No Arabic abstract
Since the launch of Swift satellite, the detections of high-z (z>4) long gamma-ray bursts (LGRBs) have been rapidly growing, even approaching the very early Universe (the record holder currently is z=8.3). The observed high-z LGRB rate shows significant excess over that estimated from the star formation history. We investigate what may be responsible for this high productivity of GRBs at high-z through Monte Carlo simulations, with effective Swif/BAT trigger and redshift detection probabilities based on current Swift/BAT sample and CGRO/BATSE LGRB sample. We compare our simulations to the Swift observations via log N-log P, peak luminosity (L) and redshift distributions. In the case that LGRB rate is purely proportional to the star formation rate (SFR), our simulations poorly reproduce the LGRB rate at z>4, although the simulated log N-log P distribution is in good agreement with the observed one. Assuming that the excess of high-z GRB rate is due to the cosmic metallicity evolution or unknown LGRB rate increase parameterized as (1+z)^delta, we find that although the two scenarios alone can improve the consistency between our simulations and observations, incorporation of them gives much better consistency. We get 0.2<epsilon<0.6 and delta<0.6, where epsilon is the metallicity threshold for the production of LGRBs. The best consistency is obtained with a parameter set (epsilon, delta)=(~0.4, ~0.4), and BAT might trigger a few LGRBs at z~14. With increasing detections of GRBs at z>4 (~15% of GRBs in current Swift LGRB sample based on our simulations), a window for very early Universe is opening by Swift and up-coming SVOM missions.
Future missions for long gammma-ray burst (GRB) observations at high redshift such as HiZ-GUNDAM and THESEUS will provide clue to the star formation history in our universe. In this paper focusing on high redshift (z>8) GRBs, we calculate the detection rate of long GRBs by future observations, considering both Population (Pop) I&II stars and Pop III stars as GRB progenitors. For the Pop I&II star formation rate (SFR), we adopt an up-to-date model of high-redshift SFR based on the halo mass function and dark matter accretion rate obtained from cosmological simulations. We show that the Pop I&II GRB rate steeply decreases with redshift. This would rather enable us to detect the different type of GRBs, Pop III GRBs, at very high redshift. If 10% or more Pop III stars die as an ultra-long GRB, the future missions would detect such GRBs in one year in spite of their low fluence. More luminous GRBs are expected from massive compact Pop III stars produced via the binary merger. In our conventional case, the detection rate of such luminous GRBs is 3-20 /yr (z>8). Those future observations contribute to revealing of the Pop III star formation history.
The gamma-ray burst (GRB) rate is essential for revealing the connection between GRBs, supernovae and stellar evolution. Additionally, the GRB rate at high redshift provides a strong probe of star formation history in the early universe. While hundreds of GRBs are observed by Swift, it remains difficult to determine the intrinsic GRB rate due to the complex trigger algorithm of Swift. Current studies of the GRB rate usually approximate the Swift trigger algorithm by a single detection threshold. However, unlike the previously flown GRB instruments, Swift has over 500 trigger criteria based on photon count rate and additional image threshold for localization. To investigate possible systematic biases and explore the intrinsic GRB properties, we develop a program that is capable of simulating all the rate trigger criteria and mimicking the image threshold. Our simulations show that adopting the complex trigger algorithm of Swift increases the detection rate of dim bursts. As a result, our simulations suggest bursts need to be dimmer than previously expected to avoid over-producing the number of detections and to match with Swift observations. Moreover, our results indicate that these dim bursts are more likely to be high redshift events than low-luminosity GRBs. This would imply an even higher cosmic GRB rate at large redshifts than previous expectations based on star-formation rate measurements, unless other factors, such as the luminosity evolution, are taken into account. The GRB rate from our best result gives a total number of 4571^{+829}_{-1584} GRBs per year that are beamed toward us in the whole universe. SPECIAL NOTE (2015.05.16): This new version incorporates an erratum. All the GRB rate normalizations ($R_{rm GRB}(z=0)$) should be a factor of 2 smaller than previously reported. Please refer to the Appendix for more details. We sincerely apologize for the mistake.
High-redshift gamma-ray bursts have several advantages for the study of the distant universe, providing unique information about the structure and properties of the galaxies in which they exploded. Spectroscopic identification with large ground-based telescopes has improved our knowledge of the class of such distant events. We present the multi-wavelength analysis of the high-$z$ Swift gamma-ray burst GRB140515A ($z = 6.327$). The best estimate of the neutral hydrogen fraction of the intergalactic medium (IGM) towards the burst is $x_{HI} leq 0.002$. The spectral absorption lines detected for this event are the weakest lines ever observed in gamma-ray burst afterglows, suggesting that GRB140515A exploded in a very low density environment. Its circum-burst medium is characterised by an average extinction (A$_{rm V} sim 0.1$) that seems to be typical of $z ge 6$ events. The observed multi-band light curves are explained either with a very flat injected spectrum ($p = 1.7$) or with a multi-component emission ($p = 2.1$). In the second case a long-lasting central engine activity is needed in order to explain the late time X-ray emission. The possible origin of GRB140515A from a Pop III (or from a Pop II stars with local environment enriched by Pop III) massive star is unlikely.
The long gamma ray bursts (GRBs) may arise from the core collapse of massive stars. However, the long GRB rate does not follow the star formation rate (SFR) at high redshifts. In this Letter, we focus on the binary merger model and consider the high spin helium stars after the merger as the progenitor of long GRBs. With this scenario, we estimate the GRB rate by the population synthesis method with the metallicity evolution. Low metallicity binaries are easier to become long GRB progenitors than those for solar metallicity due to the weak wind mass loss and the difference in the stellar evolution. In our results, the long GRB rate roughly agrees with the observed rate, and shows a similar behavior to the observed redshift evolution.
Gamma-ray bursts (GRBs) are the most violent explosions in the Universe and can be used to explore the properties of high-redshift universe. It is believed that the long GRBs are associated with the deaths of massive stars. So it is possible to use GRBs to investigate the star formation rate (SFR). In this paper, we use Lynden-Bells $c^-$ method to study the luminosity function and rate of emph{Swift} long GRBs without any assumptions. We find that the luminosity of GRBs evolves with redshift as $L(z)propto g(z)=(1+z)^k$ with $k=2.43_{-0.38}^{+0.41}$. After correcting the redshift evolution through $L_0(z)=L(z)/g(z)$, the luminosity function can be expressed as $psi(L_0)propto L_0^{-0.14pm0.02}$ for dim GRBs and $psi(L_0)propto L_0^{-0.70pm0.03}$ for bright GRBs, with the break point $L_{0}^{b}=1.43times10^{51}~{rm erg~s^{-1}}$. We also find that the formation rate of GRBs is almost constant at $z<1.0$ for the first time, which is remarkably different from the SFR. At $z>1.0$, the formation rate of GRB is consistent with the SFR. Our results are dramatically different from previous studies. Some possible reasons for this low-redshift excess are discussed. We also test the robustness of our results with Monte Carlo simulations. The distributions of mock data (i.e., luminosity-redshift distribution, luminosity function, cumulative distribution and $log N-log S$ distribution) are in good agreement with the observations. Besides, we also find that there are remarkable difference between the mock data and the observations if long GRB are unbiased tracers of SFR at $z<1.0$.