# Multi-band analyses of the bright GRB 230812B and the associated SN2023pel

T Hussenot-Desenonges, T Wouters, N Guessoum, I Abdi, A Abulwfa, C Adami, J.F. Agüí Fernández, T Ahumada, V Aivazyan, D Akl, et al.

► To cite this version:

T Hussenot-Desenonges, T Wouters, N Guessoum, I Abdi, A Abulwfa, et al. Multi-band analyses of the bright GRB 230812B and the associated SN2023pel. Mon.Not.Roy.Astron.Soc., 2024, 530 (1), pp.1-19. 10.1093/mnras/stae503. hal-04268716

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https://hal.science/hal-04268716

Submitted on 16 May 2024

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# Multi-band analyses of the bright GRB 230812B and the associated SN2023pel

T Hussenot-Desenonges, T Wouters, N Guessoum, I Abdi, A Abulwfa, C Adami, J.F. Agüí Fernández, T Ahumada, V Aivazyan, D Akl, et al.

► To cite this version:

T Hussenot-Desenonges, T Wouters, N Guessoum, I Abdi, A Abulwfa, et al. Multi-band analyses of the bright GRB 230812B and the associated SN2023pel. Monthly Notices of the Royal Astronomical Society, 2024, 530 (1), pp.1-19. 10.1093/mnras/stae503. hal-04268716

HAL Id: hal-04268716

https://hal.science/hal-04268716v1

Submitted on 16 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
# Multiband analyses of the bright GRB 230812B and the associated SN2023pel

T. Hussenot-Desenonges,¹★ T. Wouters,²,³ N. Guessoum¹,⁴★ I. Abdi,⁴ A. Abulwfa,⁵ C. Adami,⁶ J. F. Agúí Fernández,⁵,⁷ T. Ahumada,⁸ V. Aivazyan,⁹,¹⁰ D. Akl,⁴ S. Anand,⁵,⁸ C. M. Andrade,¹¹ S. Antier,¹²★ S. A. Ata,⁵ P. D'Avanzo,¹³ Y. A. Azzam,⁵ A. Baransky,¹⁴ S. Basa,⁶ M. Blazek,¹⁵,¹⁶ P. Bendjoya,¹⁷ S. Beradze,⁹,¹⁰ P. Boumis,¹⁸ M. Bremer,¹⁹ R. Brivio,¹³,²⁰ V. Buat,⁶ M. Bulla,²¹,²²,²³ O. Burkhonov,²⁴ E. Burns,²⁵ S. B. Cenko,²⁶,²⁷ M. W. Coughlin,¹¹ W. Corradi,²⁸ F. Daigne,²⁹ T. Dietrich,³⁰,³¹ D. Dornic,³² J.-G. Ducoin,²⁹,³² P.-A. Duverne,³³ E. G. Elhosseiny,⁵ F. I. Elnagahy,⁵ M. A. El-Sadek,⁵ M. Ferro,¹³,²⁰ E. Le Floc'h,³⁴ M. Freeberg,³⁵ J. P. U. Fynbo,³⁶,³⁷ D. Götz,³⁴ E. Gurbanov,³⁸ G. M. Hamed,⁵ E. Hasanov,³⁸ B. F. Healy,³⁹ K. E. Heintz,³⁶,³⁷ P. Hello,¹ R. Inasaridze,⁹,¹⁰ A. Iskandar,⁴⁰ N. Ismailov,³⁸ L. Izzo,⁴¹,⁴² S. Jhawar,³⁰ T. Jegou du Laz,⁴³ T. M. Kamel,⁵ S. Karpov,¹⁵ A. Klotz,⁴⁴,⁴⁵ E. Koulouridis,¹⁸ N. P. Kuin,⁴⁶ N. Kochiashvili,⁹ S. Leonini,⁴⁷ K.-X. Lu,⁴⁸ D. B. Malesani,³⁶,³⁷,⁴⁹ M. Mašek,⁵⁰ J. Mao,⁴⁸,⁵¹,⁵² A. Melandri,¹³,⁵³ B. M. Mihov,⁵⁴ R. Natsvlishvili,⁹ F. Navarete,⁵⁵ V. Nedora,³¹ J. Nicolas,¹² M. Odeh,¹² J. Palmerio,⁵⁶ P. T. H. Pang,²,³ M. De Pasquale,⁵⁷ H. W. Peng,⁵⁸ S. Pormente,¹² J. Peloton,¹ T. Pradier,⁵⁹ O. Pyshna,¹⁴ Y. Rajabov,²⁴ N. A. Rakotondrainibe,⁶ J.-P. Rivet,¹⁷ L. Rousselot,¹² A. Saccardi,⁵⁶ N. Sasaki,²⁸ B. Schneider,⁶⁰ M. Serrau,⁶¹ A. Shokry,⁵ L. Slavcheva-Mihova,⁵⁴ A. Simon,⁶²,⁶³ O. Sokoliuk,¹⁴,⁶⁴ G. Srinivasaragavan,²⁶,²⁷,⁶⁵ R. Strausbaugh,⁶⁶ A. Takey,⁵ N. R. Tanvir,⁶⁷ C. C. Thöne,⁶⁸ Y. Tillayev,²⁴,⁶⁹ I. Tosta e Melo,⁷⁰ D. Turpin,³⁴ A. de Ugarte Postigo,⁶,¹² V. Vasylenko,⁶²,⁶³ S. D. Vergani,⁵⁶ Z. Vidadi,³⁸ D. Xu,⁵² L. T. Wang,⁴⁰ X. F. Wang,⁵⁸,⁷¹ J. M. Winters,¹⁹ X.-L. Zhang⁴⁸ and Z. Zhu⁵²,⁷²

*Affiliations are listed at the end of the paper*

Accepted 2024 February 13. Received 2024 February 7; in original form 2023 October 22

## ABSTRACT

GRB 230812B is a bright and relatively nearby (z = 0.36) long gamma-ray burst (GRB) that has generated significant interest in the community and has thus been observed over the entire electromagnetic spectrum. We report over 80 observations in X-ray, ultraviolet, optical, infrared, and submillimetre bands from the GRANDMA (Global Rapid Advanced Network for Multimessenger Addicts) network of observatories and from observational partners. Adding complementary data from the literature, we then derive essential physical parameters associated with the ejecta and external properties (i.e. the geometry and environment) of the GRB and compare with other analyses of this event. We spectroscopically confirm the presence of an associated supernova, SN2023pel, and we derive a photospheric expansion velocity of v ~ 17 × 10³ km s⁻¹. We analyse the photometric data first using empirical fits of the flux and then with full Bayesian inference. We again strongly establish the presence of a supernova in the data, with a maximum (pseudo-)bolometric luminosity of 5.75 × 10⁴² erg s⁻¹, at 15.76[1.21] d (in the observer frame) after the trigger, with a half-max time width of 22.0 d. We compare these values with those of SN1998bw, SN2006aj, and SN2013dx. Our best-fitting model favours a very low density environment (log₁₀(nISM/cm⁻³) = −2.38+1.45/-1.60) and small values for the jet's core angle θcore = 1.54+1.02/-0.81 deg and viewing angle θobs = 0.76+1.29/-0.76 deg. GRB 230812B is thus one of the best observed afterglows with a distinctive supernova bump.

**Key words:** methods: statistical – techniques: photometric – techniques: spectroscopic – gamma-ray burst: individual: GRB 230812B – gamma-ray bursts – transients: supernovae.

<footnote>* E-mail: nguessoum@aus.edu (NG); sarah.antier@oca.edu (SA); thomas.hussenot@ijclab.in2p3.fr (THD)</footnote>
# Multiband analyses of the bright GRB 230812B and the associated SN2023pel

T. Hussenot-Desenonges,¹★ T. Wouters,²,³ N. Guessoum¹,⁴★ I. Abdi,⁴ A. Abulwfa,⁵ C. Adami,⁶ J. F. Agúí Fernández,⁵,⁷ T. Ahumada,⁸ V. Aivazyan,⁹,¹⁰ D. Akl,⁴ S. Anand,⁵,⁸ C. M. Andrade,¹¹ S. Antier,¹²★ S. A. Ata,⁵ P. D'Avanzo,¹³ Y. A. Azzam,⁵ A. Baransky,¹⁴ S. Basa,⁶ M. Blazek,¹⁵,¹⁶ P. Bendjoya,¹⁷ S. Beradze,⁹,¹⁰ P. Boumis,¹⁸ M. Bremer,¹⁹ R. Brivio,¹³,²⁰ V. Buat,⁶ M. Bulla,²¹,²²,²³ O. Burkhonov,²⁴ E. Burns,²⁵ S. B. Cenko,²⁶,²⁷ M. W. Coughlin,¹¹ W. Corradi,²⁸ F. Daigne,²⁹ T. Dietrich,³⁰,³¹ D. Dornic,³² J.-G. Ducoin,²⁹,³² P.-A. Duverne,³³ E. G. Elhosseiny,⁵ F. I. Elnagahy,⁵ M. A. El-Sadek,⁵ M. Ferro,¹³,²⁰ E. Le Floc'h,³⁴ M. Freeberg,³⁵ J. P. U. Fynbo,³⁶,³⁷ D. Götz,³⁴ E. Gurbanov,³⁸ G. M. Hamed,⁵ E. Hasanov,³⁸ B. F. Healy,³⁹ K. E. Heintz,³⁶,³⁷ P. Hello,¹ R. Inasaridze,⁹,¹⁰ A. Iskandar,⁴⁰ N. Ismailov,³⁸ L. Izzo,⁴¹,⁴² S. Jhawar,³⁰ T. Jegou du Laz,⁴³ T. M. Kamel,⁵ S. Karpov,¹⁵ A. Klotz,⁴⁴,⁴⁵ E. Koulouridis,¹⁸ N. P. Kuin,⁴⁶ N. Kochiashvili,⁹ S. Leonini,⁴⁷ K.-X. Lu,⁴⁸ D. B. Malesani,³⁶,³⁷,⁴⁹ M. Mašek,⁵⁰ J. Mao,⁴⁸,⁵¹,⁵² A. Melandri,¹³,⁵³ B. M. Mihov,⁵⁴ R. Natsvlishvili,⁹ F. Navarete,⁵⁵ V. Nedora,³¹ J. Nicolas,¹² M. Odeh,¹² J. Palmerio,⁵⁶ P. T. H. Pang,²,³ M. De Pasquale,⁵⁷ H. W. Peng,⁵⁸ S. Pormente,¹² J. Peloton,¹ T. Pradier,⁵⁹ O. Pyshna,¹⁴ Y. Rajabov,²⁴ N. A. Rakotondrainibe,⁶ J.-P. Rivet,¹⁷ L. Rousselot,¹² A. Saccardi,⁵⁶ N. Sasaki,²⁸ B. Schneider,⁶⁰ M. Serrau,⁶¹ A. Shokry,⁵ L. Slavcheva-Mihova,⁵⁴ A. Simon,⁶²,⁶³ O. Sokoliuk,¹⁴,⁶⁴ G. Srinivasaragavan,²⁶,²⁷,⁶⁵ R. Strausbaugh,⁶⁶ A. Takey,⁵ N. R. Tanvir,⁶⁷ C. C. Thöne,⁶⁸ Y. Tillayev,²⁴,⁶⁹ I. Tosta e Melo,⁷⁰ D. Turpin,³⁴ A. de Ugarte Postigo,⁶,¹² V. Vasylenko,⁶²,⁶³ S. D. Vergani,⁵⁶ Z. Vidadi,³⁸ D. Xu,⁵² L. T. Wang,⁴⁰ X. F. Wang,⁵⁸,⁷¹ J. M. Winters,¹⁹ X.-L. Zhang⁴⁸ and Z. Zhu⁵²,⁷²

*Affiliations are listed at the end of the paper*

Accepted 2024 February 13. Received 2024 February 7; in original form 2023 October 22

## ABSTRACT

GRB 230812B is a bright and relatively nearby (z = 0.36) long gamma-ray burst (GRB) that has generated significant interest in the community and has thus been observed over the entire electromagnetic spectrum. We report over 80 observations in X-ray, ultraviolet, optical, infrared, and submillimetre bands from the GRANDMA (Global Rapid Advanced Network for Multimessenger Addicts) network of observatories and from observational partners. Adding complementary data from the literature, we then derive essential physical parameters associated with the ejecta and external properties (i.e. the geometry and environment) of the GRB and compare with other analyses of this event. We spectroscopically confirm the presence of an associated supernova, SN2023pel, and we derive a photospheric expansion velocity of v ~ 17 × 10³ km s⁻¹. We analyse the photometric data first using empirical fits of the flux and then with full Bayesian inference. We again strongly establish the presence of a supernova in the data, with a maximum (pseudo-)bolometric luminosity of 5.75 × 10⁴² erg s⁻¹, at 15.76+0.81-1.21¹ d (in the observer frame) after the trigger, with a half-max time width of 22.0 d. We compare these values with those of SN1998bw, SN2006aj, and SN2013dx. Our best-fitting model favours a very low density environment (log₁₀(nISM/cm⁻³) = −2.38 ра+1.45 — 1.60) and small values for the jet’s core angle θcore = 1.54 ра+1.02 — 0.81 deg and viewing angle θobs = 0.76 ра+1.29 — 0.76 deg. GRB 230812B is thus one of the best observed afterglows with a distinctive supernova bump.

**Key words:** methods: statistical – techniques: photometric – techniques: spectroscopic – gamma-ray burst: individual: GRB 230812B – gamma-ray bursts – transients: supernovae.

<footnote>* E-mail: nguessoum@aus.edu (NG); sarah.antier@oca.edu (SA); thomas.hussenot@ijclab.in2p3.fr (THD)</footnote>
# 1 INTRODUCTION

Gamma-ray bursts (GRBs) are energetic explosions that, with their afterglows, emit over the entire range of electromagnetic radiation. Typically, they are classified in two categories: 'long' (duration), lasting more than 2 s in the gamma/X-ray bands, and 'short', lasting less than 2 s. Long GRBs are widely believed to result from the collapse and explosion of a very massive star, hence they are often referred to as 'collapsar' and hypernova. Short GRBs are thought to result from the merger of a neutron star with another neutron star or with a black hole (compact objects). In both categories, GRBs produce bipolar jets emerging from the newly formed compact object. The jets interact with the surrounding matter and, through shocks, producing 'afterglow' emission, first in the X-ray band, then, as the jet slows and weaker shocks occur, UV, optical, IR, and radio emissions. The luminosity of GRB afterglows is moderately correlated with the isotropic prompt-emission (mostly γ-ray) energy released, $E_{iso}$ (Gehrels et al. 2008; Nysewander, Fruchter & Pe'er 2009; Kann et al. 2010, 2011).

Core-collapse GRBs are also associated with an optical/near-infrared supernova (SN), which represents the more isotropic outburst (in addition to the jet) from the central explosive process (more below). GRB 980425/SN1998bw was the first well-documented example of a GRB associated with a supernova, a core-collapse event strongly associated with a (long-duration) burst (Galama et al. 1998; Patat et al. 2001). The association between SN1998bw and GRB 980425 was first made from the optical spectrum and location of a transient in a spiral arm of the galaxy ESO184-G82 (Galama et al. 1998). Observations of such cases strengthen the fact that galaxies with strong star formation have greater potential for the occurrence of long gamma-ray bursts (Bloom, Kulkarni & Djorgovski 2002).

In addition to this seminal case, a number of similar associations have been observed since then, such as GRB 030329 with SN2003dh (Hjorth et al. 2003; Stanek et al. 2003). Spectral features of SN2003dh indicated a very massive star origin (Deng et al. 2005), reinforcing the notion that the GRB resulted from a core-collapse process. These breakthrough observations opened the door for the collection of a significant number of GRB-SN associations, now a well-identified class of astrophysical events. Other thoroughly studied examples include GRB 031203/SN2003lw (Malesani et al. 2004), GRB 060218/SN2006aj (Ferrero et al. 2006; Pian et al. 2006), GRB 100316D/SN2010bh (Cano et al. 2011), GRB 120422A/SN2012bz (Melandri et al. 2012; Schulze et al. 2014), GRB 130702A/SN2013dx (D'Elia et al. 2015; Mazzali et al. 2021), GRB 161219B/SN2016jca (Ashall et al. 2019), and GRB 171010A/SN2017htp (Melandri et al. 2019).

Important elements which strengthen the association of supernovae with gamma-ray bursts (such as the above cases) include the broad lines in the object's emission spectrum, which are strongly typical of Type Ic supernova lines, and the association with star-forming galaxies; such indicators provide a coherent scenario for the GRB-SN association. Still, important issues remain to be resolved, including: in which cases does a process (collapsar, merger) produce a long or short GRB, and what are their counterparts (r-process or not?); what powers the central engine in each case (magnetar, radioactive heating, etc.); what kinds of jets are produced, etc. To address such key questions, we need a large sample of GRB events exhibiting multiband emission with a (supernova/kilonova) bump in the light curve, characteristic lines in the spectrum, rich enough data to give us constraints on the current models (radioactive heating, millisecond magnetar central engine, etc.).

Important parameters that characterize the SNe associated with GRBs include their maximum luminosity (bolometric and in various

bands), the time of their peak emission, and the width at half-max of the light curve. Many authors often use the (less physically meaningful) relative brightness factor $k$ (typically compared to SN1998bw) and the (time) 'stretch factor' $s$ (that is, a 'time width'), also compared to SN1998bw (Cano et al. 2017). A grading system, introduced by Hjorth & Bloom (2012), became widely adopted for characterizing the strength of a GRB-SN association. The grading ranges from (A), very strong (conclusive spectroscopic evidence), to (E), the weakest associations. In the last 25 yr, there have been a dozen cases rated A or A/B (Cano et al. 2017). For those, the average peak time (in the rest frame) is ~13.2 d, with a standard deviation of ~2.6 d (computed from table 3 of Cano et al. 2017).

However, the massive star origin for all long GRBs has recently been challenged by the discovery of a few long GRBs (GRB 211211A, GRB 230307A) associated with a kilonova, normally the signature of a binary compact object merger (Rastinejad et al. 2022; Troja et al. 2022; Yang et al. 2022; Bulla et al. 2023; Levan et al. 2023). In addition to these recent associations with kilonovae, there are also nearby long GRBs without a detected bright SN (Fynbo et al. 2006; Gal-Yam et al. 2006; Gehrels et al. 2006; Valle et al. 2006; Jin et al. 2015). This evidence then produces a more nuanced picture: while most long GRBs originate in massive star explosions, a few may have a different origin. It is thus crucial to obtain a revised census of the collapsar/merger origin for long GRBs. Events at low redshift ($z \lesssim 0.5$) offer an excellent opportunity to carry out this measurement, as the associated SNe, if present, can be easily detected in photometry and even confirmed spectroscopically with 10 m-class telescopes. GRB 230812B provided us with an opportunity to further explore these GRB-Supernova/Kilonova associations.

GRB-SN associations may also be found serendipitously with optical wide-field survey programmes (Soderberg et al. 2008; Sanders et al. 2012) rather than by following bursts and their afterglows. GRB 230812B was initially detected by the Fermi Gamma-ray Burst Monitor (GBM - Meegan et al. 2009), the Gravitational wave high-energy Electromagnetic Counterpart All sky Monitor (GECAM), the AGILE/MCAL instrument (Casentini et al. 2023), and the Konus-Wind instrument (Frederiks et al. 2023). This GRB is the most recent event to exhibit a clear SN feature.

Triggered at $T_0 = 18:58:12$ UT on 2023 August 12 (GBM trigger 713559497/230812790 - Fermi GBM Team 2023), the GRB's light curve in the [10–10 000] keV band showed a very bright short pulse with a $T_{90}$ duration (90 per cent of its fluence at [50, 300] keV) equal to $3.264 \pm 0.091$ s (Roberts et al. 2023). The GECAM light curve reported a value of $T_{90} = 4$ s in the [6–1000] keV range (Xiong et al. 2023), and Konus a total time of $\sim 20$ s in the [20–1200] keV range (Frederiks et al. 2023), consistent with GBM's value. The Fermi Large Area Telescope (LAT) independently detected high energy photons with a maximum of 72 GeV ($T_0 + 30$ s) (Scotton et al. 2023).

With the sky localization probability area provided by GBM or LAT (Lesage et al. 2023; Scotton et al. 2023), a series of tiled observations were obtained by the *Neil Gehrels Swift* observatory X-ray telescope (XRT) (Gehrels et al. 2004), the Zwicky Transient Facility (Salgundi et al. 2023), and the Global MASTER-Net (Lipunov et al. 2023a). The X-ray and UV counterpart of GRB 230812B was discovered 7.1 h after $T_0$ by Swift/XRT (Page & Swift-XRT Team 2023) and Swift/UVOT (Kuin & Swift/UVOT Team 2023). The optical counterpart of GRB 230812B was found by the Zwicky Transient Facility on 2023 August 13 at 03:34:56, 8.5 h after the GRB trigger time $T_0$ (Salgundi et al. 2023), and also by KAIT (the Katzman Automatic Imaging Telescope - Zheng, Filippenko & KAIT GRB team 2023), which provided localization with arcsecond accuracy. Simultaneously, the Global MASTER-Net
# 1 INTRODUCTION

Gamma-ray bursts (GRBs) are energetic explosions that, with their afterglows, emit over the entire range of electromagnetic radiation. Typically, they are classified in two categories: 'long' (duration), lasting more than 2 s in the gamma/X-ray bands, and 'short', lasting less than 2 s. Long GRBs are widely believed to result from the collapse and explosion of a very massive star, hence they are often referred to as 'collapsar' and hypernova. Short GRBs are thought to result from the merger of a neutron star with another neutron star or with a black hole (compact objects). In both categories, GRBs produce bipolar jets emerging from the newly formed compact object. The jets interact with the surrounding matter and, through shocks, producing 'afterglow' emission, first in the X-ray band, then, as the jet slows and weaker shocks occur, UV, optical, IR, and radio emissions. The luminosity of GRB afterglows is moderately correlated with the isotropic prompt-emission (mostly γ-ray) energy released, $E_{iso}$ (Gehrels et al. 2008; Nysewander, Fruchter & Pe'er 2009; Kann et al. 2010, 2011).

Core-collapse GRBs are also associated with an optical/near-infrared supernova (SN), which represents the more isotropic outburst (in addition to the jet) from the central explosive process (more below). GRB 980425/SN1998bw was the first well-documented example of a GRB associated with a supernova, a core-collapse event strongly associated with a (long-duration) burst (Galama et al. 1998; Patat et al. 2001). The association between SN1998bw and GRB 980425 was first made from the optical spectrum and location of a transient in a spiral arm of the galaxy ESO184-G82 (Galama et al. 1998). Observations of such cases strengthen the fact that galaxies with strong star formation have greater potential for the occurrence of long gamma-ray bursts (Bloom, Kulkarni & Djorgovski 2002).

