TITLE: GCN CIRCULAR NUMBER: 46262 SUBJECT: GRB 261113A: GRANDMA/NUTTELA-TAO early optical observations DATE: 26/11/14 05:14:17 GMT FROM: Zhanat Maksut at Nazarbayev University Z. Maksut (NU), E. Abdikamalov (NU), T. Komesh (NU), D. Berdikhan (NU), M. Krugov (FAI), K. Baigarin (NU), M. Coughlin (UMN), P. Hello (IJCLAB), S. Antier (IJCLAB), M. Pillas (IAP), A. Simon (TShNU), N. Jamsin (IJCLab) and S. Karpov (FZU) on behalf of the GRANDMA/NUTTELA-TAO: We observed the field of GRB 261113A (Saccardi et al., GCN 46244) with the 0.7 m NUTTelA-TAO telescope at the Assy-Turgen Astrophysical Observatory, starting on 2026-11-13 at 14:32:16 UT, 74 s after the SVOM/ECLAIRs trigger. Observations continued for two hours in the Sloan g′ and i′ bands. We detected a rapidly fading optical counterpart (Lin et al., GCN 46247; Lei et al., GCN 46248; Li et al., GCN 46249; Yin et al., GCN 46250; Chen et al., GCN 46251; Wun et al., GCN 46252; Zhao et. al., GCN 46253; Li et. al., GCN 46254; Saikia et. al., GCN 46256; Adami et. al., GCN 46257; Izzo et. al., GCN 46259). We report the following photometry for selected epochs: Date UT_mid i'(mag) err(mag) g’(mag) err(mag) -------- ------ ------- -------- 2026-11-13 14:33:56 16.3 0.07 17.2 0.08 The preliminary measurements are given in AB magnitudes and are not corrected for Galactic extinction. Observation will be continued. The data were reduced by a data processing pipeline STDWeb (Karpov et al., 2022). Images obtained with the Sloan filters were calibrated using the PanSTARRS DR1 catalog. This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP26103591). The NUTTELA-TAO Team acknowledges the support of the staff of the Assy-Turgen Astrophysical Observatory, Almaty, Kazakhstan, and the Fesenkov Astrophysical Institute, Almaty, Kazakhstan. GRANDMA is a worldwide telescope network (grandma.ijclab.in2p3.fr) devoted to the observation of transients in the context of multi-messenger astrophysics (Antier et al. 2020 MNRAS 497, 5518). Kilonova-Catcher (KNC) is the citizen science program of GRANDMA (http://kilonovacatcher.in2p3.fr/).