 in several bands, i.e., 8-15, 15-25, 25-50, 50-100, 100-350, and 350-1000 keV, to investigate the energy-dependence effect of the bimodal T90 distribution. It is found that the bimodal feature is well observed in the 50-100 and 100-350 keV bands, but is only marginally acceptable in the 25-50 keV and 350-1000 keV bands. The hypothesis of the bimodality is confidently rejected in the 8-15 and 15-25 keV bands. The T90 distributions in these bands are roughly consistent with those observed by missions with similar energy bands. The parameter T90 as a function of energy follows bar T90 propto E^{-0.20pm 0.02} for long GRBs. Considering the erratic X-ray and optical flares, the duration of a burst would be even much longer for most GRBs. Our results, together with the observed extended emission of some short GRBs, indicate that the central engine activity time scale would be much longer than T90} for both long and short GRBs and the observed bimodal T90 distribution may be due to an instrumental selection effect.
We consider the problem of estimating the predictive density of future observations from a non-parametric regression model. The density estimators are evaluated under Kullback--Leibler divergence and our focus is on establishing the exact asymptotics
of minimax risk in the case of Gaussian errors. We derive the convergence rate and constant for minimax risk among Bayesian predictive densities under Gaussian priors and we show that this minimax risk is asymptotically equivalent to that among all density estimators.
This paper has been withdrawn by the authors due to a fatal error in the analysis. The manuscript was submitted to Chemical Engineering Science. To clarify the situation, we copy the main comment from an anonymous referee here: To my understanding, t
he authors analyze i = 1 ... 63 time series and calculate their mean and standard deviation. These time series correspond to individual, single ignition processes. Is this correct? If yes, these processes, as Fig. 3 shows very clearly, are not stationary, and the pressure difference (i.e., the signal) quickly decays to zero. In this case both the mean and the standard deviation are poorly defined, for example because both depend in a trivial fashion on the observation period T. I am not aware of any study (including those cited by the authors) which allows for any conclusion from such non-stationary signals. The results of Menezes and Barabasi are strictly only valid for stationary time series, and they cannot be applied at all in this case. We agree with this insightful comment that our data are not stationary and the method adopted in our manuscript does not apply. We do not see any possibility to correct this error and decide to withdraw it. We would like to thank gratefully the referee and apologize for any inconvenience caused by our oversight.