In addition to this seminal case, a number of similar associations have been observed since then, such as GRB 030329 with SN2003dh (Hjorth et al. 2003; Stanek et al. 2003). Spectral features of SN2003dh indicated a very massive star origin (Deng et al. 2005), reinforcing the notion that the GRB resulted from a core-collapse process. These breakthrough observations opened the door for the collection of a significant number of GRB-SN associations, now a well-identified class of astrophysical events. Other thoroughly studied examples include GRB 031203/SN2003lw (Malesani et al. 2004), GRB 060218/SN2006aj (Ferrero et al. 2006; Pian et al. 2006), GRB 100316D/SN2010bh (Cano et al. 2011), GRB 120422A/SN2012bz (Melandri et al. 2012; Schulze et al. 2014), GRB 130702A/SN2013dx (D'Elia et al. 2015; Mazzali et al. 2021), GRB 161219B/SN2016jca (Ashall et al. 2019), and GRB 171010A/SN2017htp (Melandri et al. 2019).

Important elements which strengthen the association of supernovae with gamma-ray bursts (such as the above cases) include the broad lines in the object's emission spectrum, which are strongly typical of Type Ic supernova lines, and the association with star-forming galaxies; such indicators provide a coherent scenario for the GRB-SN association. Still, important issues remain to be resolved, including: in which cases does a process (collapsar, merger) produce a long or short GRB, and what are their counterparts (r-process or not?); what powers the central engine in each case (magnetar, radioactive heating, etc.); what kinds of jets are produced, etc. To address such key questions, we need a large sample of GRB events exhibiting multiband emission with a (supernova/kilonova) bump in the light curve, characteristic lines in the spectrum, rich enough data to give us constraints on the current models (radioactive heating, millisecond magnetar central engine, etc.).

Important parameters that characterize the SNe associated with GRBs include their maximum luminosity (bolometric and in various

bands), the time of their peak emission, and the width at half-max of the light curve. Many authors often use the (less physically meaningful) relative brightness factor $k$ (typically compared to SN1998bw) and the (time) 'stretch factor' $s$ (that is, a 'time width'), also compared to SN1998bw (Cano et al. 2017). A grading system, introduced by Hjorth & Bloom (2012), became widely adopted for characterizing the strength of a GRB-SN association. The grading ranges from (A), very strong (conclusive spectroscopic evidence), to (E), the weakest associations. In the last 25 yr, there have been a dozen cases rated A or A/B (Cano et al. 2017). For those, the average peak time (in the rest frame) is ~13.2 d, with a standard deviation of ~2.6 d (computed from table 3 of Cano et al. 2017).

However, the massive star origin for all long GRBs has recently been challenged by the discovery of a few long GRBs (GRB 211211A, GRB 230307A) associated with a kilonova, normally the signature of a binary compact object merger (Rastinejad et al. 2022; Troja et al. 2022; Yang et al. 2022; Bulla et al. 2023; Levan et al. 2023). In addition to these recent associations with kilonovae, there are also nearby long GRBs without a detected bright SN (Fynbo et al. 2006; Gal-Yam et al. 2006; Gehrels et al. 2006; Valle et al. 2006; Jin et al. 2015). This evidence then produces a more nuanced picture: while most long GRBs originate in massive star explosions, a few may have a different origin. It is thus crucial to obtain a revised census of the collapsar/merger origin for long GRBs. Events at low redshift ($z \lesssim 0.5$) offer an excellent opportunity to carry out this measurement, as the associated SNe, if present, can be easily detected in photometry and even confirmed spectroscopically with 10 m-class telescopes. GRB 230812B provided us with an opportunity to further explore these GRB-Supernova/Kilonova associations.

GRB-SN associations may also be found serendipitously with optical wide-field survey programmes (Soderberg et al. 2008; Sanders et al. 2012) rather than by following bursts and their afterglows. GRB 230812B was initially detected by the Fermi Gamma-ray Burst Monitor (GBM - Meegan et al. 2009), the Gravitational wave high-energy Electromagnetic Counterpart All sky Monitor (GECAM), the AGILE/MCAL instrument (Casentini et al. 2023), and the Konus-Wind instrument (Frederiks et al. 2023). This GRB is the most recent event to exhibit a clear SN feature.

Triggered at $T_0 = 18:58:12$ UT on 2023 August 12 (GBM trigger 713559497/230812790 - Fermi GBM Team 2023), the GRB's light curve in the [10–10 000] keV band showed a very bright short pulse with a $T_{90}$ duration (90 per cent of its fluence at [50, 300] keV) equal to $3.264 \pm 0.091$ s (Roberts et al. 2023). The GECAM light curve reported a value of $T_{90} = 4$ s in the [6–1000] keV range (Xiong et al. 2023), and Konus a total time of $\sim 20$ s in the [20–1200] keV range (Frederiks et al. 2023), consistent with GBM's value. The Fermi Large Area Telescope (LAT) independently detected high energy photons with a maximum of 72 GeV ($T_0 + 30$ s) (Scotton et al. 2023).

With the sky localization probability area provided by GBM or LAT (Lesage et al. 2023; Scotton et al. 2023), a series of tiled observations were obtained by the *Neil Gehrels Swift* observatory X-ray telescope (XRT) (Gehrels et al. 2004), the Zwicky Transient Facility (Salgundi et al. 2023), and the Global MASTER-Net (Lipunov et al. 2023a). The X-ray and UV counterpart of GRB 230812B was discovered 7.1 h after $T_0$ by Swift/XRT (Page & Swift-XRT Team 2023) and Swift/UVOT (Kuin & Swift/UVOT Team 2023). The optical counterpart of GRB 230812B was found by the Zwicky Transient Facility on 2023 August 13 at 03:34:56, 8.5 h after the GRB trigger time $T_0$ (Salgundi et al. 2023), and also by KAIT (the Katzman Automatic Imaging Telescope - Zheng, Filippenko & KAIT GRB team 2023), which provided localization with arcsecond accuracy. Simultaneously, the Global MASTER-Net
robotic telescopes network reported the optical counterpart at the same location (Lipunov et al. 2023b).

A series of photometric observations across the full electro-magnetic spectrum were conducted in the months following the trigger. Among them, we can cite as an example the Multi-purpose InSTRument for Astronomy at Low-resolution spectrometer (T193/MISTRAL) in optical (Amram et al. 2023; Adami et al. 2023a, b), the Italian 3.6 m TNG telescope in near-infrared, and the Northern extended millimeter array (NOEMA) in radio (de Ugarte Postigo et al. 2023b). Spectroscopic observations were also conducted in parallel. It led to the measurements of the transient's redshift: $z = 0.360$ (de Ugarte Postigo et al. 2023a). Twelve days later, observations using OSIRIS+ mounted on the Gran Telescopio Canarias (GTC) showed features in the spectrum characteristic of a GRB-SN event and matched with the spectrum of SN1998bw, indicating, rather conclusively, the presence of a supernova (Agui Fernandez et al. 2023; Agúñ Fernández et al. 2023).

Observations with GRANDMA (Global Rapid Advanced Network for Multimessenger Addicts: Antier et al. 2020a, b; Aivazyan et al. 2022; Kann et al. 2023) observatories started on 2023 August 8-13T13:34:22, 0.77 d after $T_0$, and lasted for 38 d (Mao et al. 2023; Pyshna et al. 2023). In total, more than 20 professional telescopes and several amateur telescopes imaged the source.

GRB 230812B being a high-luminosity and (relatively) close-by burst ($z=0.36$) makes it a very worthwhile target of investigation of the GRB and its afterglow, the SN features, and the correlations between the two. To compute distances, absolute magnitudes from apparent magnitudes, etc., we use the Planck18 cosmological model from astropy (Planck Collaboration VII 2020); it adopts a flat cosmology with $H_0 = 67.66 \text{ km s}^{-1} \text{ Mpc}^{-1}$ and $\Omega_m = 0.310$. The observed redshift $z = 0.360$ then corresponds to a luminosity distance of 1981 Mpc; with the fluence $2.52 \times 10^{-4} \text{ erg cm}^{-2}$ given by Fermi/GBM (Roberts et al. 2023), we obtain the total isotropic gamma energy $E_{\gamma,iso} = 1.2 \times 10^{53} \text{ erg}$; and with the duration ($T_{90} = 3.26 \text{ s}$) we get the mean gamma-ray isotropic luminosity $L_{\gamma,iso} = (1+z)E_{\gamma,iso}/T_{90} = 4.9 \times 10^{52} \text{ erg s}^{-1}$. This makes this event one of the most luminous GRB-SN events ever recorded.

In this paper, we report observations by the GRANDMA network and its partners of the bright GRB 230812B and the supernova (named SN2023pel) that emerged in the light curve about five days after the burst onset. In Section 2, we present the observational data from more than two dozen instruments and the photometric methods we use. We also explore properties from the host galaxy (brightness, line-of-sight extinction). In Section 3, we analyse our multi-epoch spectra from the GRB afterglow to the confirmation of the presence of SN2023pel. In Section 4, we present the methods we applied in the analysis of the afterglow light curves, using both empirical fits and Bayesian inference. We then present our results on the astrophysical scenarios and processes using different jet structures that best describe the data, and compare SN properties with other GRB-associated supernovae. In Section 5, we present some general discussion and conclusions.

# 2 OBSERVATIONAL DATA

## 2.1 Swift XRT, UVOT

The X-ray light curve (0.3–10 keV) of GRB 230812B was acquired from the UK Swift Science Data Centre<fnref n="1" /> (Evans et al. 2007, 2009).

The data were extracted from the Burst Analyser<fnref n="2" /> (Evans et al. 2010), which provides the light curves and spectra of the [0.3–10] keV apparent flux, as well as the unabsorbed flux density at 10 keV in Jansky units. For the spectral energy distribution (SED) fitting to measure the dust from the galaxy (see sections below), the [0.3–10 keV] XRT data were grouped by 10 counts/bin using grppha, a subpackage from HEASOFT (version 6.31.1), for statistical purposes. For the other analyses, we performed a re-binning of the unabsorbed light curve at 10 keV by dividing the observations into eight non-continuous time windows. Among these, four windows contained a cluster of observations occurring within an hour or less, while the remaining four had a single data point each. For each cluster, we computed the mean value and standard deviation to produce data points in the light curve for the analysis. These values are reported in Table A1.

We retrieved images taken by the Ultraviolet/Optical Telescope (UVOT; Roming et al. 2005) from the Swift archive.<fnref n="3" /> The source was imaged using the broad-band white filter from 0.3 to 8.2 d. In all the images, we checked the effectiveness of the aspect correction. To address the excess broadening induced by pointing jitter from the aging attitude control system (Cenko 2023), a meticulous assessment of an early image was conducted to determine where the source counts merge into the background. To accommodate this, a slightly larger aperture of 7.5 arcsec was used for the source. All further images show that the source is contained in this aperture. Background measurements were obtained by analysing an annular region extending from 10 to 22 arcsec (after a careful background region positioning). The later images were summed to get a good signal-to-noise ratio in the usual way using the Ftool uvotmaghist.<fnref n="4" /> We then transformed the Vega magnitudes to AB magnitudes by adding 0.8 mag as is appropriate in white (Breeveld et al. 2011).

The late-time magnitude upper limits suggest that the host galaxy magnitude is faint, white $>23.2$. We tried deriving a near-UV magnitude for the host galaxy from earlier observations from the Galex gPhoton database (Million et al. 2016),<fnref n="5" /> but were unsuccessful in avoiding contamination by nearby stars. We eventually chose the magnitude $23.54 \pm 0.84$ in u-band from the Sloan Digital Sky Survey DR7 (Abazajian et al. 2009) as an approximation of the white contribution, making sure we propagated properly its very conservative error bars through flux subtraction. The UVOT values, corrected from this constant galaxy flux contribution and from Milky way extinction (see below), are reported in Table A2.

## 2.2 Optical data set

We conducted simultaneous observations with GRANDMA (Antier et al. 2020a), thanks to its operational platform SKYPORTAL (Coughlin et al. 2023), and with associated partners, from less than a day after the trigger time $T_0$ up to 38 d (see Fig. 1). Details on the observational campaign in the various networks can be found in the Appendix. From the images taken, we successfully extracted the photometry of the source and corrected it from the constant flux contribution of the host galaxy and from absorption by dust along the line of sight. The data set can be found in Table A2. Our preliminary analysis of the GRANDMA observations has been reported publicly in the General Coordinates Network (GCN)<fnref n="6" /> (Mao et al. 2023; Pyshna et al. 2023).

<footnote n="1">¹https://www.swift.ac.uk/</footnote>

<footnote n="2">²https://www.swift.ac.uk/burst_analyser/00021589/</footnote>

<footnote n="3">³https://swift.gsfc.nasa.gov</footnote>

<footnote n="4">⁴https://heasarc.gsfc.nasa.gov/ftools/</footnote>

<footnote n="5">⁵https://github.com/cmillion/gPhoton/blob/master/docs/UserGuide.md</footnote>

<footnote n="6">⁶https://gcn.nasa.gov/</footnote>
robotic telescopes network reported the optical counterpart at the same location (Lipunov et al. 2023b).

A series of photometric observations across the full electro-magnetic spectrum were conducted in the months following the trigger. Among them, we can cite as an example the Multi-purpose InSTRument for Astronomy at Low-resolution spectrometer (T193/MISTRAL) in optical (Amram et al. 2023; Adami et al. 2023a, b), the Italian 3.6 m TNG telescope in near-infrared, and the Northern extended millimeter array (NOEMA) in radio (de Ugarte Postigo et al. 2023b). Spectroscopic observations were also conducted in parallel. It led to the measurements of the transient's redshift: $z = 0.360$ (de Ugarte Postigo et al. 2023a). Twelve days later, observations using OSIRIS+ mounted on the Gran Telescopio Canarias (GTC) showed features in the spectrum characteristic of a GRB-SN event and matched with the spectrum of SN1998bw, indicating, rather conclusively, the presence of a supernova (Agui Fernandez et al. 2023; Agúñ Fernández et al. 2023).

Observations with GRANDMA (Global Rapid Advanced Network for Multimessenger Addicts: Antier et al. 2020a, b; Aivazyan et al. 2022; Kann et al. 2023) observatories started on 2023 August 8-13T13:34:22, 0.77 d after $T_0$, and lasted for 38 d (Mao et al. 2023; Pyshna et al. 2023). In total, more than 20 professional telescopes and several amateur telescopes imaged the source.

GRB 230812B being a high-luminosity and (relatively) close-by burst ($z=0.36$) makes it a very worthwhile target of investigation of the GRB and its afterglow, the SN features, and the correlations between the two. To compute distances, absolute magnitudes from apparent magnitudes, etc., we use the Planck18 cosmological model from astropy (Planck Collaboration VII 2020); it adopts a flat cosmology with $H_0 = 67.66 \text{ km s}^{-1} \text{ Mpc}^{-1}$ and $\Omega_m = 0.310$. The observed redshift $z = 0.360$ then corresponds to a luminosity distance of 1981 Mpc; with the fluence $2.52 \times 10^{-4} \text{ erg cm}^{-2}$ given by Fermi/GBM (Roberts et al. 2023), we obtain the total isotropic gamma energy $E_{\gamma,iso} = 1.2 \times 10^{53} \text{ erg}$; and with the duration ($T_{90} = 3.26 \text{ s}$) we get the mean gamma-ray isotropic luminosity $L_{\gamma,iso} = (1+z)E_{\gamma,iso}/T_{90} = 4.9 \times 10^{52} \text{ erg s}^{-1}$. This makes this event one of the most luminous GRB-SN events ever recorded.

In this paper, we report observations by the GRANDMA network and its partners of the bright GRB 230812B and the supernova (named SN2023pel) that emerged in the light curve about five days after the burst onset. In Section 2, we present the observational data from more than two dozen instruments and the photometric methods we use. We also explore properties from the host galaxy (brightness, line-of-sight extinction). In Section 3, we analyse our multi-epoch spectra from the GRB afterglow to the confirmation of the presence of SN2023pel. In Section 4, we present the methods we applied in the analysis of the afterglow light curves, using both empirical fits and Bayesian inference. We then present our results on the astrophysical scenarios and processes using different jet structures that best describe the data, and compare SN properties with other GRB-associated supernovae. In Section 5, we present some general discussion and conclusions.

# 2 OBSERVATIONAL DATA

## 2.1 Swift XRT, UVOT

The X-ray light curve (0.3–10 keV) of GRB 230812B was acquired from the UK Swift Science Data Centre<fnref n="1" /> (Evans et al. 2007, 2009).

The data were extracted from the Burst Analyser<fnref n="2" /> (Evans et al. 2010), which provides the light curves and spectra of the [0.3–10] keV apparent flux, as well as the unabsorbed flux density at 10 keV in Jansky units. For the spectral energy distribution (SED) fitting to measure the dust from the galaxy (see sections below), the [0.3–10 keV] XRT data were grouped by 10 counts/bin using grppha, a subpackage from HEASOFT (version 6.31.1), for statistical purposes. For the other analyses, we performed a re-binning of the unabsorbed light curve at 10 keV by dividing the observations into eight non-continuous time windows. Among these, four windows contained a cluster of observations occurring within an hour or less, while the remaining four had a single data point each. For each cluster, we computed the mean value and standard deviation to produce data points in the light curve for the analysis. These values are reported in Table A1.

We retrieved images taken by the Ultraviolet/Optical Telescope (UVOT; Roming et al. 2005) from the Swift archive.<fnref n="3" /> The source was imaged using the broad-band white filter from 0.3 to 8.2 d. In all the images, we checked the effectiveness of the aspect correction. To address the excess broadening induced by pointing jitter from the aging attitude control system (Cenko 2023), a meticulous assessment of an early image was conducted to determine where the source counts merge into the background. To accommodate this, a slightly larger aperture of 7.5 arcsec was used for the source. All further images show that the source is contained in this aperture. Background measurements were obtained by analysing an annular region extending from 10 to 22 arcsec (after a careful background region positioning). The later images were summed to get a good signal-to-noise ratio in the usual way using the Ftool uvotmaghist.<fnref n="4" /> We then transformed the Vega magnitudes to AB magnitudes by adding 0.8 mag as is appropriate in white (Breeveld et al. 2011).

The late-time magnitude upper limits suggest that the host galaxy magnitude is faint, white $>23.2$. We tried deriving a near-UV magnitude for the host galaxy from earlier observations from the Galex gPhoton database (Million et al. 2016),<fnref n="5" /> but were unsuccessful in avoiding contamination by nearby stars. We eventually chose the magnitude $23.54 \pm 0.84$ in u-band from the Sloan Digital Sky Survey DR7 (Abazajian et al. 2009) as an approximation of the white contribution, making sure we propagated properly its very conservative error bars through flux subtraction. The UVOT values, corrected from this constant galaxy flux contribution and from Milky way extinction (see below), are reported in Table A2.

## 2.2 Optical data set

We conducted simultaneous observations with GRANDMA (Antier et al. 2020a), thanks to its operational platform SKYPORTAL (Coughlin et al. 2023), and with associated partners, from less than a day after the trigger time $T_0$ up to 38 d (see Fig. 1). Details on the observational campaign in the various networks can be found in the Appendix. From the images taken, we successfully extracted the photometry of the source and corrected it from the constant flux contribution of the host galaxy and from absorption by dust along the line of sight. The data set can be found in Table A2. Our preliminary analysis of the GRANDMA observations has been reported publicly in the General Coordinates Network (GCN)<fnref n="6" /> (Mao et al. 2023; Pyshna et al. 2023).

<footnote n="1">¹https://www.swift.ac.uk/</footnote>

<footnote n="2">²https://www.swift.ac.uk/burst_analyser/00021589/</footnote>

<footnote n="3">³https://swift.gsfc.nasa.gov</footnote>

<footnote n="4">⁴https://heasarc.gsfc.nasa.gov/ftools/</footnote>

<footnote n="5">⁵https://github.com/cmillion/gPhoton/blob/master/docs/UserGuide.md</footnote>

<footnote n="6">⁶https://gcn.nasa.gov/</footnote>
<figure><img src="image_2.png" /><figcaption>**Figure 1.** Top: Observations from this work in *g*', *r*'-, *i*'-, and *z*-band (observer frame times). Apparent magnitudes before correction by host galaxy flux or for the Milky Way foreground extinction; coloured filled regions with arbitrary errorbars 0.2 mag wide have been added to ease the visualization of the light curves. Bottom: Multiband (X-ray to IR) light curves, corrected from host galaxy flux and the Milky Way foreground extinction. In grey are power laws fit to the data points up to *T*₀ + 5 d (see Section 4.1).</figcaption></figure>

2.2.1 Photometry

Prior to photometry, all images were pre-processed in a telescope-
specific way with bias and dark subtraction and flat-fielding. We
manually masked the regions of the images containing significant
imaging artefacts or regions not fully corrected by the pre-processing.
Also, we derived astrometric solutions for the images where telescope

pipelines did not provide them by using the Astrometry.net service
(Lang et al. 2010).

In order to increase the signal-to-noise ratio of the images, we resampled and coadded individual frames using the SWARP software (Bertin 2010) for sequences of images acquired on the same telescope within a short interval of time. Then, we performed the forced photometry at the transient position using STDPIPE (Karpov 2021), a set of Python codes for performing astrometry, photometry, and transient detection tasks on optical images, in the same way as Kann et al. (2023).

In order to simplify the analysis and quality checking of the heterogeneous set of images from different telescopes, and to keep track of the results, we created a dedicated web-based application, STDWEB,<fnref n="7" /> which acts as a web interface to the STDPIPE library and provides a user-friendly way to perform all steps of its data processing, from masking bad regions to image subtraction, with thorough checking of the intermediate results of every step, and then adjusting the settings in order to acquire optimal photometry results. It also contains some heuristics for the selection of an optimal aperture radius and an optimal selection of reference photometric catalogue, refining the astrometric solution as needed, etc.

Specifically, for the photometry on all images, we used an aperture radius equal to the mean full-width at half-maximum (FWHM) value estimated over all point-like sources in each image. For photometric calibration, we used the Pan-STARRS DR1 catalogue (Flewelling et al. 2020) for processing the images acquired in filters close to the Sloan system. We used a spatially variable photometric zero-point model represented as a second-order spatial polynomial in order to compensate for the effects of improper flat-fielding, image vignetting, and positionally dependent aperture correction (e.g. due to PSF shape variations). We first performed the analysis taking into account the linear colour term (using *g* − *r* for Sloan-like filters) in order to assess how much the individual photometric system of the image deviates from the catalogue one. Then, if the colour term is negligible (e.g. smaller than 0.1), we re-run the analysis of the image without the colour term, thus directly deriving the measurement in catalogue photometric system. If the colour term is significant, we kept it in the analysis and corrected the measurement using the known colour of the transient.

When the signal-to-noise ratio obtained with the forced photom-
etry is below 5, we derive an upper limit for it by multiplying the
background noise inside the aperture by 5, and converting this flux
value to magnitudes. For images taken too close to each other (on a
logarithmic time-scale), we only selected the one with the best signal-
to-noise ratio. Images with a sensitivity too low (>>1.5 apparent
magnitude brighter than nearby measurements) were excluded from
the data analysis. Images which, after subtraction of the galaxy's
constant flux, give a larger error bar than 0.5, were also excluded
from our data set for this analysis.

