Context. There has been significant technological and scientific progress in our ability to detect, monitor and model the physics of gamma-ray bursts (GRBs) over the 50 years since their first discovery. However, the dissipation process thought to be responsible for their defining prompt emission is still unknown. Recent efforts have focused on investigating how the ultrarelativistic jet of the GRB propagates through the progenitor's stellar envelope, for different initial composition shapes, jet structures, magnetisation, and -consequently -possible energy dissipation processes. Study of the temporal variability -in particular the shortest duration of an independent emission episode within a GRB -may provide a unique way to discriminate the imprint of the inner engine activity from geometry and propagation related effects. The advent of new high-energy detectors with exquisite time resolution now makes this possible. Aims. We aim to characterise the minimum variability timescale (MVT) defined as the shortest duration of individual pulses that shape a light curve for a sample of GRBs in the keV-MeV energy range and test correlations with other key observables, such as the peak luminosity, the Lorentz factor, and the jet opening angle. We compare these correlations with predictions from recent numerical simulations for a relativistic structured -possibly wobbling -jet and assess the value of temporal variability studies as probes of prompt-emission dissipation physics. Methods. We used the peak detection algorithm mepsa to identify the shortest pulse within a GRB time history and preliminarily calibrated mepsa to estimate the full width half maximum (FWHM) duration. We then applied this framework to two sets of GRBs:

Gamma-ray Bursts (GRBs) are the most powerful transients in the Universe, over–shining for a few seconds all other γ-ray sky sources. Their emission is produced within narrowly collimated relativistic jets launched after the core–collapse of massive stars or the merger of compact binaries. THESEUS will open a new window for the use of GRBs as cosmological tools by securing a statistically significant sample of high-z GRBs, as well as by providing a large number of GRBs at low–intermediate redshifts extending the current samples to low luminosities. The wide energy band and unprecedented sensitivity of the Soft X-ray Imager (SXI) and X-Gamma rays Imaging Spectrometer (XGIS) instruments provide us a new route to unveil the nature of the prompt emission. For the first time, a full characterisation of the prompt emission spectrum from 0.3 keV to 10 MeV with unprecedented large count statistics will be possible revealing the signatures of synchrotron emission. SXI spectra, extending down to 0.3 keV, will constrain the local metal absorption and, for the brightest events, the progenitors’ ejecta composition. Investigation of the nature of the internal energy dissipation mechanisms will be obtained through the systematic study with XGIS of the sub-second variability unexplored so far over such a wide energy range. THESEUS will follow the spectral evolution of the prompt emission down to the soft X–ray band during the early steep decay and through the plateau phase with the unique ability of extending above 10 keV the spectral study of these early afterglow emission phases.

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We consider the optimisation of the observing strategy (cadence, exposure time and filter choice) using medium size (2-m class) optical telescopes in the follow-up of kilonovae localised with arcminute accuracy to be able to distinguish among various kilonova models and viewing angles. To develop an efficient observation plan, we made use of the synthetic light curves obtained with the Monte Carlo radiative transfer code possis for different kilonova models and as a function of different viewing angles and distances. By adding the appropriate photon counting noise to the synthetic light curves, we analysed four alternative sequences having the same total time exposure of 8 hours, with different time windows (0.5, 1, 2, 4 h), each with i, r, and u filters, to determine the observing sequence that maximises the chance of a correct identification of the model parameters. We suggest to avoid u filter and to avoid the use of colour curves. We also found that, if the error on distance is $\le 2~{{\%}}$, 0.5, 1, 2-hour time window sequences are equivalent, so we suggest to use 2-hour one, because it has 1 day cadence, so it can be easily realised. When the distance of the source is unknown, 0.5 h time window sequence is preferable.