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ABSTRACT Ultra-high energy cosmic rays are the most extreme energetic particles detected on Earth, however, their acceleration sites are still mysterious. We explore the contribution of low-luminosity gamma-ray bursts to the ultra-high energy cosmic ray flux, since they form the bulk of the nearby population. We analyse a representative sample of these bursts detected by BeppoSAX, INTEGRAL, and Swift between 1998–2016, and found that in order to reconcile our theoretical flux with the observed flux, these bursts should accelerate at most 10−13 M⊙ of ultra-high energy cosmic rays. 

Abstract We present the largest optical photometry compilation of Gamma-Ray Bursts (GRBs) with redshifts (z). We include 64813 observations of 535 events (including upper limits) from 28 February 1997 to 18 August 2023. We also present a user-friendly web tool grbLC which allows users to visualise photometry, coordinates, redshift, host galaxy extinction, and spectral indices for each event in our database. Furthermore, we have added a Gamma-ray Coordinate Network (GCN) scraper that can be used to collect data by gathering magnitudes from the GCNs. The web tool also includes a package for uniformly investigating colour evolution. We compute the optical spectral indices for 138 GRBs, for which we have at least 4 filters at the same epoch in our sample, and craft a procedure to distinguish between GRBs with and without colour evolution. By providing a uniform format and repository for the optical catalogue, this web-based archive is the first step towards unifying several community efforts to gather the photometric information for all GRBs with known redshifts. This catalogue will enable population studies by providing light curves (LCs) with better coverage since we have gathered data from different ground-based locations. Consequently, these LCs can be used to train future LC reconstructions for an extended inference of the redshift. The data gathering also allows us to fill some of the orbital gaps from Swift in crucial points of the LCs, e.g., at the end of the plateau emission or where a jet break is identified. 

black We present a campaign designed to train the Global Rapid Advanced Network Devoted to the Multi-messenger Addicts (GRANDMA) network and its infrastructure to follow up on transient alerts and detect their early afterglows. In preparation for O4 II campaign, we focused on gamma-ray burst (GRB) alerts since they are expected to serve as the electromagnetic counterpart of gravitational-wave events. Our goal was to improve our response to the alerts and to start prompt observations as soon as possible, so that we may better prepare the GRANDMA network for the fourth observational run of LIGO-Virgo-Kagra (launched at the end of May 2023) and future missions such as SM. black We set up a dedicated infrastructure and organized a rota of follow-up advocates (FAs) to guarantee round-the-clock assistance to our telescope teams, with an aim to receive, manage, and send out observational plansto our partner telescopes. To ensure a large number of observations, we focused on Swift GRBs whose localization errors were generally smaller than the GRANDMA telescopes' field of view. This allowed us to bypass the transient identification process and focus on the reaction time and efficiency of the network. black During the 'Ready for O4 II' phase, 11 Swift /INTEGRAL GRB triggers were selected. Of these, nine fields had been observed and three afterglows had been detected (GRB\,220403B, GRB\,220427A, GRB\,220514A) with 17 GRANDMA telescopes and 17 amateur astronomers from the citizen science project Kilonova-Catcher. Here, we highlight the GRB\,220427A analysis, where our long-term follow-up of the host galaxy allowed us to obtain a photometric redshift of $z=0.82 and its lightcurve evolution, as well as to fit the decay slope of the afterglows and study the properties of the host galaxy. black During this eight-week-long GRB follow-up campaign, we successfully fulfilled our goal of training telescope teams for O4 and improving the associated technical toolkits. For seven of the GRB alerts, our network was able to start the first observations less than one hour after the GRB trigger time. We also characterized the network efficiency to observe GRB afterglow given the resulting time delay and limiting magnitude, and to its light curve evolution based on the observation of GRB\, 220427A.