In parallel, the image reduction for *J* and *K* bands was carried out using the *jitter* task of the ESO-eclipse package.<fnref n="8" /> Astrometry was performed using the 2MASS<fnref n="9" /> catalogue. Aperture photometry was performed using the Starlink PHOTOM package.<fnref n="10" /> To minimize any systematic effect, we performed differential photometry with respect to a selection of local isolated and non-saturated reference stars from the UKIDSS<fnref n="11" /> survey.

<footnote n="7">⁷Accessible at http://stdweb.favor2.info</footnote>

<footnote n="8">⁸https://www.eso.org/sci/software/eclipse/</footnote>

<footnote n="9">⁹https://irsa.ipac.caltech.edu/Missions/2mass.html</footnote>

<footnote n="10">¹⁰http://www.starlink.ac.uk/docs/sun45.htx/sun45.html</footnote>

<footnote n="11">¹¹http://www.ukidss.org/</footnote>
<figure><img src="image_2.png" /><figcaption>**Figure 1.** Top: Observations from this work in *g*', *r*'-, *i*'-, and *z*-band (observer frame times). Apparent magnitudes before correction by host galaxy flux or for the Milky Way foreground extinction; coloured filled regions with arbitrary errorbars 0.2 mag wide have been added to ease the visualization of the light curves. Bottom: Multiband (X-ray to IR) light curves, corrected from host galaxy flux and the Milky Way foreground extinction. In grey are power laws fit to the data points up to *T*₀ + 5 d (see Section 4.1).</figcaption></figure>

2.2.1 Photometry

Prior to photometry, all images were pre-processed in a telescope-
specific way with bias and dark subtraction and flat-fielding. We
manually masked the regions of the images containing significant
imaging artefacts or regions not fully corrected by the pre-processing.
Also, we derived astrometric solutions for the images where telescope

pipelines did not provide them by using the Astrometry.net service
(Lang et al. 2010).

In order to increase the signal-to-noise ratio of the images, we resampled and coadded individual frames using the SWARP software (Bertin 2010) for sequences of images acquired on the same telescope within a short interval of time. Then, we performed the forced photometry at the transient position using STDPIPE (Karpov 2021), a set of Python codes for performing astrometry, photometry, and transient detection tasks on optical images, in the same way as Kann et al. (2023).

In order to simplify the analysis and quality checking of the heterogeneous set of images from different telescopes, and to keep track of the results, we created a dedicated web-based application, STDWEB,<fnref n="7" /> which acts as a web interface to the STDPIPE library and provides a user-friendly way to perform all steps of its data processing, from masking bad regions to image subtraction, with thorough checking of the intermediate results of every step, and then adjusting the settings in order to acquire optimal photometry results. It also contains some heuristics for the selection of an optimal aperture radius and an optimal selection of reference photometric catalogue, refining the astrometric solution as needed, etc.

Specifically, for the photometry on all images, we used an aperture radius equal to the mean full-width at half-maximum (FWHM) value estimated over all point-like sources in each image. For photometric calibration, we used the Pan-STARRS DR1 catalogue (Flewelling et al. 2020) for processing the images acquired in filters close to the Sloan system. We used a spatially variable photometric zero-point model represented as a second-order spatial polynomial in order to compensate for the effects of improper flat-fielding, image vignetting, and positionally dependent aperture correction (e.g. due to PSF shape variations). We first performed the analysis taking into account the linear colour term (using *g* − *r* for Sloan-like filters) in order to assess how much the individual photometric system of the image deviates from the catalogue one. Then, if the colour term is negligible (e.g. smaller than 0.1), we re-run the analysis of the image without the colour term, thus directly deriving the measurement in catalogue photometric system. If the colour term is significant, we kept it in the analysis and corrected the measurement using the known colour of the transient.

When the signal-to-noise ratio obtained with the forced photom-
etry is below 5, we derive an upper limit for it by multiplying the
background noise inside the aperture by 5, and converting this flux
value to magnitudes. For images taken too close to each other (on a
logarithmic time-scale), we only selected the one with the best signal-
to-noise ratio. Images with a sensitivity too low (>1.5 apparent
magnitude brighter than nearby measurements) were excluded from
the data analysis. Images which, after subtraction of the galaxy's
constant flux, give a larger error bar than 0.5, were also excluded
from our data set for this analysis.

In parallel, the image reduction for *J* and *K* bands was carried out using the *jitter* task of the ESO-eclipse package.<fnref n="8" /> Astrometry was performed using the 2MASS<fnref n="9" /> catalogue. Aperture photometry was performed using the Starlink PHOTOM package.<fnref n="10" /> To minimize any systematic effect, we performed differential photometry with respect to a selection of local isolated and non-saturated reference stars from the UKIDSS<fnref n="11" /> survey.

<footnote n="7">⁷Accessible at http://stdweb.favor2.info</footnote>

<footnote n="8">⁸https://www.eso.org/sci/software/eclipse/</footnote>

<footnote n="9">⁹https://irsa.ipac.caltech.edu/Missions/2mass.html</footnote>

<footnote n="10">¹⁰http://www.starlink.ac.uk/docs/sun45.htx/sun45.html</footnote>

<footnote n="11">¹¹http://www.ukidss.org/</footnote>
<table><caption>**Table 1.** Apparent magnitudes of the host galaxy used for flux subtraction and the Milky Way (MW) extinction in the line of sight in different filters.</caption><thead><tr><th rowspan="2">Filter</th><th colspan="2">Host galaxy contribution</th><th rowspan="2">MW extinction</th></tr><tr><th>Magnitude</th><th>Error</th></tr></thead><tbody><tr><td>u: white</td><td>23.54 (AB)</td><td>0.84</td><td>0.099</td></tr><tr><td>g'</td><td>23.78 (AB)</td><td>0.12</td><td>0.077</td></tr><tr><td>r'</td><td>22.83 (AB)</td><td>0.10</td><td>0.053</td></tr><tr><td>i'</td><td>22.54 (AB)</td><td>0.12</td><td>0.040</td></tr><tr><td>z'</td><td>22.34 (AB)</td><td>0.12</td><td>0.029</td></tr><tr><td>J</td><td>21.82 (AB)</td><td>0.32</td><td>0.017</td></tr><tr><td>K</td><td>-</td><td></td><td>0.007</td></tr></tbody></table>

### 2.2.2 Host galaxy properties

The host galaxy of GRB 230812B is SDSS J163631.47+475131.8, with measurements available in SDSS DR16 (Ahumada et al. 2020), but its photometry there is marked as unreliable. The host galaxy's redshift $z = 0.36$ was determined through GTC spectroscopic observations of emission lines (de Ugarte Postigo et al. 2023a). We studied its brightness, both for host flux subtraction and spectral analysis.

Constant flux from the host at the location of GRB 230812B – To better characterize the host galaxy flux, we acquired the data for the GRB position from archival Pan-STARRS DR1 (Waters et al. 2020) images in $i'$ filters, and from the DESI Legacy Surveys DR10 (Dey et al. 2019) stacked image in $g'$, $r'$, and $z'$ filters. We then performed forced photometry on these images, on the same apertures and with the same parameters as used above for the reduction of the data set. To convert Legacy Survey measurements to the Pan-STARRS photometric system, we estimated the colour term<fnref n="12" /> while calibrating these images. For the $g'$ filter, this happened to be negligible, but for $r'$ and $z'$, we used the following equations:

$$r' - 0.11 * (g' - r') = 22.73 \pm 0.07$$

$$z' - 0.11 * (r' - i') = 22.31 \pm 0.11,$$

where the magnitudes $g'$, $r'$, $i'$, $z'$ correspond to the Pan-STARRS system. To extract $r'$ and $z'$, we used the $g'$ values estimated from the Legacy Survey image, and $i'$ values from Pan-STARRS image. The results are summarized in Table 1. These host flux contributions were then subtracted from the apparent flux to obtain the transient flux, combining the flux errors from the apparent magnitude and the host contribution to obtain the errors on the host-subtracted flux.

In *J* and *K* filters, there are to our knowledge no NIR detections of the host in available survey catalogues. We obtained a deep late-time *J*-band observation at $T_0 + 60$ d using the TNG telescope, finding a magnitude of $20.91 \pm 0.32$ (Vega), i.e. $21.82$ (AB). This approximate host galaxy contribution could then be subtracted from the other TNG *J* images. Unfortunately, no late-time imaging in *K*-band could be performed, so no host contribution could be estimated in this filter.

Star formation rate from the host galaxy – Using these host flux contributions as approximations for the observed magnitude of the galaxy as a whole, we apply the CIGALE<fnref n="13" /> code (Boquien et al. 2019) to study the spectral energy distribution (SED) of the galaxy. This analysis constrains the model parameter space to a mass $M = (1.99 \pm 0.54) \times 10^9$ M$_\odot$, a star formation rate (on the last 10 Myr) SFR = $0.17 \pm 0.07$ M$_\odot$yr$^{-1}$, and an attenuation $A_V = 0.09 \pm 0.06$

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Spectrum of the best-fitting host galaxy model in CIGALE, constrained by our estimations in *ugriz* and *J* bands.</figcaption></figure>

mag. We show the best-fitting spectrum in Fig. 2. However, one should keep in mind that we are effectively considering the flux of the host galaxy within the aperture size of the transient (a few arcseconds because of point spread of the instruments; to be compared with the 5 kpc arcsec$^{-1}$ scale at $z \simeq 0.36$), and are thus missing a fraction of the galaxy, underestimating the flux by an unknown amount that may bias these galaxy parameters. The SFR is especially hard to constrain without more UV data, so its uncertainty provided here is likely underestimated.

### 2.2.3 Line-of-sight extinction

**Milky Way (MW) extinction:** We corrected the UV, *griz*, *J*, and *K* bands from the MW extinction values from Schlafly & Finkbeiner (2011), computed along the line of sight by the NED calculator.<fnref n="14" /> These corrections are reported in Table 1.

**Host galaxy dust extinction:** To estimate the extinction suffered by the afterglow due to the host galaxy dust, we created a spectral energy distribution (SED) from X-ray to optical at two epochs: $T_0 + 2.2$ d, corresponding to the quasi-simultaneity of the *whitegriz* bands, and at $T_0 + 4$ d, to include observations from the *J*, *K* bands; as no quasi-simultaneous observation was available at this epoch for *griJ*, the photometric points were estimated through interpolations. We considered the typical extinction curves of MW, Large Magellanic Cloud, and Small Magellanic Cloud of Pei (1992), which gave similar results.

We report the results obtained with the average SMC dust extinction law. For each epoch, the intrinsic spectrum was modelled with a single or broken power law using the afterglow theory outlined in Sari, Piran & Narayan (1998). For the broken power law, the difference in slope between X-ray and NIR wavelengths was set to $\Delta\beta = \beta_X - \beta_o = 0.5$, which corresponds to the change in slope due to the cooling break. For both epochs, the best fit of the X-ray/NIR SED is obtained with a single power law, and the measured dust extinction $A_V$ is compatible with zero (see Table 2). The higher uncertainty in $A_V$ for $T_0 + 4$ d is due to higher uncertainties in the *J*- and *K*-band observed fluxes. The best fits of the SED at both epochs are shown in Fig. 3.

<footnote n="12">¹²The colour term *C* here defines the instrumental photometric system through catalogue magnitude and colour as $m_{instr} = m_{cat} + C \cdot \text{colour}_{cat}$ and may be fitted during the photometric calibration of the image.</footnote>

<footnote n="13">¹³https://cigale.lam.fr/</footnote>

<footnote n="14">¹⁴http://ned.ipac.caltech.edu/forms/calculator.html</footnote>
<table><caption>**Table 1.** Apparent magnitudes of the host galaxy used for flux subtraction and the Milky Way (MW) extinction in the line of sight in different filters.</caption><thead><tr><th rowspan="2">Filter</th><th colspan="2">Host galaxy contribution</th><th rowspan="2">MW extinction</th></tr><tr><th>Magnitude</th><th>Error</th></tr></thead><tbody><tr><td>u: white</td><td>23.54 (AB)</td><td>0.84</td><td>0.099</td></tr><tr><td>g'</td><td>23.78 (AB)</td><td>0.12</td><td>0.077</td></tr><tr><td>r'</td><td>22.83 (AB)</td><td>0.10</td><td>0.053</td></tr><tr><td>i'</td><td>22.54 (AB)</td><td>0.12</td><td>0.040</td></tr><tr><td>z'</td><td>22.34 (AB)</td><td>0.12</td><td>0.029</td></tr><tr><td>J</td><td>21.82 (AB)</td><td>0.32</td><td>0.017</td></tr><tr><td>K</td><td>-</td><td></td><td>0.007</td></tr></tbody></table>

### 2.2.2 Host galaxy properties

The host galaxy of GRB 230812B is SDSS J163631.47+475131.8, with measurements available in SDSS DR16 (Ahumada et al. 2020), but its photometry there is marked as unreliable. The host galaxy’s redshift $z = 0.36$ was determined through GTC spectroscopic observations of emission lines (de Ugarte Postigo et al. 2023a). We studied its brightness, both for host flux subtraction and spectral analysis.

Constant flux from the host at the location of GRB 230812B – To better characterize the host galaxy flux, we acquired the data for the GRB position from archival Pan-STARRS DR1 (Waters et al. 2020) images in $i'$ filters, and from the DESI Legacy Surveys DR10 (Dey et al. 2019) stacked image in $g'$, $r'$, and $z'$ filters. We then performed forced photometry on these images, on the same apertures and with the same parameters as used above for the reduction of the data set. To convert Legacy Survey measurements to the Pan-STARRS photometric system, we estimated the colour term<fnref n="12" /> while calibrating these images. For the $g'$ filter, this happened to be negligible, but for $r'$ and $z'$, we used the following equations:

$$r' - 0.11 * (g' - r') = 22.73 \pm 0.07$$

$$z' - 0.11 * (r' - i') = 22.31 \pm 0.11,$$

where the magnitudes $g'$, $r'$, $i'$, $z'$ correspond to the Pan-STARRS system. To extract $r'$ and $z'$, we used the $g'$ values estimated from the Legacy Survey image, and $i'$ values from Pan-STARRS image. The results are summarized in Table 1. These host flux contributions were then subtracted from the apparent flux to obtain the transient flux, combining the flux errors from the apparent magnitude and the host contribution to obtain the errors on the host-subtracted flux.

In $J$ and $K$ filters, there are to our knowledge no NIR detections of the host in available survey catalogues. We obtained a deep late-time $J$-band observation at $T_0 + 60$ d using the TNG telescope, finding a magnitude of $20.91 \pm 0.32$ (Vega), i.e. $21.82$ (AB). This approximate host galaxy contribution could then be subtracted from the other TNG $J$ images. Unfortunately, no late-time imaging in $K$-band could be performed, so no host contribution could be estimated in this filter.

Star formation rate from the host galaxy – Using these host flux contributions as approximations for the observed magnitude of the galaxy as a whole, we apply the CIGALE<fnref n="13" /> code (Boquien et al. 2019) to study the spectral energy distribution (SED) of the galaxy. This analysis constrains the model parameter space to a mass $M = (1.99 \pm 0.54) \times 10^9$ M$_\odot$, a star formation rate (on the last 10 Myr) SFR = $0.17 \pm 0.07$ M$_\odot$yr$^{-1}$, and an attenuation $A_V = 0.09 \pm 0.06$

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Spectrum of the best-fitting host galaxy model in CIGALE, constrained by our estimations in *ugriz* and $J$ bands.</figcaption></figure>

mag. We show the best-fitting spectrum in Fig. 2. However, one should keep in mind that we are effectively considering the flux of the host galaxy within the aperture size of the transient (a few arcseconds because of point spread of the instruments; to be compared with the 5 kpc arcsec$^{-1}$ scale at $z \simeq 0.36$), and are thus missing a fraction of the galaxy, underestimating the flux by an unknown amount that may bias these galaxy parameters. The SFR is especially hard to constrain without more UV data, so its uncertainty provided here is likely underestimated.

### 2.2.3 Line-of-sight extinction

**Milky Way (MW) extinction:** We corrected the UV, *griz*, $J$, and $K$ bands from the MW extinction values from Schlafly & Finkbeiner (2011), computed along the line of sight by the NED calculator.<fnref n="14" /> These corrections are reported in Table 1.

**Host galaxy dust extinction:** To estimate the extinction suffered by the afterglow due to the host galaxy dust, we created a spectral energy distribution (SED) from X-ray to optical at two epochs: $T_0 + 2.2$ d, corresponding to the quasi-simultaneity of the *whitegriz* bands, and at $T_0 + 4$ d, to include observations from the $J$, $K$ bands; as no quasi-simultaneous observation was available at this epoch for *griJ*, the photometric points were estimated through interpolations. We considered the typical extinction curves of MW, Large Magellanic Cloud, and Small Magellanic Cloud of Pei (1992), which gave similar results.

We report the results obtained with the average SMC dust extinction law. For each epoch, the intrinsic spectrum was modelled with a single or broken power law using the afterglow theory outlined in Sari, Piran & Narayan (1998). For the broken power law, the difference in slope between X-ray and NIR wavelengths was set to $\Delta\beta = \beta_X - \beta_o = 0.5$, which corresponds to the change in slope due to the cooling break. For both epochs, the best fit of the X-ray/NIR SED is obtained with a single power law, and the measured dust extinction $A_V$ is compatible with zero (see Table 2). The higher uncertainty in $A_V$ for $T_0 + 4$ d is due to higher uncertainties in the $J$- and $K$-band observed fluxes. The best fits of the SED at both epochs are shown in Fig. 3.

<footnote n="12">¹²The colour term $C$ here defines the instrumental photometric system through catalogue magnitude and colour as $m_{instr} = m_{cat} + C \cdot \text{colour}_{cat}$ and may be fitted during the photometric calibration of the image.</footnote>

<footnote n="13">¹³https://cigale.lam.fr/</footnote>

<footnote n="14">¹⁴http://ned.ipac.caltech.edu/forms/calculator.html</footnote>
<table><caption>**Table 2.** Results of the spectral analysis for both epochs.</caption><thead><tr><th>Epoch</th><th>A<sub>V</sub> (mag)</th><th>β</th><th>χ<sup>2</sup> (dof)</th></tr></thead><tbody><tr><td>T<sub>0</sub> + 2.2 d</td><td>0.0 ± 0.075</td><td>0.710 ± 0.027</td><td>19.269 (7)</td></tr><tr><td>T<sub>0</sub> + 4 d</td><td>0.0 ± 0.185</td><td>0.712 ± 0.036</td><td>4.773 (7)</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Figure 3.** X-ray to NIR SED of the afterglow of GRB 230812B at $T_0 + 2.2$ d and $T_0 + 4$ d (observer-frame times). The dashed lines correspond to the best-fitting intrinsic model (single power law). The solid lines illustrate the best fit to the data, including the absorption in the X-ray. The 0.3–10 keV XRT spectrum extracted around $T_0 + 2.2$ d has been rescaled and used for the SED at $T_0 + 4$ d.</figcaption></figure>

The $T_0 + 2.2$ d SED constrains best the host galaxy dust extinction as $A_V = 0.0 \pm 0.075$ mag, corresponding to a reddening of $E(B-V) = 0.0 \pm 0.026$ mag for the average SMC model with $R_V = 2.93$ (this constraint is tighter than but compatible with the upper limit $E(B-V) < 0.07$ mag ($3\sigma$) in Srinivasaragavan et al. (2024). This is consistent with the CIGALE analysis finding a very low global attenuation. We thus chose not to apply any additional extinction correction to the photometric points in Table A2.

## 2.3 Radio

We also added to our data set two unique submillimetre measurements from NOEMA, taken 3.8 d post $T_0$: see a brief description of the analysis in de Ugarte Postigo et al. (2023b). To complete our multiwavelength data set at lower energies, we gathered the published results of radio observations of GRB230812B starting two days after $T_0$ and covering different radio bands from 1 to 15.5 GHz. We use the data from the Arcminute Microkelvin Imager Large-Array (Rhodes et al. 2023), the Karl G. Jansky Very Large Array (Chandra et al. 2023; Giarratana et al. 2023), and the upgraded Giant Meterwave Radio Telescope (Mohnani et al. 2023). These data are summarized in Table A1. No correction from the host constant flux and extinction were applied to these measurements.

## 3 SPECTRAL ANALYSIS

We performed spectroscopy of the optical counterpart of GRB 230812B on 3 epochs using OSIRIS+ (Cepa et al. 2000) on the 10.4 m Gran Telescopio Canarias (GTC) (see details in the appendix). These spectra, together with the host galaxy model derived from the SED fit are shown in Fig. 4.

<figure><img src="image_5.png" /><figcaption>**Figure 4.** Spectra of GRB 230812B obtained with OSIRIS+. At 1.1 d the emission was dominated by the afterglow, with a simple power-law continuum with absorption lines from the line of sight and emission lines from the host. At 12 and 15 d the supernova component is responsible for most of the emission, with little evolution between the two epochs. We have plotted the host galaxy spectrum derived from the SED fit to understand its contribution to the observations.</figcaption></figure>

<table><caption>**Table 3.** Identification and equivalent width of the spectral features observed in the afterglow spectrum.</caption><thead><tr><th>Feature</th><th>Obs. wavelength<br>Å</th><th>EW<br>Å</th></tr></thead><tbody><tr><td>Mg II</td><td>3801.01</td><td>2.55 ± 0.34</td></tr><tr><td>Mg II</td><td>3811.40</td><td>1.76 ± 0.27</td></tr><tr><td>Mg I</td><td>3878.76</td><td>2.40 ± 0.29</td></tr><tr><td>[O II]/[O I]</td><td>5073.53</td><td>-2.26 ± 0.15</td></tr><tr><td>Ca II</td><td>5353.00</td><td>1.70 ± 0.16</td></tr><tr><td>Ca II</td><td>5401.00</td><td>1.52 ± 0.15</td></tr><tr><td>Ca I</td><td>5753.43</td><td>1.23 ± 0.15</td></tr><tr><td>H-beta</td><td>6614.73</td><td>-0.93 ± 0.17</td></tr><tr><td>[O III]</td><td>6750.73</td><td>-0.74 ± 0.16</td></tr><tr><td>[O III]</td><td>6813.99</td><td>-1.83 ± 0.15</td></tr></tbody></table>

The first epoch was obtained 1.1 d after the GRB, when the strong continuum was dominated by the power law, synchrotron emission of the afterglow. As already mentioned by de Ugarte Postigo et al. (2023a), the spectrum shows a strong trace with both emission and absorption lines which we identify as Mg II, Mg I, Ca II, Ca I in absorption, and [O II] and [O III] in emission, at an average redshift of $0.3602 \pm 0.0006$, which we identified as the refined redshift of the GRB. The spectral features and their equivalent widths (EW) are displayed in Table 3. The emission line EWs do not carry much information due to the varying continuum, but the absorption features tell us about the line of sight to the GRB within its own host galaxy. We can calculate the line strength parameter as proposed by de Ugarte Postigo et al. (2012), which determines the strength of the features as compared to a large sample of afterglows. The line of sight towards GRB 230812B displays a line strength parameter of LSP = $0.15 \pm 0.16$, indicating that the features are just slightly stronger than the average of the sample (percentile 60 of the sample). The only significant difference with respect to the typical GRB spectrum is the relative strength of Mg I with respect to Mg II. In our case Mg I, is relatively strong, implying that the host galaxy of GRB 230812B is likely to have a low-ionized interstellar environment.

