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The hidden population of long gamma-ray bursts from compact object mergers

R. Maccary, C. Guidorzi, L. Amati, M. Bulla, S. Kobayashi, M. Maistrello, A. Rossi, G. Stratta, A. Tsvetkova

Abstract

Context. The prompt-emission time profiles of GRB 230307A and other long-duration compact object merger (COM) candidates exhibit a unique set of temporal properties, characterised by a deterministic evolution of waiting times and pulse widths. Aims. We searched the Fermi/GBM catalogue for other unidentified long COM candidates exhibiting temporal properties similar to those observed in GRB 230307A. Methods. We examined the temporal and spectral prompt-emission properties of GRBs featuring at least eight light-curve peaks. For candidates, all with unknown redshifts, that exhibited properties similar to GRB 230307A, we analysed their trajectories in the Ep,i-Eiso plane as a function of redshift. We then evaluated the joint likelihood of their compatibility with the Ep,i-Eiso relation satisfied by the bulk of long GRBs. Furthermore, we calculated their minimum variability timescales (MVTs) for comparison against known COM and collapsar populations. Results. We identified 9 COM candidates with unknown redshifts and demonstrated that there are at least two outliers of the Ep,i-Eiso relation with 3.1 sigma (Gaussian) confidence level. Furthermore, their MVTs are more consistent with those of COM than with collapsar GRBs. Conclusions. These results indicate that this specific set of temporal properties can serve as a diagnostic tool to distinguish long-duration COMs from the broader collapsar population. Furthermore, our findings suggest that the fraction of unidentified COMs among long GRBs may be larger than previously assumed.

The hidden population of long gamma-ray bursts from compact object mergers

Abstract

Context. The prompt-emission time profiles of GRB 230307A and other long-duration compact object merger (COM) candidates exhibit a unique set of temporal properties, characterised by a deterministic evolution of waiting times and pulse widths. Aims. We searched the Fermi/GBM catalogue for other unidentified long COM candidates exhibiting temporal properties similar to those observed in GRB 230307A. Methods. We examined the temporal and spectral prompt-emission properties of GRBs featuring at least eight light-curve peaks. For candidates, all with unknown redshifts, that exhibited properties similar to GRB 230307A, we analysed their trajectories in the Ep,i-Eiso plane as a function of redshift. We then evaluated the joint likelihood of their compatibility with the Ep,i-Eiso relation satisfied by the bulk of long GRBs. Furthermore, we calculated their minimum variability timescales (MVTs) for comparison against known COM and collapsar populations. Results. We identified 9 COM candidates with unknown redshifts and demonstrated that there are at least two outliers of the Ep,i-Eiso relation with 3.1 sigma (Gaussian) confidence level. Furthermore, their MVTs are more consistent with those of COM than with collapsar GRBs. Conclusions. These results indicate that this specific set of temporal properties can serve as a diagnostic tool to distinguish long-duration COMs from the broader collapsar population. Furthermore, our findings suggest that the fraction of unidentified COMs among long GRBs may be larger than previously assumed.
Paper Structure (12 sections, 3 equations, 7 figures, 5 tables)

This paper contains 12 sections, 3 equations, 7 figures, 5 tables.

Figures (7)

  • Figure 1: Temporal evolution of the PR, WT, FWHM, and $E_{\mathrm{p}}$ for three GRBs selected from the sample $S_0$. The grey solid lines represent the best-fitting exponential evolution and the shaded areas show the 3$\sigma$ confidence intervals.
  • Figure 2: Tracks of type-I candidates (sample $S_0$) in the $E_{\text{p,i}}$–$E_{\text{iso}}$ plane as a function of $z$. The tracks are colour-coded according to their $\mathcal{L}_{*}$ values, with darker (lighter) colours corresponding to higher (lower) $\mathcal{L}_{*}$. Blue and brown points represent GRBs from sample $S_{\rm I}$ and $S_{\rm II}$, respectively. The red line shows the $E_{\text{p,i}}$–$E_{\text{iso}}$ relation and the shaded areas are the 1-, 2-, and 3-$\sigma_{\rm int}$ regions. The gold star is GRB 230307A.
  • Figure 3: MVT-$T_{\rm 90}$ plane, with MVT defined as $\rm FWHM_{min}$ (adapted from Maccary25). The filled circles represent the type-I GRB candidates (sample $S_0$) identified in the present analysis. The blue and red crosses indicate short ($T_{90}<2~s$) and long ($T_{90}>2~s)$ GRBs, respectively. Gold points represent SN-associated GRBs. Magenta, lime, and cyan points represent SEE-GRBs from Lien16Lan20Kaneko15, respectively. Three extragalactic magnetar giant flare candidates, 180128A, 200415A, and 231115A are shown in brown. The solid black line represents the equality line while the dashed, dashed-dotted, and dotted lines represent a factor of 10, 100, and 1000 respectively, deviation from equality.
  • Figure 4: Temporal evolution of the PR, WTs, FWHM, and $E_{\mathrm{p}}$ for the six remaining GRBs of the sample $S_0$. The grey solid lines represent the best fits of the linear relation and the shaded grey regions represent the 3$\sigma$ confidence intervals of the fits.
  • Figure 5: Left: distribution of likelihoods (given by $\exp(-\mathcal{L_*})$, $\mathcal{L_*}$ being the negative log-likelihood) for GRBs from sample $S_{\rm IInz}$. Vertical lines show the values of $S_0$ candidates. Right: histogram of $\exp{(-\mathcal{L_*}^{\rm (tot)})}$, where $\mathcal{L_*}^{\rm (tot)}=\sum_{i=1}^{9} \mathcal{L_*}^{(i)}$ obtained from $10^{6}$ realisations of random selection of 9 GRBs from $S_{ \rm IInz}$ (Sec. \ref{['sec:EpiEiso']}). The vertical blue line shows the value obtained from the sample $S_0$, $\exp{(-{\cal L}_{*,S_0}^{\rm (tot)})}$. The fraction of simulations for which is it ${\cal L}_{*}^{\rm (tot)} \ge {\cal L}_{*,S_0}^{\rm (tot)}$ is the joint probability that all 9 GRBs from $S_0$ are consistent with the $E_{\rm p,i}-E_{\rm iso}$ for type-II GRBs. This fraction turns out to be $1.2 \times 10^{-4}$, equivalent to $3.7 \sigma$ (Gaussian).
  • ...and 2 more figures