The other two epochs (12.12 and 15.12 d post $T_0$) show similar, broad features typical of broad-line Ic supernovae. The second epoch
<table><caption>**Table 2.** Results of the spectral analysis for both epochs.</caption><thead><tr><th>Epoch</th><th>A<sub>V</sub> (mag)</th><th>β</th><th>χ<sup>2</sup> (dof)</th></tr></thead><tbody><tr><td>T<sub>0</sub> + 2.2 d</td><td>0.0 ± 0.075</td><td>0.710 ± 0.027</td><td>19.269 (7)</td></tr><tr><td>T<sub>0</sub> + 4 d</td><td>0.0 ± 0.185</td><td>0.712 ± 0.036</td><td>4.773 (7)</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Figure 3.** X-ray to NIR SED of the afterglow of GRB 230812B at $T_0 + 2.2$ d and $T_0 + 4$ d (observer-frame times). The dashed lines correspond to the best-fitting intrinsic model (single power law). The solid lines illustrate the best fit to the data, including the absorption in the X-ray. The 0.3–10 keV XRT spectrum extracted around $T_0 + 2.2$ d has been rescaled and used for the SED at $T_0 + 4$ d.</figcaption></figure>

The $T_0 + 2.2$ d SED constrains best the host galaxy dust extinction as $A_V = 0.0 \pm 0.075$ mag, corresponding to a reddening of $E(B-V) = 0.0 \pm 0.026$ mag for the average SMC model with $R_V = 2.93$ (this constraint is tighter than but compatible with the upper limit $E(B-V) < 0.07$ mag ($3\sigma$) in Srinivasaragavan et al. (2024). This is consistent with the CIGALE analysis finding a very low global attenuation. We thus chose not to apply any additional extinction correction to the photometric points in Table A2.

## 2.3 Radio

We also added to our data set two unique submillimetre measurements from NOEMA, taken 3.8 d post $T_0$: see a brief description of the analysis in de Ugarte Postigo et al. (2023b). To complete our multiwavelength data set at lower energies, we gathered the published results of radio observations of GRB230812B starting two days after $T_0$ and covering different radio bands from 1 to 15.5 GHz. We use the data from the Arcminute Microkelvin Imager Large-Array (Rhodes et al. 2023), the Karl G. Jansky Very Large Array (Chandra et al. 2023; Giarratana et al. 2023), and the upgraded Giant Meterwave Radio Telescope (Mohnani et al. 2023). These data are summarized in Table A1. No correction from the host constant flux and extinction were applied to these measurements.

## 3 SPECTRAL ANALYSIS

We performed spectroscopy of the optical counterpart of GRB 230812B on 3 epochs using OSIRIS+ (Cepa et al. 2000) on the 10.4 m Gran Telescopio Canarias (GTC) (see details in the appendix). These spectra, together with the host galaxy model derived from the SED fit are shown in Fig. 4.

<figure><img src="image_5.png" /><figcaption>**Figure 4.** Spectra of GRB 230812B obtained with OSIRIS+. At 1.1 d the emission was dominated by the afterglow, with a simple power-law continuum with absorption lines from the line of sight and emission lines from the host. At 12 and 15 d the supernova component is responsible for most of the emission, with little evolution between the two epochs. We have plotted the host galaxy spectrum derived from the SED fit to understand its contribution to the observations.</figcaption></figure>

<table><caption>**Table 3.** Identification and equivalent width of the spectral features observed in the afterglow spectrum.</caption><thead><tr><th>Feature</th><th>Obs. wavelength<br>Å</th><th>EW<br>Å</th></tr></thead><tbody><tr><td>Mg II</td><td>3801.01</td><td>2.55 ± 0.34</td></tr><tr><td>Mg II</td><td>3811.40</td><td>1.76 ± 0.27</td></tr><tr><td>Mg I</td><td>3878.76</td><td>2.40 ± 0.29</td></tr><tr><td>[O II]/[O I]</td><td>5073.53</td><td>-2.26 ± 0.15</td></tr><tr><td>Ca II</td><td>5353.00</td><td>1.70 ± 0.16</td></tr><tr><td>Ca II</td><td>5401.00</td><td>1.52 ± 0.15</td></tr><tr><td>Ca I</td><td>5753.43</td><td>1.23 ± 0.15</td></tr><tr><td>H-beta</td><td>6614.73</td><td>-0.93 ± 0.17</td></tr><tr><td>[O III]</td><td>6750.73</td><td>-0.74 ± 0.16</td></tr><tr><td>[O III]</td><td>6813.99</td><td>-1.83 ± 0.15</td></tr></tbody></table>

The first epoch was obtained 1.1 d after the GRB, when the strong continuum was dominated by the power law, synchrotron emission of the afterglow. As already mentioned by de Ugarte Postigo et al. (2023a), the spectrum shows a strong trace with both emission and absorption lines which we identify as Mg II, Mg I, Ca II, Ca I in absorption, and [O II] and [O III] in emission, at an average redshift of $0.3602 \pm 0.0006$, which we identified as the refined redshift of the GRB. The spectral features and their equivalent widths (EW) are displayed in Table 3. The emission line EWs do not carry much information due to the varying continuum, but the absorption features tell us about the line of sight to the GRB within its own host galaxy. We can calculate the line strength parameter as proposed by de Ugarte Postigo et al. (2012), which determines the strength of the features as compared to a large sample of afterglows. The line of sight towards GRB 230812B displays a line strength parameter of LSP = $0.15 \pm 0.16$, indicating that the features are just slightly stronger than the average of the sample (percentile 60 of the sample). The only significant difference with respect to the typical GRB spectrum is the relative strength of Mg I with respect to Mg II. In our case Mg I, is relatively strong, implying that the host galaxy of GRB 230812B is likely to have a low-ionized interstellar environment.

The other two epochs (12.12 and 15.12 d post $T_0$) show similar, broad features typical of broad-line Ic supernovae. The second epoch
<figure><img src="image_6.png" /><figcaption>**Figure 5.** Comparison of the host subtracted spectra of GRB 230812B at times close to the peak of SN2023pel with spectra of SN1998bw at similar rest frame epochs.</figcaption></figure>

has a slightly redder continuum, that could be due to the cooling of the ejecta. In our analysis, we consider that the contamination by the afterglow continuum is negligible at these epochs.

To analyse the clean SN spectra, we subtracted the contribution from the host galaxy using the host spectrum template that was fit to the host photometry in Section 2.2.2. The host subtracted spectra resemble well the ones obtained for SN1998bw at similar rest-frame observing epochs as was earlier noted by Aguií Fernández et al. (2023), who identify SN2023pel as a broad-line type Ic supernova.

Furthermore, we use NGSF (Goldwasser et al. 2022) on the host-subtracted spectra to determine the type of SN associated with the burst. For the spectra taken on August 27, the best matches are indeed those of type Ic, the best one being SN2006aj, at phase 2 d (after its peak), with a reduced $\chi^2/dof = 1.74$, followed by SN2002ap, SN2005ek, and SN1998bw with $\chi^2/dof = 1.77, 1.78$, and 1.79, respectively. We note that Srinivasaragavan et al. (2024) also find SN2002ap and SN1998bw to be good matches to their spectrum. See Figure 5 for a comparison of the spectra, after removing the host contribution, with SN1998bw.

Additionally, we measured the photospheric velocity of SN2023pel using host-subtracted spectra from GTC. Narrow emission lines and artefacts were first clipped using the IRAF-based routine WOMBAT, and then smoothed the spectra using the open-source code SESNSPECTRAPCA.<sup>15</sup> We measure the velocity of the Fe II line near the SN peak, a proxy for the photospheric velocity of the SN, using SESNSPECTRALIB<sup>16</sup> (Liu et al. 2016; Modjaz et al. 2016). SESNSPECTRALIB computes the blue-shift of the Fe II 5169 Å line between a normalized SN Ic template and the pre-processed and pre-smoothed SN Ic-BL spectrum. Since the Fe II feature in a standard SN Ic spectrum is actually a combination of three lines (at 4924 Å, 5018 Å, 5169 Å), one can measure the relative blue shift of the 5169 Å line in an SN Ic-BL spectrum to a normalized SN Ic template of the same phase. The uncertainty on the velocity measurement is calculated by adding the uncertainty of the mean SN Ic template (at a particular phase) in quadrature with the uncertainty on the relative blue-shifted Fe II absorption velocity. We measure $v_{ph} = 19\,000 \pm 4000$ km s<sup>-1</sup> for the spectrum taken on 2023 August 24 and $v_{ph} = 17\,000 \pm 3000$ km s<sup>-1</sup> for the spectrum taken on 2023 August 27. The velocity we measure is broadly consistent with

<figure><img src="image_7.png" /><figcaption>**Figure 6.** Posteriors of multiband fit of optical afterglow (emission up to 5 d): log of the zero-point flux (at 1 d, 1 Hz, in mJy), $\alpha$ the temporal decay slope and $\beta$ the spectral slope.</figcaption></figure>

Srinivasaragavan et al. (2024) and with that of the larger population of GRB-SNe at a similar phase Cano et al. (2017), for which the average velocity at peak is $v = 20000 \pm 8000$ km s<sup>-1</sup>.

# 4 MULTIWAVELENGTH PHOTOMETRIC ANALYSIS OF GRB 230812B AND SN2023PEL

## 4.1 Empirical light-curve analysis

As a first empirical analysis of the afterglow, we perform a multiband fit of our data up to 5 d (Fig. 1, bottom), to avoid including the contribution from the emerging supernova. Assuming a power-law function of the form $F_v \propto t^{-\alpha}v^{-\beta}$, we derive a decay slope of $\alpha = 1.35 \pm 0.02$ and a spectral slope $\beta = 0.74 \pm 0.01$ (Fig. 6). We note that these values are almost identical to those obtained by Srinivasaragavan et al. (2024) for this GRB: in their work, $\alpha_o = 1.31 \pm 0.02$ and $\beta_o = 0.74 \pm 0.02$. These slopes give an indication of the physical conditions in the GRB's jet (which produces the afterglow through shocks), particularly the electron distribution's index $p$ ($N_e(E) \propto E^{-p}$).

Using the forward shock model, different assumptions about the afterglow environment lead to different analytical equations and relations between $p$ and $\alpha$ and $\beta$ (Sari, Piran & Narayan 1998; Panaitescu & Kumar 2000). For instance, a fast-cooling scenario describes a spectral index $\beta = p/2$ leading to an unusual $p = 1.48 \pm 0.03$, but for a slow-cooling scenario, $\beta = (p-1)/2$, which would give a more reasonable $p = 2.48 \pm 0.03$. For the time-decay slope $\alpha$, a uniform external medium gives $\alpha = (3/4)(p-1)$, which means $p = 2.80 \pm 0.04$, while a wind medium gives $\alpha = (3p-1)/4$, $p = 2.14 \pm 0.04$. The temporal and spectral indices are not satisfied by the same value of $p$, thus, a more sophisticated model (e.g. jet with structure) is needed, and that is what the NMM Bayesian inference analysis will undertake.

<footnote n="15"><sup>15</sup>https://github.com/nyusngroup/SESNspectraPCA</footnote>

<footnote n="16"><sup>16</sup>https://github.com/nyusngroup/SESNspectraLib</footnote>
<figure><img src="image_6.png" /><figcaption>**Figure 5.** Comparison of the host subtracted spectra of GRB 230812B at times close to the peak of SN2023pel with spectra of SN1998bw at similar rest frame epochs.</figcaption></figure>

has a slightly redder continuum, that could be due to the cooling of the ejecta. In our analysis, we consider that the contamination by the afterglow continuum is negligible at these epochs.

To analyse the clean SN spectra, we subtracted the contribution from the host galaxy using the host spectrum template that was fit to the host photometry in Section 2.2.2. The host subtracted spectra resemble well the ones obtained for SN1998bw at similar rest-frame observing epochs as was earlier noted by Aguií Fernández et al. (2023), who identify SN2023pel as a broad-line type Ic supernova.

Furthermore, we use NGSF (Goldwasser et al. 2022) on the host-subtracted spectra to determine the type of SN associated with the burst. For the spectra taken on August 27, the best matches are indeed those of type Ic, the best one being SN2006aj, at phase 2 d (after its peak), with a reduced $\chi^2/dof = 1.74$, followed by SN2002ap, SN2005ek, and SN1998bw with $\chi^2/dof = 1.77, 1.78$, and 1.79, respectively. We note that Srinivasaragavan et al. (2024) also find SN2002ap and SN1998bw to be good matches to their spectrum. See Figure 5 for a comparison of the spectra, after removing the host contribution, with SN1998bw.

Additionally, we measured the photospheric velocity of SN2023pel using host-subtracted spectra from GTC. Narrow emission lines and artefacts were first clipped using the IRAF-based routine WOMBAT, and then smoothed the spectra using the open-source code SESNSPECTRAPCA.<sup>15</sup> We measure the velocity of the Fe II line near the SN peak, a proxy for the photospheric velocity of the SN, using SESNSPECTRALIB<sup>16</sup> (Liu et al. 2016; Modjaz et al. 2016). SESNSPECTRALIB computes the blue-shift of the Fe II 5169 Å line between a normalized SN Ic template and the pre-processed and pre-smoothed SN Ic-BL spectrum. Since the Fe II feature in a standard SN Ic spectrum is actually a combination of three lines (at 4924 Å, 5018 Å, 5169 Å), one can measure the relative blue shift of the 5169 Å line in an SN Ic-BL spectrum to a normalized SN Ic template of the same phase. The uncertainty on the velocity measurement is calculated by adding the uncertainty of the mean SN Ic template (at a particular phase) in quadrature with the uncertainty on the relative blue-shifted Fe II absorption velocity. We measure $v_{ph} = 19\,000 \pm 4000$ km s<sup>-1</sup> for the spectrum taken on 2023 August 24 and $v_{ph} = 17\,000 \pm 3000$ km s<sup>-1</sup> for the spectrum taken on 2023 August 27. The velocity we measure is broadly consistent with

<figure><img src="image_7.png" /><figcaption>**Figure 6.** Posteriors of multiband fit of optical afterglow (emission up to 5 d): log of the zero-point flux (at 1 d, 1 Hz, in mJy), $\alpha$ the temporal decay slope and $\beta$ the spectral slope.</figcaption></figure>

Srinivasaragavan et al. (2024) and with that of the larger population of GRB-SNe at a similar phase Cano et al. (2017), for which the average velocity at peak is $v = 20000 \pm 8000$ km s<sup>-1</sup>.

# 4 MULTIWAVELENGTH PHOTOMETRIC ANALYSIS OF GRB 230812B AND SN2023PEL

## 4.1 Empirical light-curve analysis

As a first empirical analysis of the afterglow, we perform a multiband fit of our data up to 5 d (Fig. 1, bottom), to avoid including the contribution from the emerging supernova. Assuming a power-law function of the form $F_v \propto t^{-\alpha}v^{-\beta}$, we derive a decay slope of $\alpha = 1.35 \pm 0.02$ and a spectral slope $\beta = 0.74 \pm 0.01$ (Fig. 6). We note that these values are almost identical to those obtained by Srinivasaragavan et al. (2024) for this GRB: in their work, $\alpha_o = 1.31 \pm 0.02$ and $\beta_o = 0.74 \pm 0.02$. These slopes give an indication of the physical conditions in the GRB's jet (which produces the afterglow through shocks), particularly the electron distribution's index $p$ ($N_e(E) \propto E^{-p}$).

Using the forward shock model, different assumptions about the afterglow environment lead to different analytical equations and relations between $p$ and $\alpha$ and $\beta$ (Sari, Piran & Narayan 1998; Panaitescu & Kumar 2000). For instance, a fast-cooling scenario describes a spectral index $\beta = p/2$ leading to an unusual $p = 1.48 \pm 0.03$, but for a slow-cooling scenario, $\beta = (p-1)/2$, which would give a more reasonable $p = 2.48 \pm 0.03$. For the time-decay slope $\alpha$, a uniform external medium gives $\alpha = (3/4)(p-1)$, which means $p = 2.80 \pm 0.04$, while a wind medium gives $\alpha = (3p-1)/4$, $p = 2.14 \pm 0.04$. The temporal and spectral indices are not satisfied by the same value of $p$, thus, a more sophisticated model (e.g. jet with structure) is needed, and that is what the NMM Bayesian inference analysis will undertake.

<footnote n="15"><sup>15</sup>https://github.com/nyusngroup/SESNspectraPCA</footnote>

<footnote n="16"><sup>16</sup>https://github.com/nyusngroup/SESNspectraLib</footnote>
## 4.2 Bayesian inference for the investigation of the jet structure, SN properties, and comparison with state of the art (using NMMA)

The GRB+SN astrophysical scenario of GRB230812B is modelled with the combination of two independent models: the semi-analytic code afterglowpy (van Eerten et al. 2010; Ryan et al. 2020) allowing for different structures of the jet, and the nugent-hyper model from sncosmo (Levan et al. 2005) for the supernova. We have previously used the same models on similar Kunert et al. (2024) and Kann et al. (2023).

In afterglowpy (van Eerten et al. 2010; Ryan et al. 2020), the thin-shell approximation is used for handling the dynamics of the relativistic ejecta propagating through the interstellar medium, and the angular structure is introduced by dissecting the blast wave into angular elements, each of which evolves independently, including lateral expansion. The analytical descriptions in Sari, Piran & Narayan (1998) are used for the magnetic-field amplification, electron acceleration, and synchrotron emission from the forward shock. The observed radiation is then computed by performing equal-time arrival surface integration. It should be noted that the model does not account for the presence of a reverse shock or an early coasting phase and does not include inverse-Compton radiation. This limits its applicability to the early afterglow of very bright GRBs. In addition, it does not allow us to explore a wind-like medium, which may be relevant in a case like GRB230812B. In sncosmo, the supernova modelization is constructed from observations of the supernova SN1998bw associated with the long GRB 980425.

We use the Nuclear physics and MultiMessenger Astronomy framework NMMA (Dietrich et al. 2020; Pang et al. 2023)<fnref n="17" /> to evaluate the statistical significance of the different jet structures and provide physical properties of the GRB afterglow and the supernova component.¹⁸NMMA uses Bayesian inference that allows us to quantify which theoretical model $M$ fits the observational data set $d$ best by computing posterior probability distributions $P(\theta) = p(\theta|d, M)$. Here $\theta$ denotes the model's parameters. These posteriors are computed via Bayes' theorem:

$$P(\theta) = \frac{p(d|\theta, M)p(\theta|M)}{p(d|M)} = \frac{\mathcal{L}(\theta)\pi(\theta)}{\mathcal{Z}(d)}, \quad (1)$$

where $\mathcal{L}(\theta)$, $\pi(\theta)$, and $\mathcal{Z}(d)$ are called the likelihood, the prior, and the evidence, respectively. The nested sampling algorithm implemented in PYMULTINEST (Buchner 2016) is used for obtaining the posterior samples and the evidence.

Assuming a priori that the different scenarios considered are equally likely to explain the data, the plausibility of $M_1$ over $M_2$ is quantified by the Bayes factor

$$B = \frac{p(d|M_1)}{p(d|M_2)}, \quad (2)$$

with $B > 1(\ln B > 0)$ indicating a preference for $M_1$, and vice versa. Given a set of AB magnitude measurements $\{m_i^j(t_i)\}$ (and the associated statistical uncertainties $\sigma_i^j$) across different times $\{t_i\}$

and filters $\{j\}$, the likelihood is given by

$$\mathcal{L}(\theta) = \prod_{i,j} \frac{1}{\sqrt{2\pi((\sigma_i^j)^2 + (\sigma_{\text{sys}})^2)}} \exp \left( -\frac{1}{2} \frac{(m_i^j - m_{\text{est}}^j(\theta))^2}{(\sigma_i^j)^2 + (\sigma_{\text{sys}})^2} \right) \quad (3)$$

where $m_{\text{est}}^j(\theta)$ is the estimated AB magnitude for the parameters $\theta$ given different models. Moreover, as an improvement over Kunert et al. (2024) and Kann et al. (2023), the systematic uncertainty $\sigma_{\text{sys}}$ is treated as a free parameter and sampled over during the nested sampling and not kept fixed at a particular value. Therefore, the resulting posterior of $\sigma_{\text{sys}}$ can also be interpreted as the goodness of fit. The lower the $\sigma_{\text{sys}}$, the better the fit, and vice versa.

We have analysed our full data set (X-ray, UV, optical, IR, and radio)<fnref n="19" /> with NMMA. All the values quoted in this section are medians with a 95 per cent credible interval as uncertainty.

### 4.2.1 Jet structure

We vary the jet structure of the GRB to try to characterize or to constrain the jet. To do this, we considered Gaussian (Gauss) and power-law (Power-law) jet structures. Gaussian jets feature an angular dependence $E(\theta_{\text{obs}}) \propto \exp(-\theta_{\text{obs}}^2/(2\theta_c^2))$ for $\theta_{\text{obs}} \le \theta_w$, with $\theta_w$ being an additional free parameter. A power-law jet features an angular dependence $E(\theta_{\text{obs}}) \propto (1 + (\theta_{\text{obs}}/\theta_c)^2/b)^{-b/2}$ for $\theta_{\text{obs}} \le \theta_w$, with $\theta_w$ and $b$ being additional parameters. The resulting log Bayes factor $\ln B$ of Power-law+SN relative to Tophat+SN and Gauss+SN is found to be 18.360 ± 0.020 and 17.356 ± 0.020, respectively, demonstrating a preference for the power-law jet.

The light-curve fits of our best-performing model, i.e. Power-law+SN, are shown in Fig. 7. The posterior distributions of the GRB+SN models for all jet structures considered in this work are shown in Fig. 8 (with corresponding priors displayed in Table 4). The corresponding best-fitting light curves are shown in Fig. D1 in the Appendix.

Given the Bayes factors with the interpretation of Jeffreys (1961) and Kass & Raftery (1995), one will conclude that the power-law jet is decisively favoured against the Gaussian and the top-hat jets. Yet, as previously explained, the models presented in afterglowpy have limitations for early-time GRB afterglow, and the early-time data are also the main source of discriminatory power between different jet structures (as seen in Fig. D1). Thus one can only conclude that there is a preference for power-law jet structure over top-hat and Gaussian jet structures, but it is not a confirmation for detecting such a structure.

In Fig. 8, we present the NMMA posteriors for the source parameters, namely the isotropic energy $E_0$, the interstellar medium density $n_{\text{ISM}}$, the viewing angle $\theta_{\text{obs}}$, the half-opening angle of the jet core $\theta_{\text{core}}$, and the microphysical parameters $\{p, \epsilon_e, \epsilon_B\}$ (the power-law index of the electron energy distribution, the fraction of energy in electrons, the fraction of energy in the magnetic field, respectively) using the different jet structure models with SN.

The numerical results for the posteriors and the associated priors can be found in Table 4. For the best-fitting model, namely Power-law+SN, the posterior of $p$ gives $p = 2.04^{+0.04}_{-0.02}$. Moreover, we find $\log_{10}(E_0/\text{erg}) = 52.82^{+0.35}_{-0.31}$ and $\log_{10}(n_{\text{ISM}}/\text{cm}^{-3}) = -2.38^{+1.45}_{-1.60}$ which is rather low. If such an inferred low-density is not uncommon in long GRBs (GRB 990123 – Granot & Taylor 2005; GRB 090510 – Corsi, Guetta & Piro 2010; Joshi & Razzaque

<footnote n="19">¹⁹With the exception of the K band, for which host flux contributions cannot be computed due to the absence of late-time observations.</footnote>

<footnote n="17">¹⁷https://github.com/nuclear-multimessenger-astronomy/nmma</footnote>

<footnote n="18">¹⁸In order to study and compare the statistical significance between different GRB+SN scenarios in NMMA, we assessed as a first step how statistically favoured the GRB+SN scenario (regardless of the jet structure) is compared to a compact object merger scenario. This study is presented in the Appendix D.</footnote>
## 4.2 Bayesian inference for the investigation of the jet structure, SN properties, and comparison with state of the art (using NMMA)

The GRB+SN astrophysical scenario of GRB230812B is modelled with the combination of two independent models: the semi-analytic code afterglowpy (van Eerten et al. 2010; Ryan et al. 2020) allowing for different structures of the jet, and the nugent-hyper model from sncosmo (Levan et al. 2005) for the supernova. We have previously used the same models on similar Kunert et al. (2024) and Kann et al. (2023).

In afterglowpy (van Eerten et al. 2010; Ryan et al. 2020), the thin-shell approximation is used for handling the dynamics of the relativistic ejecta propagating through the interstellar medium, and the angular structure is introduced by dissecting the blast wave into angular elements, each of which evolves independently, including lateral expansion. The analytical descriptions in Sari, Piran & Narayan (1998) are used for the magnetic-field amplification, electron acceleration, and synchrotron emission from the forward shock. The observed radiation is then computed by performing equal-time arrival surface integration. It should be noted that the model does not account for the presence of a reverse shock or an early coasting phase and does not include inverse-Compton radiation. This limits its applicability to the early afterglow of very bright GRBs. In addition, it does not allow us to explore a wind-like medium, which may be relevant in a case like GRB230812B. In sncosmo, the supernova modelization is constructed from observations of the supernova SN1998bw associated with the long GRB 980425.

We use the Nuclear physics and MultiMessenger Astronomy framework NMMA (Dietrich et al. 2020; Pang et al. 2023)<fnref n="17" /> to evaluate the statistical significance of the different jet structures and provide physical properties of the GRB afterglow and the supernova component.¹⁸NMMA uses Bayesian inference that allows us to quantify which theoretical model $M$ fits the observational data set $d$ best by computing posterior probability distributions $P(\theta) = p(\theta|d, M)$. Here $\theta$ denotes the model's parameters. These posteriors are computed via Bayes' theorem:

$$P(\theta) = \frac{p(d|\theta, M)p(\theta|M)}{p(d|M)} = \frac{\mathcal{L}(\theta)\pi(\theta)}{\mathcal{Z}(d)}, \quad (1)$$

where $\mathcal{L}(\theta)$, $\pi(\theta)$, and $\mathcal{Z}(d)$ are called the likelihood, the prior, and the evidence, respectively. The nested sampling algorithm implemented in PYMULTINEST (Buchner 2016) is used for obtaining the posterior samples and the evidence.

Assuming a priori that the different scenarios considered are equally likely to explain the data, the plausibility of $M_1$ over $M_2$ is quantified by the Bayes factor

$$B = \frac{p(d|M_1)}{p(d|M_2)}, \quad (2)$$

with $B > 1(\ln B > 0)$ indicating a preference for $M_1$, and vice versa. Given a set of AB magnitude measurements $\{m_i^j(t_i)\}$ (and the associated statistical uncertainties $\sigma_i^j$) across different times $\{t_i\}$

and filters $\{j\}$, the likelihood is given by

$$\mathcal{L}(\theta) = \prod_{i,j} \frac{1}{\sqrt{2\pi((\sigma_i^j)^2 + (\sigma_{\text{sys}})^2)}} \exp \left( -\frac{1}{2} \frac{(m_i^j - m_{\text{est}}^j(\theta))^2}{(\sigma_i^j)^2 + (\sigma_{\text{sys}})^2} \right) \quad (3)$$

where $m_{\text{est}}^j(\theta)$ is the estimated AB magnitude for the parameters $\theta$ given different models. Moreover, as an improvement over Kunert et al. (2024) and Kann et al. (2023), the systematic uncertainty $\sigma_{\text{sys}}$ is treated as a free parameter and sampled over during the nested sampling and not kept fixed at a particular value. Therefore, the resulting posterior of $\sigma_{\text{sys}}$ can also be interpreted as the goodness of fit. The lower the $\sigma_{\text{sys}}$, the better the fit, and vice versa.

We have analysed our full data set (X-ray, UV, optical, IR, and radio)<fnref n="19" /> with NMMA. All the values quoted in this section are medians with a 95 per cent credible interval as uncertainty.

### 4.2.1 Jet structure

We vary the jet structure of the GRB to try to characterize or to constrain the jet. To do this, we considered Gaussian (Gauss) and power-law (Power-law) jet structures. Gaussian jets feature an angular dependence $E(\theta_{\text{obs}}) \propto \exp(-\theta_{\text{obs}}^2/(2\theta_c^2))$ for $\theta_{\text{obs}} \le \theta_w$, with $\theta_w$ being an additional free parameter. A power-law jet features an angular dependence $E(\theta_{\text{obs}}) \propto (1 + (\theta_{\text{obs}}/\theta_c)^2/b)^{-b/2}$ for $\theta_{\text{obs}} \le \theta_w$, with $\theta_w$ and $b$ being additional parameters. The resulting log Bayes factor $\ln B$ of Power-law+SN relative to Tophat+SN and Gauss+SN is found to be 18.360 ± 0.020 and 17.356 ± 0.020, respectively, demonstrating a preference for the power-law jet.

The light-curve fits of our best-performing model, i.e. Power-law+SN, are shown in Fig. 7. The posterior distributions of the GRB+SN models for all jet structures considered in this work are shown in Fig. 8 (with corresponding priors displayed in Table 4). The corresponding best-fitting light curves are shown in Fig. D1 in the Appendix.

Given the Bayes factors with the interpretation of Jeffreys (1961) and Kass & Raftery (1995), one will conclude that the power-law jet is decisively favoured against the Gaussian and the top-hat jets. Yet, as previously explained, the models presented in afterglowpy have limitations for early-time GRB afterglow, and the early-time data are also the main source of discriminatory power between different jet structures (as seen in Fig. D1). Thus one can only conclude that there is a preference for power-law jet structure over top-hat and Gaussian jet structures, but it is not a confirmation for detecting such a structure.

In Fig. 8, we present the NMMA posteriors for the source parameters, namely the isotropic energy $E_0$, the interstellar medium density $n_{\text{ISM}}$, the viewing angle $\theta_{\text{obs}}$, the half-opening angle of the jet core $\theta_{\text{core}}$, and the microphysical parameters $\{p, \epsilon_e, \epsilon_B\}$ (the power-law index of the electron energy distribution, the fraction of energy in electrons, the fraction of energy in the magnetic field, respectively) using the different jet structure models with SN.

The numerical results for the posteriors and the associated priors can be found in Table 4. For the best-fitting model, namely Power-law+SN, the posterior of $p$ gives $p = 2.04^{+0.04}_{-0.02}$. Moreover, we find $\log_{10}(E_0/\text{erg}) = 52.82^{+0.35}_{-0.31}$ and $\log_{10}(n_{\text{ISM}}/\text{cm}^{-3}) = -2.38^{+1.45}_{-1.60}$ which is rather low. If such an inferred low-density is not uncommon in long GRBs (GRB 990123 – Granot & Taylor 2005; GRB 090510 – Corsi, Guetta & Piro 2010; Joshi & Razzaque

<footnote n="19">¹⁹With the exception of the K band, for which host flux contributions cannot be computed due to the absence of late-time observations.</footnote>

<footnote n="17">¹⁷https://github.com/nuclear-multimessenger-astronomy/nmma</footnote>

<footnote n="18">¹⁸In order to study and compare the statistical significance between different GRB+SN scenarios in NMMA, we assessed as a first step how statistically favoured the GRB+SN scenario (regardless of the jet structure) is compared to a compact object merger scenario. This study is presented in the Appendix D.</footnote>
<figure><img src="image_8.png" /><figcaption>**Figure 7.** Best-fitting light curves of the Power-law+SN model. Datapoints are reported in the observer frame.</figcaption></figure>

2021; GRB 140515A – Melandri et al. 2015; GRB 160509A – Fraija et al. 2020), it remains surprising in this case where the supernova association is strong evidence for a massive progenitor. This may reflect a strong reduction of the progenitor mass-loss in the last centuries before the collapse or that the environment had likely been blown away before the jet’s interaction with it. The fractions of energy in the electrons and in the magnetic field are $\epsilon_e = 10^{-0.10+0.10}_{-0.29}$ and $\epsilon_B = 10^{-2.29+1.02}_{-0.94}$; and the jet’s core angle $\theta_{\text{core}} = 1.54^{+1.02}_{-0.81}$ deg and viewing angle $\theta_{\text{obs}} = 0.76^{+1.29}_{-0.76}$ deg.

### 4.2.2 Investigation on the X-ray residual

Fig. 7 shows that the best-fitting model has substantial residuals in the X-ray band, especially at earlier times. To further understand this phenomenon, we have performed additional analyses considering data up to 5 d after trigger time, all with the power-law model, the best-performing GRB model considered. The analyses consider either only the X-ray data or only the UV, optical, and IR (UVOIR) data. The results vary in significance, as demonstrated, for instance, by the electron energy distribution index $p$. The analysis with the UVOIR data set gives $p = 2.39_{-0.14}^{+0.11}$, whereas the analysis with only X-ray data gives $p = 2.25_{-0.27}^{+0.22}$. We should, however, note the limitations of this restricted analysis as it results in posterior distributions that are less constrained due to the lower amount of data considered, in the X-ray band, in particular. Moreover, afterglowpy does not include early-time components such as a reverse shock or inverse-Compton radiation. The UVOIR data have a higher weight in the Bayesian analysis due to the higher number of data points in those bands, and since the SN model used here does not support the X-ray band, we can ascribe the high residuals in the X-ray band to a combined effect of the different sizes of the data sets in different filters and a limitation of the models considered in this work.

### 4.2.3 Comparison of SN2023pel with other GRB-associated SNe

We compare the luminosity of SN2023pel with those of several well-studied GRB-associated supernovae, namely SN1998bw, SN2006aj, and SN2013dx (Mazzali et al. 2021). To do this, we use the bolometry tool from SNoopy (Burns et al. 2011)<fnref n="20" /> to obtain a bolometric light curve in the (450–1050) nm range. We grouped our griz and J-band data points (see Table A2) into 1-d bins. When an optical band has no observed data in a bin, we use the flux from the best-fitting model light curves as a proxy. We then subtract the bolometric flux from the GRB component of the best-fitting model from the total curve in order to get the SN component. Our results are shown in Fig. 9. We compare the maximum luminosities, the peak times, and half-max time widths of those four supernovae (SN2023pel, SN1998bw, SN2006aj, and SN2013dx, see Table 5). SN2023pel has a (rest-frame) peak time of 11.6 d, close to that of SN2013dx, but shorter than for SN1998bw and longer than for SN2006aj. It is also consistent with the average peak-time of 13.2 ± 2.6 d that Cano et al. (2017) find for a collection of GRB-SN events. However, SN2023pel notably declines somewhat faster than the other three, especially SN1998bw, with a half-max time width of 16.2 d compared to 36.0 d for the latter. We also note the differing evolution of the supernova in each band, e.g. the half-max time widths in the *i*' and *r'* bands, measured in the source frame, are $17.32_{-1.23}^{+1.27}$ d and $13.30_{-0.96}^{+0.97}$ d, respectively.

Additionally, we compute the brightness factor $k_{SN}$ and (time) stretch factor $s_{SN}$ (both relative to SN1998bw) to compare SN2023pel with the results of the recent Srinivasaragavan et al. (2024) paper on this supernova. We find $k_{SN} = 1.08_{-0.10}^{+0.09}$ and $s_{SN} = 0.67_{-0.05}^{+0.05}$, respectively. For comparison, Srinivasaragavan et al. (2024) find $k_{SN} \approx 0.92$ and $s_{SN} \approx 0.76$, yielding good agreement. Looking at the known correlation between brightness and time-stretch (see fig. 3 in Cano et al. 2017), SN2023pel is the brightest one among events of similar characteristic times, but still compatible with the distribution.

Further investigations have been pursued by Srinivasaragavan et al. (2024) to contextualize GRB 230812B/SN 2023pel with respect to a complete GRB-SN population beyond the three examples mentioned above [see Section 4.3 of Srinivasaragavan et al. (2024)]. Their comparison (using statistical correlations between $L_{\gamma, \text{iso}}$ and $k_{SN, 1998bw}$, $L_{\gamma, \text{iso}}$ and $M_{\text{Ni}}$) shows that SN 2023pel is a rather ordinary SN with respect to the overall GRB-SN population, adding more evidence that the central engine and SN powering mechanisms are decoupled in GRB-SN systems.

## 5 DISCUSSION AND CONCLUSION

GRB 230812B was a bright and relatively nearby gamma-ray burst that displayed a number of important features: it was accompanied by a luminous supernova, it produced radiation from a high energy of 72 GeV down to radio wavelengths, and was observed for at least a few months since the initial burst, which was detected by several space detectors. Dozens of images and measurements were taken from observatories across the world, including some 80 data points from our GRANDMA network and partner institutions, necessitating not only careful reductions and analyses but also subtractions of backgrounds, host, and Milky Way Galaxy absorption (dust) and extinction corrections, etc.

<footnote n="20">²⁰https://csp OBS.Carnegiescience.edu/data/snpy</footnote>
<figure><img src="image_8.png" /><figcaption>**Figure 7.** Best-fitting light curves of the Power-law+SN model. Datapoints are reported in the observer frame.</figcaption></figure>

2021; GRB 140515A – Melandri et al. 2015; GRB 160509A – Fraija et al. 2020), it remains surprising in this case where the supernova association is strong evidence for a massive progenitor. This may reflect a strong reduction of the progenitor mass-loss in the last centuries before the collapse or that the environment had likely been blown away before the jet’s interaction with it. The fractions of energy in the electrons and in the magnetic field are $\epsilon_e = 10^{-0.10} {}^{+0.10}_{-0.29}$ and $\epsilon_B = 10^{-2.29} {}^{+1.02}_{-0.94}$; and the jet’s core angle $\theta_{\text{core}} = 1.54 {}^{+1.02}_{-0.81}$ deg and viewing angle $\theta_{\text{obs}} = 0.76 {}^{+1.29}_{-0.76}$ deg.

### 4.2.2 Investigation on the X-ray residual

Fig. 7 shows that the best-fitting model has substantial residuals in the X-ray band, especially at earlier times. To further understand this phenomenon, we have performed additional analyses considering data up to 5 d after trigger time, all with the power-law model, the best-performing GRB model considered. The analyses consider either only the X-ray data or only the UV, optical, and IR (UVOIR) data. The results vary in significance, as demonstrated, for instance, by the electron energy distribution index $p$. The analysis with the UVOIR data set gives $p = 2.39 {}^{+0.11}_{-0.14}$, whereas the analysis with only X-ray data gives $p = 2.25 {}^{+0.22}_{-0.27}$. We should, however, note the limitations of this restricted analysis as it results in posterior distributions that are less constrained due to the lower amount of data considered, in the X-ray band, in particular. Moreover, afterglowpy does not include early-time components such as a reverse shock or inverse-Compton radiation. The UVOIR data have a higher weight in the Bayesian analysis due to the higher number of data points in those bands, and since the SN model used here does not support the X-ray band, we can ascribe the high residuals in the X-ray band to a combined effect of the different sizes of the data sets in different filters and a limitation of the models considered in this work.

### 4.2.3 Comparison of SN2023pel with other GRB-associated SNe

We compare the luminosity of SN2023pel with those of several well-studied GRB-associated supernovae, namely SN1998bw, SN2006aj, and SN2013dx (Mazzali et al. 2021). To do this, we use the bolometry tool from SNooPy (Burns et al. 2011)<fnref n="20" /> to obtain a bolometric light curve in the (450–1050) nm range. We grouped our *griz* and *J*-band data points (see Table A2) into 1-d bins. When an optical band has no observed data in a bin, we use the flux from the best-fitting model light curves as a proxy. We then subtract the bolometric flux from the GRB component of the best-fitting model from the total curve in order to get the SN component. Our results are shown in Fig. 9. We compare the maximum luminosities, the peak times, and half-max time widths of those four supernovae (SN2023pel, SN1998bw, SN2006aj, and SN2013dx, see Table 5). SN2023pel has a (rest-frame) peak time of 11.6 d, close to that of SN2013dx, but shorter than for SN1998bw and longer than for SN2006aj. It is also consistent with the average peak-time of 13.2 ± 2.6 d that Cano et al. (2017) find for a collection of GRB-SN events. However, SN2023pel notably declines somewhat faster than the other three, especially SN1998bw, with a half-max time width of 16.2 d compared to 36.0 d for the latter. We also note the differing evolution of the supernova in each band, e.g. the half-max time widths in the *i'* and *r'* bands, measured in the source frame, are $17.32 {}^{+1.27}_{-1.23}$ d and $13.30 {}^{+0.97}_{-0.96}$ d, respectively.

Additionally, we compute the brightness factor $k_{SN}$ and (time) stretch factor $s_{SN}$ (both relative to SN1998bw) to compare SN2023pel with the results of the recent Srinivasaragavan et al. (2024) paper on this supernova. We find $k_{SN} = 1.08 {}^{+0.09}_{-0.10}$ and $s_{SN} = 0.67 {}^{+0.05}_{-0.05}$, respectively. For comparison, Srinivasaragavan et al. (2024) find $k_{SN} \approx 0.92$ and $s_{SN} \approx 0.76$, yielding good agreement. Looking at the known correlation between brightness and time-stretch (see fig. 3 in Cano et al. 2017), SN2023pel is the brightest one among events of similar characteristic times, but still compatible with the distribution.

Further investigations have been pursued by Srinivasaragavan et al. (2024) to contextualize GRB 230812B/SN 2023pel with respect to a complete GRB-SN population beyond the three examples mentioned above [see Section 4.3 of Srinivasaragavan et al. (2024)]. Their comparison (using statistical correlations between $L_{\gamma, \text{iso}}$ and $k_{SN, 1998bw}, L_{\gamma}, \text{iso}$ and $M_{Ni}$) shows that SN 2023pel is a rather ordinary SN with respect to the overall GRB-SN population, adding more evidence that the central engine and SN powering mechanisms are decoupled in GRB-SN systems.

## 5 DISCUSSION AND CONCLUSION

GRB 230812B was a bright and relatively nearby gamma-ray burst that displayed a number of important features: it was accompanied by a luminous supernova, it produced radiation from a high energy of 72 GeV down to radio wavelengths, and was observed for at least a few months since the initial burst, which was detected by several space detectors. Dozens of images and measurements were taken from observatories across the world, including some 80 data points from our GRANDMA network and partner institutions, necessitating not only careful reductions and analyses but also subtractions of backgrounds, host, and Milky Way Galaxy absorption (dust) and extinction corrections, etc.

<footnote n="20">²⁰https://cspobs.carnegiescience.edu/data/snpy</footnote>
<figure><img src="image_9.png" /><figcaption>**Figure 8.** Posterior distribution using different jet models of afterglowpy and nugent-hyper for the supernova component.</figcaption></figure>

With a duration $T_{90}$ of 3.264 ± 0.091 s (in the [50–300] keV band), GRB 230812B falls in the ‘long’ category, thus (in principle) the result of a very massive star’s collapse, which produces powerful jets and (oftentimes) a more isotropic supernova, which may be detected several days after the initial burst and afterglow. However, motivated by recent cases indicating that ‘long’ GRBs may sometimes display kilonova characteristics (which are normally associated with ‘short’, merger-type GRBs) and vice versa (‘short’ GRBs displaying collapsar-type characteristics), it was worthwhile to analyse this GRB’s multiband emission to see if it is best fit with a supernova or a kilonova, in addition to determining its jet properties, i.e. geometry (observed and core angle) and physical parameters (electron and magnetic field energy fractions, etc.).

In a nutshell, our analyses (both photometric and spectral) found a clear confirmation of a supernova, and, using NMMA, a GRB best fit

by a high (but not abnormal) total energy $E_0 = 10^{52.82^{+0.35}_{-0.31}}$ erg. The associated supernova SN2023pel peaked $15.76^{+0.81}_{-1.21}$ d (in the observer frame) after the trigger, consistent with Srinivasaragavan et al. (2024) for this supernova and similar to cases of strong GRB-SN associations (Cano et al. 2017). We also plotted pseudo-bolometric light curves for SN2023pel and three other GRB-associated supernovae (SN1998bw, SN2006aj, SN2013dx); we found this new one to have evolved similarly to the others, albeit somewhat faster (especially in decay times).

Our best-fitting model also gave a very low ambient density $n_{ISM} = 10^{-2.38^{+1.45}_{-1.60}}$ cm$^{-3}$, similar to a number of previously modelled cases (see the brief discussion and references given above). Further investigations with different models are called for to confirm and understand all these findings.
<figure><img src="image_9.png" /><figcaption>**Figure 8.** Posterior distribution using different jet models of afterglowpy and nugent-hyper for the supernova component.</figcaption></figure>

With a duration $T_{90}$ of 3.264 ± 0.091 s (in the [50–300] keV band), GRB 230812B falls in the ‘long’ category, thus (in principle) the result of a very massive star’s collapse, which produces powerful jets and (oftentimes) a more isotropic supernova, which may be detected several days after the initial burst and afterglow. However, motivated by recent cases indicating that ‘long’ GRBs may sometimes display kilonova characteristics (which are normally associated with ‘short’, merger-type GRBs) and vice versa (‘short’ GRBs displaying collapsar-type characteristics), it was worthwhile to analyse this GRB’s multiband emission to see if it is best fit with a supernova or a kilonova, in addition to determining its jet properties, i.e. geometry (observed and core angle) and physical parameters (electron and magnetic field energy fractions, etc.).

In a nutshell, our analyses (both photometric and spectral) found a clear confirmation of a supernova, and, using NMMA, a GRB best fit

by a high (but not abnormal) total energy $E_0 = 10^{52.82^{+0.35}_{-0.31}}$ erg. The associated supernova SN2023pel peaked $15.76^{+0.81}_{-1.21}$ d (in the observer frame) after the trigger, consistent with Srinivasaragavan et al. (2024) for this supernova and similar to cases of strong GRB-SN associations (Cano et al. 2017). We also plotted pseudo-bolometric light curves for SN2023pel and three other GRB-associated supernovae (SN1998bw, SN2006aj, SN2013dx); we found this new one to have evolved similarly to the others, albeit somewhat faster (especially in decay times).

Our best-fitting model also gave a very low ambient density $n_{ISM} = 10^{-2.38^{+1.45}_{-1.60}}$ cm$^{-3}$, similar to a number of previously modelled cases (see the brief discussion and references given above). Further investigations with different models are called for to confirm and understand all these findings.
<table><caption>**Table 4.** NMMA – Parameters and prior bounds employed in our Bayesian inferences. We report median posterior values at 95 per cent credibility for various physical scenarios and jet structures for the GRB. ‘Uniform’ refers to an uniform distribution, and ‘LogUniform’ refers to an uniform distribution for the log of the parameter. $N(\mu, \sigma^2)$ refers to a Gaussian distribution with mean $\mu$ and variance $\sigma^2$.</caption><thead><tr><th>Parameter</th><th>Prior</th><th>Prior range</th><th>Tophat+SN</th><th>Gauss+SN</th><th>Power-law+SN</th></tr></thead><tbody><tr><td>(log-) Isotropic afterglow energy E<sub>0</sub> (erg)</td><td>Uniform</td><td>[47, 57]</td><td>52.91<sup>+2.20</sup><sub>-0.78</sub></td><td>52.58<sup>+2.00</sup><sub>-0.42</sub></td><td>52.82<sup>+0.35</sup><sub>-0.31</sub></td></tr><tr><td>(log-) Ambient medium’s density n<sub>ism</sub>(cm<sup>-3</sup>)</td><td>Uniform</td><td>[−6, 3]</td><td>−1.36<sup>+1.34</sup><sub>-2.94</sub></td><td>−1.38<sup>+1.30</sup><sub>-2.27</sub></td><td>−2.38<sup>+1.45</sup><sub>-1.60</sub></td></tr><tr><td>(log-) Energy fraction in electrons ε<sub>e</sub></td><td>Uniform</td><td>[−5, 0]</td><td>−0.13<sup>+0.13</sup><sub>-0.49</sub></td><td>−0.12<sup>+0.12</sup><sub>-0.43</sub></td><td>−0.10<sup>+0.10</sup><sub>-0.29</sub></td></tr><tr><td>(log-) Energy fraction in magnetic field ε<sub>B</sub></td><td>Uniform</td><td>[−10, 0]</td><td>−4.02<sup>+1.83</sup><sub>-2.65</sub></td><td>−3.56<sup>+0.59</sup><sub>-2.52</sub></td><td>−2.29<sup>+0.22</sup><sub>-0.94</sub></td></tr><tr><td>Electron distribution power-law index p</td><td>Uniform</td><td>[2.01, 3]</td><td>2.25<sup>+0.09</sup><sub>-0.19</sub></td><td>2.15<sup>+0.16</sup><sub>-0.09</sub></td><td>2.04<sup>+0.04</sup><sub>-0.02</sub></td></tr><tr><td>Viewing angle θ<sub>obs</sub> (deg)</td><td>N(0, θ<sub>core</sub><sup>2</sup>)</td><td>—</td><td>2.77<sup>+2.24</sup><sub>-2.42</sub></td><td>2.20<sup>+2.28</sup><sub>-2.11</sub></td><td>0.76<sup>+1.29</sup><sub>-0.76</sub></td></tr><tr><td>Jet core’s opening angle θ<sub>core</sub> (deg)</td><td>Uniform</td><td>[0.6, 18]</td><td>4.96<sup>+3.30</sup><sub>-4.20</sub></td><td>3.96<sup>+2.45</sup><sub>-3.09</sub></td><td>1.54<sup>+1.02</sup><sub>-0.81</sub></td></tr><tr><td>‘Wing’ truncation angle θ<sub>wing</sub> (deg)</td><td>Uniform</td><td>[0.6, 45]</td><td>—</td><td>25.18<sup>+19.77</sup><sub>-17.50</sub></td><td>18.25<sup>+19.07</sup><sub>-11.48</sub></td></tr><tr><td>Power-law structure index b</td><td>Uniform</td><td>[0.1, 7]</td><td>—</td><td>—</td><td>1.64<sup>+0.49</sup><sub>-0.47</sub></td></tr><tr><td>Angle ratio θ<sub>obs</sub>/θ<sub>core</sub></td><td>—</td><td>—</td><td>0.56<sup>+0.23</sup><sub>-0.21</sub></td><td>0.64<sup>+0.41</sup><sub>-0.57</sub></td><td>0.49<sup>+0.91</sup><sub>-0.49</sub></td></tr><tr><td>Supernova boost k<sub>SN</sub></td><td>Uniform</td><td>[0.01, 100]</td><td>1.06<sup>+0.18</sup><sub>-0.18</sub></td><td>1.08<sup>+0.15</sup><sub>-0.15</sub></td><td>1.08<sup>+0.09</sup><sub>-0.10</sub></td></tr><tr><td>Supernova stretch s<sub>SN</sub></td><td>Uniform</td><td>[0.1, 5.0]</td><td>0.69<sup>+0.08</sup><sub>-0.07</sub></td><td>0.68<sup>+0.07</sup><sub>-0.07</sub></td><td>0.67<sup>+0.05</sup><sub>-0.05</sub></td></tr><tr><td>Systematic error σ<sub>sys</sub></td><td>LogUniform</td><td>[0.01, 2.0]</td><td>0.28<sup>+0.08</sup><sub>-0.08</sub></td><td>0.28<sup>+0.08</sup><sub>-0.07</sub></td><td>0.14<sup>+0.06</sup><sub>-0.05</sub></td></tr></tbody></table>

<figure><img src="image_10.png" /><figcaption>**Figure 9.** Comparison of pseudo-bolometric (grizJ) luminosity (erg s<sup>-1</sup>) of SN2023pel with those of SN1998bw, SN2006aj, and SN2013dx. The dotted line shows the light curve computed from the best-fitting *nugent-hyper* model, while the points with error bars are the observational data after subtraction of the best-fitting GRB component.</figcaption></figure>

<table><caption>**Table 5.** Comparison of maximum pseudo-bolometric luminosities, (rest-frame) peak times and half-max time widths of SN2023pel, SN1998bw, SN2006aj, and SN2013dx.</caption><thead><tr><th>SN</th><th>L<sub>max</sub><br>(erg s<sup>-1</sup>)</th><th>Peak time<br>(d)</th><th>Half-max<br>time width (d)</th></tr></thead><tbody><tr><td>SN2023pel</td><td>5.75 × 10<sup>42</sup></td><td>11.6</td><td>16.2</td></tr><tr><td>SN1998bw</td><td>5.67 × 10<sup>42</sup></td><td>15.3</td><td>36.0</td></tr><tr><td>SN2006aj</td><td>3.80 × 10<sup>42</sup></td><td>9.50</td><td>26.9</td></tr><tr><td>SN2013dx</td><td>7.10 × 10<sup>42</sup></td><td>12.3</td><td>25.1</td></tr></tbody></table>

Our NMMA framework/simulation also gave best-fitting parameter values for the jet’s geometry (shape and core and viewing angles) and physical conditions (electron energy distribution index, electron energy fraction, and magnetic field energy fraction). The jet’s geometry/shape was best described by the (angular) ‘power-law’ model; the electron energy distribution index *p* was found to be ≈2.1, which is quite typical; the best-fitting magnetic field energy fraction $\epsilon_B$ was ≈10<sup>-2.4</sup>, also quite typical. However, the electron energy fraction was found to be rather high: $\epsilon_e \approx 0.5 - 1$ (10<sup>-0.10</sup><sup>+0.10</sup><sub>-0.29</sub>). The jet’s core and viewing angles were found to be small: $\theta_{core} = 1.54^{+1.02}_{-0.81}$ deg and $\theta_{obs} = 0.76^{+1.29}_{-0.76}$ deg, respectively. Despite these atypical values, the parameters still allow an on-axis jet scenario.

GRB 230812B, bright and relatively close-by, provided us (the GRANDMA network and its partners) the opportunity to perform dozens of observations in UV, optical, near infrared, and submillimetre resulting in some 80 high-quality data points. The light curves in optical showed a distinctive supernova bump, SN2023pel, which turned out to be about as bright as the famous SN1998bw. Our spectroscopic analysis determined a photospheric velocity $v_{ph} = 17\,000 \pm 3000$ km s<sup>-1</sup> near the peak, and the host-subtracted spectra was best fit by SN2006aj, slightly better than SN2002ap, SN2005ek, and SN1998bw.

The rich data that we have produced, coupled with data from other groups (Srinivasaragavan et al. 2024) and facilities, will help explore this event and other GRB-SN associations with additional tools and models. Covering nine orders of magnitude in frequency, our multiband analysis presented some information about the jet and the supernova, but further investigations can help confirm or refine our results.

## ACKNOWLEDGEMENTS

This work has been coordinated with Mansi Kasliwal and Brad Cenko’s group, with whom we shared common developments and visions for time-domain astronomy tools and methods (e.g. SKYPOR-TAL). We thank Gokul Prem Srinivasaragavan in particular for fruitful exchanges on this object. We also thank the anonymous reviewer for constructive comments that have helped improve the paper.
<table><caption>**Table 4.** NMMA – Parameters and prior bounds employed in our Bayesian inferences. We report median posterior values at 95 per cent credibility for various physical scenarios and jet structures for the GRB. ‘Uniform’ refers to an uniform distribution, and ‘LogUniform’ refers to an uniform distribution for the log of the parameter. $N(\mu, \sigma^2)$ refers to a Gaussian distribution with mean $\mu$ and variance $\sigma^2$.</caption><thead><tr><th>Parameter</th><th>Prior</th><th>Prior range</th><th>Tophat+SN</th><th>Gauss+SN</th><th>Power-law+SN</th></tr></thead><tbody><tr><td>(log-) Isotropic afterglow energy E<sub>0</sub> (erg)</td><td>Uniform</td><td>[47, 57]</td><td>52.91<sup>+2.20</sup><sub>-0.78</sub></td><td>52.58<sup>+2.00</sup><sub>-0.42</sub></td><td>52.82<sup>+0.35</sup><sub>-0.31</sub></td></tr><tr><td>(log-) Ambient medium’s density n<sub>ism</sub>(cm<sup>-3</sup>)</td><td>Uniform</td><td>[−6, 3]</td><td>−1.36<sup>+1.34</sup><sub>-2.94</sub></td><td>−1.38<sup>+1.30</sup><sub>-2.27</sub></td><td>−2.38<sup>+1.45</sup><sub>-1.60</sub></td></tr><tr><td>(log-) Energy fraction in electrons ϵ<sub>e</sub></td><td>Uniform</td><td>[−5, 0]</td><td>−0.13<sup>+0.13</sup><sub>-0.49</sub></td><td>−0.12<sup>+0.12</sup><sub>-0.43</sub></td><td>−0.10<sup>+0.10</sup><sub>-0.29</sub></td></tr><tr><td>(log-) Energy fraction in magnetic field ϵ<sub>B</sub></td><td>Uniform</td><td>[−10, 0]</td><td>−4.02<sup>+1.83</sup><sub>-2.65</sub></td><td>−3.56<sup>+0.59</sup><sub>-2.52</sub></td><td>−2.29<sup>+0.02</sup><sub>-0.94</sub></td></tr><tr><td>Electron distribution power-law index p</td><td>Uniform</td><td>[2.01, 3]</td><td>2.25<sup>+0.09</sup><sub>-0.19</sub></td><td>2.15<sup>+0.16</sup><sub>-0.09</sub></td><td>2.04<sup>+0.04</sup><sub>-0.02</sub></td></tr><tr><td>Viewing angle θ<sub>obs</sub> (deg)</td><td>N(0, θ<sub>core</sub><sup>2</sup>)</td><td>—</td><td>2.77<sup>+2.24</sup><sub>-2.42</sub></td><td>2.20<sup>+2.28</sup><sub>-2.11</sub></td><td>0.76<sup>+1.29</sup><sub>-0.76</sub></td></tr><tr><td>Jet core’s opening angle θ<sub>core</sub> (deg)</td><td>Uniform</td><td>[0.6, 18]</td><td>4.96<sup>+3.30</sup><sub>-4.20</sub></td><td>3.96<sup>+2.45</sup><sub>-3.09</sub></td><td>1.54<sup>+1.02</sup><sub>-0.81</sub></td></tr><tr><td>‘Wing’ truncation angle θ<sub>wing</sub> (deg)</td><td>Uniform</td><td>[0.6, 45]</td><td>—</td><td>25.18<sup>+19.77</sup><sub>-17.50</sub></td><td>18.25<sup>+19.07</sup><sub>-11.48</sub></td></tr><tr><td>Power-law structure index b</td><td>Uniform</td><td>[0.1, 7]</td><td>—</td><td>—</td><td>1.64<sup>+0.49</sup><sub>-0.47</sub></td></tr><tr><td>Angle ratio θ<sub>obs</sub>/θ<sub>core</sub></td><td>—</td><td>—</td><td>0.56<sup>+0.23</sup><sub>-0.21</sub></td><td>0.64<sup>+0.41</sup><sub>-0.57</sub></td><td>0.49<sup>+0.91</sup><sub>-0.49</sub></td></tr><tr><td>Supernova boost k<sub>SN</sub></td><td>Uniform</td><td>[0.01, 100]</td><td>1.06<sup>+0.18</sup><sub>-0.18</sub></td><td>1.08<sup>+0.15</sup><sub>-0.15</sub></td><td>1.08<sup>+0.09</sup><sub>-0.10</sub></td></tr><tr><td>Supernova stretch s<sub>SN</sub></td><td>Uniform</td><td>[0.1, 5.0]</td><td>0.69<sup>+0.08</sup><sub>-0.07</sub></td><td>0.68<sup>+0.07</sup><sub>-0.07</sub></td><td>0.67<sup>+0.05</sup><sub>-0.05</sub></td></tr><tr><td>Systematic error σ<sub>sys</sub></td><td>LogUniform</td><td>[0.01, 2.0]</td><td>0.28<sup>+0.08</sup><sub>-0.08</sub></td><td>0.28<sup>+0.08</sup><sub>-0.07</sub></td><td>0.14<sup>+0.06</sup><sub>-0.05</sub></td></tr></tbody></table>

<figure><img src="image_10.png" /><figcaption>**Figure 9.** Comparison of pseudo-bolometric (grizJ) luminosity (erg s<sup>-1</sup>) of SN2023pel with those of SN1998bw, SN2006aj, and SN2013dx. The dotted line shows the light curve computed from the best-fitting *nugent-hyper* model, while the points with error bars are the observational data after subtraction of the best-fitting GRB component.</figcaption></figure>

<table><caption>**Table 5.** Comparison of maximum pseudo-bolometric luminosities, (rest-frame) peak times and half-max time widths of SN2023pel, SN1998bw, SN2006aj, and SN2013dx.</caption><thead><tr><th>SN</th><th>L<sub>max</sub><br>(erg s<sup>-1</sup>)</th><th>Peak time<br>(d)</th><th>Half-max<br>time width (d)</th></tr></thead><tbody><tr><td>SN2023pel</td><td>5.75 × 10<sup>42</sup></td><td>11.6</td><td>16.2</td></tr><tr><td>SN1998bw</td><td>5.67 × 10<sup>42</sup></td><td>15.3</td><td>36.0</td></tr><tr><td>SN2006aj</td><td>3.80 × 10<sup>42</sup></td><td>9.50</td><td>26.9</td></tr><tr><td>SN2013dx</td><td>7.10 × 10<sup>42</sup></td><td>12.3</td><td>25.1</td></tr></tbody></table>

Our NMMA framework/simulation also gave best-fitting parameter values for the jet’s geometry (shape and core and viewing angles) and physical conditions (electron energy distribution index, electron energy fraction, and magnetic field energy fraction). The jet’s geometry/shape was best described by the (angular) ‘power-law’ model; the electron energy distribution index *p* was found to be ≈2.1, which is quite typical; the best-fitting magnetic field energy fraction ϵ<sub>B</sub> was ≈10<sup>-2.4</sup>, also quite typical. However, the electron energy fraction was found to be rather high: ϵ<sub>e</sub> ≈ 0.5 − 1 (10<sup>-0.10</sup><sub>-0.29</sub>). The jet’s core and viewing angles were found to be small: θ<sub>core</sub> = 1.54<sup>+1.02</sup><sub>-0.81</sub> deg and θ<sub>obs</sub> = 0.76<sup>+1.29</sup><sub>-0.76</sub> deg, respectively. Despite these atypical values, the parameters still allow an on-axis jet scenario.

GRB 230812B, bright and relatively close-by, provided us (the GRANDMA network and its partners) the opportunity to perform dozens of observations in UV, optical, near infrared, and submillimetre resulting in some 80 high-quality data points. The light curves in optical showed a distinctive supernova bump, SN2023pel, which turned out to be about as bright as the famous SN1998bw. Our spectroscopic analysis determined a photospheric velocity $v_{ph}$ = 17 000 ± 3000 km s<sup>-1</sup> near the peak, and the host-subtracted spectra was best fit by SN2006aj, slightly better than SN2002ap, SN2005ek, and SN1998bw.

The rich data that we have produced, coupled with data from other groups (Srinivasaragavan et al. 2024) and facilities, will help explore this event and other GRB-SN associations with additional tools and models. Covering nine orders of magnitude in frequency, our multiband analysis presented some information about the jet and the supernova, but further investigations can help confirm or refine our results.

ACKNOWLEDGEMENTS

This work has been coordinated with Mansi Kasliwal and Brad Cenko’s group, with whom we shared common developments and visions for time-domain astronomy tools and methods (e.g. SKYPOR-TAL). We thank Gokul Prem Srinivasaragavan in particular for fruitful exchanges on this object. We also thank the anonymous reviewer for constructive comments that have helped improve the paper.
The GRANDMA collaboration thanks its entire network of observatories/observers, all its partners in observations and analyses, and the amateur participants of its Kilonova-Catcher (KNC) programme.

We dedicate this work to D. A. Kann, whose groundbreaking work in the field of GRBs earned him international recognition over the past two decades. Alex, your contributions to the world of GRB science will always be remembered. We deeply miss you and hope you are proud of the way the GRB community carries on your legacy.

This research has also made use of the MISTRAL data base, based on observations made at Observatoire de Haute Provence (CNRS), France, with the MISTRAL spectro-imager, and operated at CeSAM (LAM), Marseille, France. The GRB OHP observing team is particularly grateful to Jérome Schmitt for the major role he has played in the development and operations of the MISTRAL instrument at the T193 telescope. GRANDMA thanks amateur astronomers for their observations: MS, KF, SL, JN, MF, MO. This work is based on observations carried out under project number S23BG with the IRAM NOEMA interferometer. Partly based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, on the island of La Palma. Partly based on observations made with the Nordic Optical Telescope, owned in collaboration by the University of Turku and Aarhus University, and operated jointly by Aarhus University, the University of Turku, and the University of Oslo, representing Denmark, Finland, and Norway, the University of Iceland and Stockholm University at the Observatorio del Roque de los Muchachos, La Palma, Spain, of the Instituto de Astrofísica de Canarias. This work is based on observations collected at the Centro Astronómico Hispano en Andalucía (CAHA) at Calar Alto, operated jointly by Junta de Andalucía and Consejo Superior de Investigaciones Científicas (IAA-CSIC) (Programme code: 23B-2.2-24, PI Agui Fernández, J. F.). This work used Expanse at the San Diego Supercomputer Cluster through allocation AST200029 – ‘Towards a complete catalog of variable sources to support efficient searches for compact binary mergers and their products’ from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) programme. WC and NS wish to thank Laboratório Nacional de Astrofísica – LNA and OPD staff, Universidade do Estado do Amazonas – UEA and the Brazilian Agencies CNPq and Capes.

GRANDMA has received financial support from the CNRS through the MITI interdisciplinary programmes. TW and PTHI are supported by the research programme of the Netherlands Organization for Scientific Research (NWO). SA acknowledges the financial support of the Programme National Hautes Energies (PNHE). MWC acknowledges support from the National Science Foundation with grant numbers PHY-2347628 and OAC-2117997. CA and MWC were supported by the Preparing for Astrophysics with LSST Program, funded by the Heising-Simons Foundation through grant 2021–2975, and administered by Las Cumbres Observatory. The Egyptian team acknowledges support from the Science, Technology & Innovation Funding Authority (STDF) under grant number 45779. SK is supported by European Structural and Investment Fund and the Czech Ministry of Education, Youth and Sports (Project CoGraDS – CZ.02.1.01/0.0/0.0/15_003/0000437). NPMK is supported by the UKSA *Swift* operations grant. NG, DA, and IA acknowledge support from the American University of Sharjah (UAE) through the grant FRG22-C-S68. MM is supported by the LM2023032 and LM2023047 grants of the Ministry of Education of the Czech Republic. JM is supported by the National Key R & D Program of China (2023YFE0101200), the Yunnan Revitalization Talent Support Program (YunLing Scholar Award), and NSFC grant

12393813. DBM acknowledges support from the European Research Council (ERC) under the European Union's research and innovation programme (ERC Grant HEAVYMETAL No. 101071865). JGD is supported by a research grant from the Ile-de-France Region within the framework of the Domaine d'Intérêt Majeur-Astrophysique et Conditions d'Apparition de la Vie (DIM-ACAV). The work of FN is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The Kilonova-Catcher programme is supported by the IdEx Université de Paris Cité, ANR-18-IDEX-0001 and Paris-Saclay, IJCLAB. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain). The Cosmic Dawn Center is supported by the Danish National Research Foundation. The Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) programme is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.

تجبر مجموعة "جراندما" (GRANDMA) عن مواساتها وتضامنها مع سكان "أوكايمدن" عقب كارثة الزلزال الذي حدث في أغسطس 2023 بالمملكة المغربية.
صادق التمعزي للزملاء بمرصد "أوكايمدن" ولاهالي الضحايا، وتعاطفنا ودعمنا
للمتضررين إثر هذا الحدث المفجع.

DATA AVAILABILITY

Images and raw data are available upon request.

REFERENCES

Abazajian K. N. et al., 2009, ApJS, 182, 543

Adami C. et al., 2023a, GCN Circ., 34418, 1

Adami C. et al., 2023b, GCN Circ., 34743, 1

Aguí Fernández J. F., de Ugarte Postigo A., Thoene C. C., Malesani D. B., Izzo L., Cabrera Lavers A. L., 2023, GCN Circ., 34597, 1

Aguí Fernández J. F., de Ugarte Postigo A., Thoene C. C., Malesani D. B., Izzo L., Cabrera Lavers A. L., 2023, Transient Name Server Classification Report, 2023-2115, 1

Ahumada R. et al., 2020, ApJS, 249, 3

Aivazyan V. et al., 2022, MNRAS, 515, 6007

Amram P. et al., 2023, GCN Circ., 34762, 1

Anand S. et al., 2023, preprint (arXiv:2307.11080)

Antier S. et al., 2020a, MNRAS, 492, 3904

Antier S. et al., 2020b, MNRAS, 497, 5518

Ashall C. et al., 2019, MNRAS, 487, 5824

Bellm E. C. et al., 2019, PASP, 131, 018002

Bertin E., 2010, SWarp: Resampling and Co-adding FITS Images Together, Astrophysics Source Code Library, record ascl:1010.068

Bloom J. S., Kulkarni S. R., Djorgovski S. G., 2002, AJ, 123, 1111

Boquien M., Burgarella D., Roehlly Y., Buat V., Ciesla L., Corre D., Inoue A. K., Salas H., 2019, A&A, 622, A103

Breeveld A. A., Landsman W., Holland S. T., Roming P., Kuin N. P. M., Page M. J., 2011, in McEnery J. E., Racusin J. L., Gehrels N., eds, AIP Conf. Proc. Vol. 1358, Gamma Ray Bursts 2010. Am. Inst. Phys., New York, p. 373

Buchner J., 2016, PyMultiNest: Python interface for MultiNest, Astrophysics Source Code Library, record ascl:1606.005

Bulla M., Camisasca A. E., Guidorzi C., Amati L., Rossi A., Stratta G., Singh P., 2023, GCN Circ., 33578, 1

Burns C. R. et al., 2011, AJ, 141, 19

Cano Z. et al., 2011, ApJ, 740, 41

Cano Z., Wang S.-Q., Dai Z.-G., Wu X.-F., 2017, Adv. Astron., 2017, 1

Casentini C. et al., 2023, GCN Circ., 34402, 1

Cenko B., 2023, GCN Circ., 34633, 1

Cepa J. et al., 2000, in Iye M., Moorwood A. F., eds, Proc. SPIE Conf. Ser. Vol. 4008, Optical and IR Telescope Instrumentation and Detectors. SPIE, Bellingham, p. 623
The GRANDMA collaboration thanks its entire network of observatories/observers, all its partners in observations and analyses, and the amateur participants of its Kilonova-Catcher (KNC) programme.

We dedicate this work to D. A. Kann, whose groundbreaking work in the field of GRBs earned him international recognition over the past two decades. Alex, your contributions to the world of GRB science will always be remembered. We deeply miss you and hope you are proud of the way the GRB community carries on your legacy.

This research has also made use of the MISTRAL data base, based on observations made at Observatoire de Haute Provence (CNRS), France, with the MISTRAL spectro-imager, and operated at CeSAM (LAM), Marseille, France. The GRB OHP observing team is particularly grateful to Jérome Schmitt for the major role he has played in the development and operations of the MISTRAL instrument at the T193 telescope. GRANDMA thanks amateur astronomers for their observations: MS, KF, SL, JN, MF, MO. This work is based on observations carried out under project number S23BG with the IRAM NOEMA interferometer. Partly based on observations made with the Gran Telescopio Canarias (GTC), installed at the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofísica de Canarias, on the island of La Palma. Partly based on observations made with the Nordic Optical Telescope, owned in collaboration by the University of Turku and Aarhus University, and operated jointly by Aarhus University, the University of Turku, and the University of Oslo, representing Denmark, Finland, and Norway, the University of Iceland and Stockholm University at the Observatorio del Roque de los Muchachos, La Palma, Spain, of the Instituto de Astrofísica de Canarias. This work is based on observations collected at the Centro Astronómico Hispano en Andalucía (CAHA) at Calar Alto, operated jointly by Junta de Andalucía and Consejo Superior de Investigaciones Científicas (IAA-CSIC) (Programme code: 23B-2.2-24, PI Agui Fernández, J. F.). This work used Expanse at the San Diego Supercomputer Cluster through allocation AST200029 – ‘Towards a complete catalog of variable sources to support efficient searches for compact binary mergers and their products’ from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) programme. WC and NS wish to thank Laboratório Nacional de Astrofísica – LNA and OPD staff, Universidade do Estado do Amazonas – UEA and the Brazilian Agencies CNPq and Capes.

GRANDMA has received financial support from the CNRS through the MITI interdisciplinary programmes. TW and PTHI are supported by the research programme of the Netherlands Organization for Scientific Research (NWO). SA acknowledges the financial support of the Programme National Hautes Energies (PNHE). MWC acknowledges support from the National Science Foundation with grant numbers PHY-2347628 and OAC-2117997. CA and MWC were supported by the Preparing for Astrophysics with LSST Program, funded by the Heising-Simons Foundation through grant 2021–2975, and administered by Las Cumbres Observatory. The Egyptian team acknowledges support from the Science, Technology & Innovation Funding Authority (STDF) under grant number 45779. SK is supported by European Structural and Investment Fund and the Czech Ministry of Education, Youth and Sports (Project CoGraDS – CZ.02.1.01/0.0/0.0/15_003/0000437). NPMK is supported by the UKSA *Swift* operations grant. NG, DA, and IA acknowledge support from the American University of Sharjah (UAE) through the grant FRG22-C-S68. MM is supported by the LM2023032 and LM2023047 grants of the Ministry of Education of the Czech Republic. JM is supported by the National Key R & D Program of China (2023YFE0101200), the Yunnan Revitalization Talent Support Program (YunLing Scholar Award), and NSFC grant

12393813. DBM acknowledges support from the European Research Council (ERC) under the European Union's research and innovation programme (ERC Grant HEAVYMETAL No. 101071865). JGD is supported by a research grant from the Ile-de-France Region within the framework of the Domaine d'Intérêt Majeur-Astrophysique et Conditions d'Apparition de la Vie (DIM-ACAV). The work of FN is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The Kilonova-Catcher programme is supported by the IdEx Université de Paris Cité, ANR-18-IDEX-0001 and Paris-Saclay, IJCLAB. IRAM is supported by INSU/CNRS (France), MPG (Germany) and IGN (Spain). The Cosmic Dawn Center is supported by the Danish National Research Foundation. The Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) programme is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.

تجبر مجموعة "جراندما" (GRANDMA) عن مواساتها وتضامنها مع سكان "أوكايمدن" عقب كارثة الزلزال الذي حدث في أغسطس 2023 بالمملكة المغربية.
صادق التمعزي للزملاء بمرصد "أوكايمدن" ولاهالي الضحايا، وتعاطفنا ودعمنا
للمتضررين إثر هذا الحدث المفجع.

DATA AVAILABILITY

Images and raw data are available upon request.

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## APPENDIX A: PHOTOMETRIC OBSERVATIONS DETAILS

In this section, we detail observations for GRB 230812B by GRANDMA and associated partners. The observations of the optical afterglow of GRB 230812B started on 2023-08-13T13:34:22 UTC, 18.5 h after the trigger by the *Fermi* Gamma-ray Burst Monitor (GBM), with the GMG 2.4-m telescope, located at the Lijiang station of Yunnan Observatories. In the context of GRANDMA, this first observation was conducted after the GRANDMA collaboration decided to follow up on this GRB, which goes beyond its standard gravitational-wave follow-up programme, 12 h after the trigger time. We measured a magnitude of 19.9 ± 0.1 in the *R* band. The TAROT telescopes and other automated systems were inactive during that period.

The full observational campaign lasted 38 d and ended with observations performed by the 2-m at Observatoire de Haute Provence.
Chandra P. et al., 2023, GCN Circ., 34735, 1

Corsi A., Guetta D., Piro L., 2010, ApJ, 720, 1008

Coughlin M. W. et al., 2018, MNRAS, 478, 692

Coughlin M. W. et al., 2023, ApJS, 267, 31

D'Elia V. et al., 2015, A&A, 577, A116

de Ugarte Postigo A. et al., 2012, A&A, 548, A11

de Ugarte Postigo A., Agúñ Fernández J. F., Thoene C. C., Izzo L., 2023a,
GCN Circ., 34409, 1

de Ugarte Postigo A., Winters J. M., Thoene C. C., Antier S., Agúñ Fernández
J. F., Bremer M., Perley D. A., Martin S., 2023b, GCN Circ., 34468, 1

Deng J., Tominaga N., Mazzali P. A., Maeda K., Nomoto K., 2005, ApJ, 624, 898

Dey A. et al., 2019, AJ, 157, 168

Dietrich T., Coughlin M. W., Pang P. T. H., Bulla M., Heinzel J., Issa L., Tews
I., Antier S., 2020, Science, 370, 1450

Evans P. A. et al., 2007, A&A, 469, 379

Evans P. A. et al., 2009, MNRAS, 397, 1177

Evans P. A. et al., 2010, A&A, 519, A102

Fermi GBM Team, 2023, GCN Circ., 34386, 1

Ferrero P. et al., 2006, A&A, 457, 857

Flewelling H A et al., 2020, Astrophys. J., Suppl. Ser., 25, 7

Fraija N., Laskar T., Dichiara S., Beniamini P., Duran R. B., Dainotti M., Becerra R., 2020, ApJ, 905, 112

Frederiks D., Lysenko A., Ridnaia A., Svinkin D., Tsvetkova A., Ulanov M., Cline T., Konus-Wind Team, 2023, GCN Circ., 34403, 1

Fynbo J. P. U. et al., 2006, Nature, 444, 1047

Gal-Yam A. et al., 2006, Nature, 444, 1053

Galama T. J. et al., 1998, Nature, 395, 670

Gehrels N. et al., 2004, ApJ, 611, 1005

Gehrels N. et al., 2006, Nature, 444, 1044

Gehrels N. et al., 2008, ApJ, 689, 1161

Giarratana S., Giroletti M., Ghirlanda G., Di Lalla N., Omodei N., 2023,
GCN Circ., 34552, 1

Goldwasser S., Yaron O., Sass A., Irani I., Gal-Yam A., Howell D. A., 2022,
Trans. Name Server AstroNote, 191, 1

Graham M. J. et al., 2019, PASP, 131, 078001

Granot J., Taylor G. B., 2005, ApJ, 625, 263

Hjorth J. et al., 2003, Nature, 423, 847

Hjorth J., Bloom J. S., 2012, in Kouveliotou C., Wijers R. A. M. J., Woosley S., eds, Chapter 9 in 'Gamma-Ray Bursts'. Cambridge Univ. Press, Cambridge, p. 169

Jeffreys H., 1961, Theory of Probability, Oxford Univ. Press, Oxford

Jin Z.-P., Li X., Cano Z., Covino S., Fan Y.-Z., Wei D.-M., 2015, ApJ, 811, L22

Jockers K. et al., 2000, Kinematika Fiz. Nebesnykh Tel Suppl., 3, 13

Joshi J. C., Razzaque S., 2021, MNRAS, 505, 1718

Kann D. A. et al., 2010, ApJ, 720, 1513

Kann D. A. et al., 2011, ApJ, 734, 96

Kann D. A. et al., 2023, ApJ, 948, L12

Karpov S., 2021, STDPipe: Simple Transient Detection Pipeline, record ascl:2112.006

Kasen D., Metzger B., Barnes J., Quataert E., Ramirez-Ruiz E., 2017, Nature, 551, 80

Kass R. E., Raftery A. E., 1995, J. Am. Stat. Assoc., 90, 773

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APPENDIX A: PHOTOMETRIC OBSERVATIONS
DETAILS

In this section, we detail observations for GRB 230812B by GRANDMA and associated partners. The observations of the optical afterglow of GRB 230812B started on 2023-08-13T13:34:22 UTC, 18.5 h after the trigger by the *Fermi* Gamma-ray Burst Monitor (GBM), with the GMG 2.4-m telescope, located at the Lijiang station of Yunnan Observatories. In the context of GRANDMA, this first observation was conducted after the GRANDMA collaboration decided to follow up on this GRB, which goes beyond its standard gravitational-wave follow-up programme, 12 h after the trigger time. We measured a magnitude of 19.9 ± 0.1 in the *R* band. The TAROT telescopes and other automated systems were inactive during that period.

The full observational campaign lasted 38 d and ended with ob-
servations performed by the 2-m at Observatoire de Haute Provence.
<table><caption>**Table A1.** X-ray and radio data used in this work. 'Delay' is the time interval between the start of the observation ($T_{start}$) and the Fermi GBM's GRB trigger time (2023-08-12T18:58:12). We display both the unabsorbed flux densities and the corresponding computed AB magnitudes.</caption><thead><tr><th>UT</th><th>T<sub>start</sub></th><th>MJD</th><th>Delay (d)</th><th>Band (s)</th><th>Central frequency</th><th>AB Magnitude</th><th>Flux Flux density (Jy)</th><th>Error (Jy)</th><th>Instrument</th></tr></thead><tbody><tr><td colspan="10" style="text-align:center; font-weight:bold;">X-ray bands</td></tr><tr><td>2023-08-13T02:15:22</td><td>60169.094</td><td>0.304</td><td>26230</td><td>10 keV</td><td>25.50 ± 0.45</td><td>2.29 × 10<sup>-7</sup></td><td>9.5 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-13T03:48:00</td><td>60169.158</td><td>0.368</td><td>31788</td><td>10 keV</td><td>25.78 ± 0.35</td><td>1.77 × 10<sup>-7</sup></td><td>5.7 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-13T05:20:10</td><td>60169.222</td><td>0.432</td><td>37317</td><td>10 keV</td><td>26.45 ± 0.37</td><td>9.55 × 10<sup>-8</sup></td><td>3.3 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-15T00:20:43</td><td>60171.014</td><td>2.224</td><td>192151</td><td>10 keV</td><td>28.01 ± 0.25</td><td>2.27 × 10<sup>-8</sup></td><td>5.3 × 10<sup>-9</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-15T06:25:05</td><td>60171.267</td><td>2.477</td><td>214012</td><td>10 keV</td><td>28.28 ± 0.26</td><td>1.77 × 10<sup>-8</sup></td><td>4.2 × 10<sup>-9</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-18T22:40:51</td><td>60174.945</td><td>6.155</td><td>531759</td><td>10 keV</td><td>30.15 ± 0.20</td><td>3.15 × 10<sup>-9</sup></td><td>5.7 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-24T07:02:27</td><td>60180.293</td><td>11.503</td><td>993854</td><td>10 keV</td><td>30.25 ± 0.23</td><td>2.89 × 10<sup>-9</sup></td><td>6.1 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-29T05:47:45</td><td>60185.241</td><td>16.451</td><td>1421373</td><td>10 keV</td><td>31.41 ± 0.59</td><td>9.94 × 10<sup>-10</sup></td><td>5.4 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td colspan="10" style="text-align:center; font-weight:bold;">Radio bands</td></tr><tr><td>2023-08-14T18:13:52</td><td>60170.760</td><td>1.969</td><td>170139</td><td>15.5 GHz</td><td>17.78 ± 0.16</td><td>2.8 × 10<sup>-4</sup></td><td>4 × 10<sup>-5</sup></td><td>AMI-LA</td></tr><tr><td>2023-08-15T01:52:24</td><td>60171.078</td><td>2.288</td><td>197652</td><td>6 GHz</td><td>18.00 ± 0.05</td><td>2.3 × 10<sup>-4</sup></td><td>1 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-08-15T01:52:24</td><td>60171.078</td><td>2.288</td><td>197652</td><td>10 GHz</td><td>18.17 ± 0.04</td><td>1.96 × 10<sup>-4</sup></td><td>7 × 10<sup>-6</sup></td><td>VLA</td></tr><tr><td>2023-08-16T13:49:00</td><td>60172.576</td><td>3.785</td><td>327048</td><td>75 GHz</td><td>18.55 ± 0.33</td><td>1.38 × 10<sup>-4</sup></td><td>4.2 × 10<sup>-5</sup></td><td>NOEMA</td></tr><tr><td>2023-08-16T13:49:00</td><td>60172.576</td><td>3.785</td><td>327048</td><td>90 GHz</td><td>18.87 ± 0.40</td><td>1.03 × 10<sup>-4</sup></td><td>3.8 × 10<sup>-5</sup></td><td>NOEMA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>3 GHz</td><td>20.19 ± 0.40</td><td>3.06 × 10<sup>-5</sup></td><td>1.12 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>6 GHz</td><td>19.67 ± 0.17</td><td>4.92 × 10<sup>-5</sup></td><td>7.9 × 10<sup>-6</sup></td><td>VLA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>6 GHz</td><td>20.27 ± 0.39</td><td>2.82 × 10<sup>-5</sup></td><td>1.01 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-09-17T11:30:00</td><td>60204.479</td><td>35.689</td><td>3083508</td><td>1.26 GHz</td><td>> 19.82</td><td>&lt; 4.3 × 10<sup>-5</sup></td><td>–</td><td>uGMRT</td></tr></tbody></table>

<table><caption>**Table A2.** UVOIR observations of GRB 230812B. In column (2), $T_{(s)}$ is the time delay between the start of the observation and the Fermi GBM's GRB trigger time (2023-08-12T18:58:12), all in days. Column (5) gives apparent magnitudes or 5-$\sigma$ upper-limits in the AB system, without any correction. Column (6) gives magnitudes in the AB systems for the afterglow and the associated SN, i.e. corrected for the host galaxy and the dust from the MW (AG + SN). When only upper limits were obtained, we corrected only for the MW dust. In Column (7), a cross means we did use this data point for the Bayesian analysis; in some cases the data were not used due to redundancy, i.e. a better measurement was made by another telescope at about the same time.</caption><thead><tr><th>T<sub>start</sub><br>UT<br>(1)</th><th>T<sub>start</sub> (d)<br>MJD<br>(2)</th><th>Filter<br>T-T<sub>GRB</sub><br>(3)</th><th>Exposure<br>(4)</th><th>Magnitude<br>Apparent (5)</th><th>Corrected Magnitude<br>AG + SN (6)</th><th>Telescope</th><th>Analysis<br>(7)</th></tr></thead><tbody><tr><td colspan="8" style="text-align:center; font-weight:bold;">uv band</td></tr><tr><td>2023-08-13T02:01:49</td><td>60169.085</td><td>0.294</td><td>white</td><td>–</td><td>19.05 ± 0.03</td><td>18.97 ± 0.03</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-13T03:33:56</td><td>60169.149</td><td>0.358</td><td>white</td><td>–</td><td>19.36 ± 0.03</td><td>19.28 ± 0.04</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-13T05:12:56</td><td>60169.217</td><td>0.427</td><td>white</td><td>–</td><td>19.58 ± 0.04</td><td>19.51 ± 0.05</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-15T00:12:30</td><td>60171.009</td><td>2.218</td><td>white</td><td>–</td><td>21.62 ± 0.11</td><td>21.72 ± 0.21</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-17T12:14:49</td><td>60173.510</td><td>4.720</td><td>white</td><td>–</td><td>22.77 ± 0.23</td><td>23.40 ± 0.88</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-19T04:17:04</td><td>60175.179</td><td>6.388</td><td>white</td><td>–</td><td>> 22.82</td><td>> 22.72</td><td>UVOT</td><td>x</td></tr><tr><td colspan="8" style="text-align:center; font-weight:bold;">g band</td></tr><tr><td>2023-08-13T04:50:07</td><td>60169.201</td><td>0.411</td><td>g'</td><td>1 × 300 s</td><td>19.22 ± 0.10</td><td>19.14 ± 0.10</td><td>ZTF</td><td>x</td></tr><tr><td>2023-08-13T18:00:11</td><td>60169.750</td><td>0.960</td><td>g'</td><td>10 × 180 s</td><td>20.49 ± 0.08</td><td>20.47 ± 0.08</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:09:14</td><td>60169.840</td><td>1.049</td><td>g'</td><td>4 × 240 s</td><td>20.50 ± 0.03</td><td>20.48 ± 0.03</td><td>CAHA</td><td>–</td></tr><tr><td>2023-08-14T12:47:47</td><td>60170.533</td><td>1.743</td><td>g'</td><td>1 × 600 s</td><td>21.00 ± 0.14</td><td>21.01 ± 0.15</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:41:38</td><td>60170.987</td><td>2.197</td><td>g'</td><td>1 × 600 s</td><td>21.6 ± 0.03</td><td>21.68 ± 0.04</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T20:48:26</td><td>60171.867</td><td>3.077</td><td>g'</td><td>4 × 300 s</td><td>22.18 ± 0.09</td><td>22.39 ± 0.10</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-18 20:57:22</td><td>60174.873</td><td>6.083</td><td>g'</td><td>4 × 300 s</td><td>22.24 ± 0.3</td><td>22.46 ± 0.40</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-19T19:35:17</td><td>60175.816</td><td>7.026</td><td>g'</td><td>14 × 180 s</td><td>> 21.2</td><td>> 21.1</td><td>KAO</td><td>–</td></tr><tr><td>2023-08-21T22:00:18</td><td>60177.917</td><td>9.126</td><td>g'</td><td>3 × 500 s</td><td>22.83 ± 0.05</td><td>23.34 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-04T15:03:01</td><td>60191.627</td><td>22.840</td><td>g'</td><td>2 × 600 s</td><td>> 21.8</td><td>> 21.7</td><td>GMG</td><td>–</td></tr><tr><td>2023-09-12T6:38:16</td><td>60199.277</td><td>30.486</td><td>g'</td><td>10 × 30 s</td><td>23.32 ± 0.05</td><td>24.40 ± 0.27</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td colspan="8" style="text-align:center; font-weight:bold;">r band</td></tr><tr><td>2023-08-13T03:34:57</td><td>60169.149</td><td>0.359</td><td>r'</td><td>1 × 300 s</td><td>18.85 ± 0.05</td><td>18.80 ± 0.05</td><td>ZTF</td><td>x</td></tr><tr><td>2023-08-13T18:41:01</td><td>60169.778</td><td>0.989</td><td>r'</td><td>10 × 180 s</td><td>20.19 ± 0.11</td><td>20.24 ± 0.12</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:09:15</td><td>60169.840</td><td>1.050</td><td>r'</td><td>4x300 s</td><td>20.39 ± 0.05</td><td>20.46 ± 0.06</td><td>T193/MISTRAL</td><td>x</td></tr><tr><td>2023-08-13T20:23:43</td><td>60169.850</td><td>1.059</td><td>r'</td><td>4 × 240 s</td><td>20.38 ± 0.02</td><td>20.45 ± 0.03</td><td>CAHA</td><td>–</td></tr><tr><td>2023-08-14T12:58:38</td><td>60170.541</td><td>1.750</td><td>r'</td><td>1 × 600 s</td><td>20.98 ± 0.06</td><td>21.15 ± 0.08</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:24:41</td><td>60170.975</td><td>2.185</td><td>r'</td><td>1 × 600 s</td><td>21.28 ± 0.04</td><td>21.52 ± 0.06</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T16:36:09</td><td>60171.692</td><td>2.901</td><td>r'</td><td>6 × 100 s</td><td>21.60 ± 0.10</td><td>21.97 ± 0.15</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-15T21:12:19</td><td>60171.884</td><td>3.093</td><td>r'</td><td>3 × 300 s</td><td>21.78 ± 0.1</td><td>22.25 ± 0.17</td><td>CAHA</td><td>–</td></tr><tr><td>2023-08-17T00:31:21</td><td>60173.0218</td><td>4.231</td><td>r'</td><td>18 × 600 s</td><td>21.78 ± 0.04</td><td>22.25 ± 0.09</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-17T15:36:49</td><td>60173.651</td><td>4.860</td><td>r'</td><td>18 × 200 s</td><td>22.15 ± 0.15</td><td>22.93 ± 0.34</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-17T21:46:15</td><td>60173.907</td><td>5.117</td><td>r'</td><td>1 × 1200 s</td><td>21.85 ± 0.1</td><td>22.36 ± 0.18</td><td>T193/MISTRAL</td><td>x</td></tr></tbody></table>
<table><caption>**Table A1.** X-ray and radio data used in this work. 'Delay' is the time interval between the start of the observation ($T_{start}$) and the Fermi GBM's GRB trigger time (2023-08-12T18:58:12). We display both the unabsorbed flux densities and the corresponding computed AB magnitudes.</caption><thead><tr><th>UT</th><th><i>T</i><sub>start</sub><br>(1)</th><th>MJD</th><th>Delay<br>(d)</th><th>Band<br>(s)</th><th>Central frequency</th><th>AB Magnitude</th><th>Flux<br>Flux density (Jy)</th><th>Error (Jy)</th><th>Instrument</th></tr></thead><tbody><tr><td colspan="10" style="text-align:center; font-weight:bold;">X-ray bands</td></tr><tr><td>2023-08-13T02:15:22</td><td>60169.094</td><td>0.304</td><td>26230</td><td>10 keV</td><td>25.50 ± 0.45</td><td>2.29 × 10<sup>-7</sup></td><td>9.5 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-13T03:48:00</td><td>60169.158</td><td>0.368</td><td>31788</td><td>10 keV</td><td>25.78 ± 0.35</td><td>1.77 × 10<sup>-7</sup></td><td>5.7 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-13T05:20:10</td><td>60169.222</td><td>0.432</td><td>37317</td><td>10 keV</td><td>26.45 ± 0.37</td><td>9.55 × 10<sup>-8</sup></td><td>3.3 × 10<sup>-8</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-15T00:20:43</td><td>60171.014</td><td>2.224</td><td>192151</td><td>10 keV</td><td>28.01 ± 0.25</td><td>2.27 × 10<sup>-8</sup></td><td>5.3 × 10<sup>-9</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-15T06:25:05</td><td>60171.267</td><td>2.477</td><td>214012</td><td>10 keV</td><td>28.28 ± 0.26</td><td>1.77 × 10<sup>-8</sup></td><td>4.2 × 10<sup>-9</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-18T22:40:51</td><td>60174.945</td><td>6.155</td><td>531759</td><td>10 keV</td><td>30.15 ± 0.20</td><td>3.15 × 10<sup>-9</sup></td><td>5.7 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-24T07:02:27</td><td>60180.293</td><td>11.503</td><td>993854</td><td>10 keV</td><td>30.25 ± 0.23</td><td>2.89 × 10<sup>-9</sup></td><td>6.1 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td>2023-08-29T05:47:45</td><td>60185.241</td><td>16.451</td><td>1421373</td><td>10 keV</td><td>31.41 ± 0.59</td><td>9.94 × 10<sup>-10</sup></td><td>5.4 × 10<sup>-10</sup></td><td>Swift XRT</td></tr><tr><td colspan="10" style="text-align:center; font-weight:bold;">Radio bands</td></tr><tr><td>2023-08-14T18:13:52</td><td>60170.760</td><td>1.969</td><td>170139</td><td>15.5 GHz</td><td>17.78 ± 0.16</td><td>2.8 × 10<sup>-4</sup></td><td>4 × 10<sup>-5</sup></td><td>AMI-LA</td></tr><tr><td>2023-08-15T01:52:24</td><td>60171.078</td><td>2.288</td><td>197652</td><td>6 GHz</td><td>18.00 ± 0.05</td><td>2.3 × 10<sup>-4</sup></td><td>1 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-08-15T01:52:24</td><td>60171.078</td><td>2.288</td><td>197652</td><td>10 GHz</td><td>18.17 ± 0.04</td><td>1.96 × 10<sup>-4</sup></td><td>7 × 10<sup>-6</sup></td><td>VLA</td></tr><tr><td>2023-08-16T13:49:00</td><td>60172.576</td><td>3.785</td><td>327048</td><td>75 GHz</td><td>18.55 ± 0.33</td><td>1.38 × 10<sup>-4</sup></td><td>4.2 × 10<sup>-5</sup></td><td>NOEMA</td></tr><tr><td>2023-08-16T13:49:00</td><td>60172.576</td><td>3.785</td><td>327048</td><td>90 GHz</td><td>18.87 ± 0.40</td><td>1.03 × 10<sup>-4</sup></td><td>3.8 × 10<sup>-5</sup></td><td>NOEMA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>3 GHz</td><td>20.19 ± 0.40</td><td>3.06 × 10<sup>-5</sup></td><td>1.12 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>6 GHz</td><td>19.67 ± 0.17</td><td>4.92 × 10<sup>-5</sup></td><td>7.9 × 10<sup>-6</sup></td><td>VLA</td></tr><tr><td>2023-09-02T18:24:52</td><td>60189.767</td><td>20.977</td><td>1812399</td><td>6 GHz</td><td>20.27 ± 0.39</td><td>2.82 × 10<sup>-5</sup></td><td>1.01 × 10<sup>-5</sup></td><td>VLA</td></tr><tr><td>2023-09-17T11:30:00</td><td>60204.479</td><td>35.689</td><td>3083508</td><td>1.26 GHz</td><td>> 19.82</td><td>&lt; 4.3 × 10<sup>-5</sup></td><td>—</td><td>uGMRT</td></tr></tbody></table>

<table><caption>**Table A2.** UVOIR observations of GRB 230812B. In column (2), $T_{(s)}$ is the time delay between the start of the observation and the Fermi GBM's GRB trigger time (2023-08-12T18:58:12), all in days. Column (5) gives apparent magnitudes or 5-$\sigma$ upper-limits in the AB system, without any correction. Column (6) gives magnitudes in the AB systems for the afterglow and the associated SN, i.e. corrected for the host galaxy and the dust from the MW (AG + SN). When only upper limits were obtained, we corrected only for the MW dust. In Column (7), a cross means we did use this data point for the Bayesian analysis; in some cases the data were not used due to redundancy, i.e. a better measurement was made by another telescope at about the same time.</caption><thead><tr><th><i>T</i><sub>start</sub><br>UT<br>(1)</th><th><i>T</i><sub>start</sub> (d)<br>MJD<br>(2)</th><th>Filter<br><i>T</i>−<i>T</i><sub>GRB</sub><br>(3)</th><th>Exposure<br>(4)</th><th>Magnitude<br>Apparent (5)</th><th>Corrected Magnitude<br>AG + SN (6)</th><th>Telescope</th><th>Analysis<br>(7)</th></tr></thead><tbody><tr><td colspan="8" style="text-align:center; font-weight:bold;">uv band</td></tr><tr><td>2023-08-13T02:01:49</td><td>60169.085</td><td>0.294</td><td>white</td><td>19.05 ± 0.03</td><td>18.97 ± 0.03</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-13T03:33:56</td><td>60169.149</td><td>0.358</td><td>white</td><td>19.36 ± 0.03</td><td>19.28 ± 0.04</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-13T05:12:56</td><td>60169.217</td><td>0.427</td><td>white</td><td>19.58 ± 0.04</td><td>19.51 ± 0.05</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-15T00:12:30</td><td>60171.009</td><td>2.218</td><td>white</td><td>21.62 ± 0.11</td><td>21.72 ± 0.21</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-17T12:14:49</td><td>60173.510</td><td>4.720</td><td>white</td><td>22.77 ± 0.23</td><td>23.40 ± 0.88</td><td>UVOT</td><td>x</td></tr><tr><td>2023-08-19T04:17:04</td><td>60175.179</td><td>6.388</td><td>white</td><td>> 22.82</td><td>> 22.72</td><td>UVOT</td><td>x</td></tr><tr><td colspan="8" style="text-align:center; font-weight:bold;">g band</td></tr><tr><td>2023-08-13T04:50:07</td><td>60169.201</td><td>0.411</td><td>g'</td><td>1 × 300 s</td><td>19.22 ± 0.10</td><td>19.14 ± 0.10</td><td>ZTF</td><td>x</td></tr><tr><td>2023-08-13T18:00:11</td><td>60169.750</td><td>0.960</td><td>g'</td><td>10 × 180 s</td><td>20.49 ± 0.08</td><td>20.47 ± 0.08</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:09:14</td><td>60169.840</td><td>1.049</td><td>g'</td><td>4 × 240 s</td><td>20.50 ± 0.03</td><td>20.48 ± 0.03</td><td>CAHA</td><td>—</td></tr><tr><td>2023-08-14T12:47:47</td><td>60170.533</td><td>1.743</td><td>g'</td><td>1 × 600 s</td><td>21.00 ± 0.14</td><td>21.01 ± 0.15</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:41:38</td><td>60170.987</td><td>2.197</td><td>g'</td><td>1 × 600 s</td><td>21.6 ± 0.03</td><td>21.68 ± 0.04</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T20:48:26</td><td>60171.867</td><td>3.077</td><td>g'</td><td>4 × 300 s</td><td>22.18 ± 0.09</td><td>22.39 ± 0.10</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-18 20:57:22</td><td>60174.873</td><td>6.083</td><td>g'</td><td>4 × 300 s</td><td>22.24 ± 0.3</td><td>22.46 ± 0.40</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-19T19:35:17</td><td>60175.816</td><td>7.026</td><td>g'</td><td>14 × 180 s</td><td>> 21.2</td><td>> 21.1</td><td>KAO</td><td>—</td></tr><tr><td>2023-08-21T22:00:18</td><td>60177.917</td><td>9.126</td><td>g'</td><td>3 × 500 s</td><td>22.83 ± 0.05</td><td>23.34 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-04T15:03:01</td><td>60191.627</td><td>22.840</td><td>g'</td><td>2 × 600 s</td><td>> 21.8</td><td>> 21.7</td><td>GMG</td><td>—</td></tr><tr><td>2023-09-12T6:38:16</td><td>60199.277</td><td>30.486</td><td>g'</td><td>10 × 30 s</td><td>23.32 ± 0.05</td><td>24.40 ± 0.27</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td colspan="8" style="text-align:center; font-weight:bold;">r band</td></tr><tr><td>2023-08-13T03:34:57</td><td>60169.149</td><td>0.359</td><td>r'</td><td>1 × 300 s</td><td>18.85 ± 0.05</td><td>18.80 ± 0.05</td><td>ZTF</td><td>x</td></tr><tr><td>2023-08-13T18:41:01</td><td>60169.778</td><td>0.989</td><td>r'</td><td>10 × 180 s</td><td>20.19 ± 0.11</td><td>20.24 ± 0.12</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:09:15</td><td>60169.840</td><td>1.050</td><td>r'</td><td>4 × 300 s</td><td>20.39 ± 0.05</td><td>20.46 ± 0.06</td><td>T193/MISTRAL</td><td>x</td></tr><tr><td>2023-08-13T20:23:43</td><td>60169.850</td><td>1.059</td><td>r'</td><td>4 × 240 s</td><td>20.38 ± 0.02</td><td>20.45 ± 0.03</td><td>CAHA</td><td>—</td></tr><tr><td>2023-08-14T12:58:38</td><td>60170.541</td><td>1.750</td><td>r'</td><td>1 × 600 s</td><td>20.98 ± 0.06</td><td>21.15 ± 0.08</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:24:41</td><td>60170.975</td><td>2.185</td><td>r'</td><td>1 × 600 s</td><td>21.28 ± 0.04</td><td>21.52 ± 0.06</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T16:36:09</td><td>60171.692</td><td>2.901</td><td>r'</td><td>6 × 100 s</td><td>21.60 ± 0.10</td><td>21.97 ± 0.15</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-15T21:12:19</td><td>60171.884</td><td>3.093</td><td>r'</td><td>3 × 300 s</td><td>21.78 ± 0.1</td><td>22.25 ± 0.17</td><td>CAHA</td><td>—</td></tr><tr><td>2023-08-17T00:31:21</td><td>60173.0218</td><td>4.231</td><td>r'</td><td>18 × 600 s</td><td>21.78 ± 0.04</td><td>22.25 ± 0.09</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-17T15:36:49</td><td>60173.651</td><td>4.860</td><td>r'</td><td>18 × 200 s</td><td>22.15 ± 0.15</td><td>22.93 ± 0.34</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-17T21:46:15</td><td>60173.907</td><td>5.117</td><td>r'</td><td>1 × 1200 s</td><td>21.85 ± 0.1</td><td>22.36 ± 0.18</td><td>T193/MISTRAL</td><td>x</td></tr></tbody></table>
<table><caption>Table A2 – continued</caption><thead><tr><th rowspan="2">T<sub>start</sub><br>UT<br>(1)</th><th colspan="2">T<sub>start</sub> (d)</th><th rowspan="2">Filter<br>(3)</th><th rowspan="2">Exposure<br>(4)</th><th rowspan="2">Magnitude<br>Apparent (5)</th><th rowspan="2">Corrected Magnitude<br>AG + SN (6)</th><th rowspan="2">Telescope</th><th rowspan="2">Analysis<br>(7)</th></tr><tr><th>MJD<br>(2)</th><th>T-T<sub>GRB</sub><br>(1)</th></tr></thead><tbody><tr><td>2023-08-18T20:55:50</td><td>60174.872</td><td>6.081</td><td>r'</td><td>1 x 600 s</td><td>21.90 ± 0.04</td><td>22.45 ± 0.10</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-18T21:22:09</td><td>60174.890</td><td>6.100</td><td>r'</td><td>3 x 300 s</td><td>21.71 ± 0.14</td><td>22.14 ± 0.22</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-19T17:11:42</td><td>60175.716</td><td>6.926</td><td>r'</td><td>15 x 200 s</td><td>21.59 ± 0.07</td><td>21.95 ± 0.11</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-21T16:41:57</td><td>60177.696</td><td>8.905</td><td>r'</td><td>16 x 100 s</td><td>21.55 ± 0.07</td><td>21.90 ± 0.11</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-21T18:37:20</td><td>60177.776</td><td>8.986</td><td>r'</td><td>18 x 180 s</td><td>21.40 ± 0.13</td><td>21.69 ± 0.18</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T21:32:28</td><td>60177.898</td><td>9.107</td><td>r'</td><td>1 x 600 s</td><td>21.76 ± 0.04</td><td>22.21 ± 0.09</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-22T21:10:00</td><td>60178.882</td><td>10.092</td><td>r'</td><td>15 x 300 s</td><td>21.62 ± 0.06</td><td>22.00 ± 0.1</td><td>C2PU</td><td>x</td></tr><tr><td>2023-08-26T22:45:58</td><td>60182.949</td><td>14.158</td><td>r'</td><td>1 x 600 s</td><td>21.64 ± 0.09</td><td>22.03 ± 0.14</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-04T15:23:48</td><td>60191.642</td><td>22.850</td><td>r'</td><td>2 x 600 s</td><td>> 21.7</td><td>> 21.65</td><td>GMG</td><td>-</td></tr><tr><td>2023-09-05T14:33:44</td><td>60192.607</td><td>23.816</td><td>r'</td><td>16 x 100 s</td><td>> 21.9</td><td>> 21.85</td><td>NOWT</td><td>-</td></tr><tr><td>2023-09-07T22:14:52</td><td>60194.927</td><td>26.136</td><td>r'</td><td>3 x 1800 s</td><td>22.12 ± 0.03</td><td>22.86 ± 0.13</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-09T19:30:00</td><td>60196.813</td><td>28.022</td><td>r'</td><td>5 x 600 s</td><td>22.35 ± 0.10</td><td>23.41 ± 0.33</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-09-11T19:14:55</td><td>60198.802</td><td>30.012</td><td>r'</td><td>11 x 600 s</td><td>22.18 ± 0.10</td><td>23.00 ± 0.26</td><td>NAO-2m</td><td>-</td></tr><tr><td>2023-09-12T06:31:48</td><td>60199.272</td><td>30.482</td><td>r'</td><td>3 x 40 s</td><td>22.33 ± 0.05</td><td>23.36 ± 0.22</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td>2023-09-12T19:30:18</td><td>60199.813</td><td>31.023</td><td>r'</td><td>11 x 600 s</td><td>22.31 ± 0.10</td><td>23.31 ± 0.31</td><td>NAO-2m</td><td>-</td></tr><tr><td>2023-09-19T19:58:00</td><td>60206.832</td><td>38.042</td><td>r'</td><td>9 x 600 s</td><td>22.45 ± 0.1</td><td>23.72 ± 0.41</td><td>T193/MISTRAL</td><td>x</td></tr><tr><td colspan="10" style="text-align: center;">i band</td></tr><tr><td>2023-08-13T19:28:23</td><td>60169.811</td><td>1.021</td><td>i'</td><td>2 x 150 s</td><td>20.16 ± 0.05</td><td>20.25 ± 0.06</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:46:19</td><td>60169.865</td><td>1.705</td><td>i'</td><td>3 x 240 s</td><td>20.29 ± 0.03</td><td>20.40 ± 0.04</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-14T13:09:36</td><td>60170.548</td><td>1.758</td><td>i'</td><td>1 x 600 s</td><td>21.08 ± 0.20</td><td>21.37 ± 0.27</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:52:51</td><td>60170.995</td><td>2.205</td><td>i'</td><td>1 x 300 s</td><td>21.31 ± 0.06</td><td>21.69 ± 0.11</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T21:30:45</td><td>60171.896</td><td>3.106</td><td>i'</td><td>4 x 300 s</td><td>21.59 ± 0.11</td><td>22.14 ± 0.21</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-16T20:12:30</td><td>60172.842</td><td>4.052</td><td>i'</td><td>9 x 300 s</td><td>21.64 ± 0.07</td><td>22.22 ± 0.16</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-08-17T00:42:36</td><td>60173.030</td><td>4.239</td><td>i'</td><td>1 x 600s</td><td>21.74 ± 0.06</td><td>22.41 ± 0.16</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-17T19:12:05</td><td>60173.800</td><td>5.001</td><td>i'</td><td>14 x 300s</td><td>21.69 ± 0.09</td><td>22.31 ± 0.19</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-08-18T21:07:04</td><td>60174.880</td><td>6.089</td><td>i'</td><td>1 x 600 s</td><td>21.68 ± 0.04</td><td>22.29 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-18T21:39:40</td><td>60174.903</td><td>6.112</td><td>i'</td><td>4 x 300 s</td><td>21.64 ± 0.15</td><td>22.22 ± 0.19</td><td>CAHA</td><td>-</td></tr><tr><td>2023-08-19T19:50:40</td><td>60175.827</td><td>7.037</td><td>i'</td><td>20 x 180 s</td><td>21.95 ± 0.20</td><td>22.85 ± 0.51</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-20T18:01:44</td><td>60176.751</td><td>7.961</td><td>i'</td><td>29 x 180 s</td><td>21.51 ± 0.06</td><td>22.00 ± 0.12</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T19:41:01</td><td>60177.820</td><td>9.030</td><td>i'</td><td>20 x 180 s</td><td>21.36 ± 0.06</td><td>21.77 ± 0.11</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T22:27:57</td><td>60177.936</td><td>9.146</td><td>i'</td><td>1 x 600 s</td><td>21.58 ± 0.04</td><td>22.12 ± 0.11</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-22T19:30:17</td><td>60178.813</td><td>10.022</td><td>i'</td><td>20 x 180 s</td><td>21.49 ± 0.09</td><td>21.97 ± 0.16</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-23T19:56:13</td><td>60179.831</td><td>11.040</td><td>i'</td><td>19 x 180 s</td><td>21.42 ± 0.07</td><td>21.86 ± 0.13</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-26T22:57:10</td><td>60182.956</td><td>14.165</td><td>i'</td><td>1 x 600 s</td><td>21.42 ± 0.08</td><td>21.86 ± 0.14</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-28T19:20:25</td><td>60184.806</td><td>16.015</td><td>i'</td><td>26 x 180 s</td><td>21.40 ± 0.11</td><td>21.83 ± 0.18</td><td>KAO</td><td>x</td></tr><tr><td>2023-09-04T15:50:00</td><td>60191.660</td><td>22.870</td><td>i'</td><td>2 x 600 s</td><td>21.51 ± 0.24</td><td>22.00 ± 0.40</td><td>GMG</td><td>x</td></tr><tr><td>2023-09-12T06:24:15</td><td>60199.267</td><td>30.476</td><td>i'</td><td>3 x 60 s</td><td>21.79 ± 0.04</td><td>22.51 ± 0.14</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td>2023-10-07T19:44:24</td><td>60224.822</td><td>56.032</td><td>i'</td><td>1 x 3000 s</td><td>22.34 ± 0.04</td><td>24.07 ± 0.60</td><td>NOT</td><td>-</td></tr><tr><td colspan="10" style="text-align: center;">z band</td></tr><tr><td>2023-08-14T13:20:38</td><td>60170.556</td><td>1.766</td><td>z'</td><td>1 x 600 s</td><td>> 20.5</td><td>> 20.47</td><td>GMG</td><td>-</td></tr><tr><td>2023-08-14T23:30:23</td><td>60170.979</td><td>2.189</td><td>z'</td><td>1 x 600 s</td><td>20.98 ± 0.08</td><td>21.31 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-21T21:43:40</td><td>60177.905</td><td>9.115</td><td>z'</td><td>1 x 900 s</td><td>21.68 ± 0.10</td><td>22.49 ± 0.26</td><td>NOT</td><td>x</td></tr><tr><td colspan="10" style="text-align: center;">J band</td></tr><tr><td>2023-08-16T21:33:58</td><td>60172.899</td><td>4.108</td><td>J</td><td>20 x 50 s</td><td>21.00 ± 0.17</td><td>21.67 ± 0.43</td><td>TNG</td><td>-</td></tr><tr><td>2023-08-21T21:29:22</td><td>60177.895</td><td>9.105</td><td>J</td><td>45 x 60 s</td><td>21.26 ± 0.27</td><td>22.23 ± 0.57</td><td>TNG</td><td>-</td></tr><tr><td>2023-10-11T20:15:22</td><td>60228.844</td><td>60.054</td><td>J</td><td>45 x 80 s</td><td>21.82 ± 0.32</td><td>-</td><td>TNG</td><td>-</td></tr><tr><td colspan="10" style="text-align: center;">K band</td></tr><tr><td>2023-08-16T20:49:28</td><td>60172.868</td><td>4.077</td><td>K</td><td>30 x 50 s</td><td>21.41 ± 0.33</td><td>21.40 ± 0.33 with host</td><td>TNG</td><td>-</td></tr></tbody></table>

While we took images in V, R, I, g', r', i', and z' bands, we use for this work only data in g', r', i', and z' bands for extracting the physical properties of the event. We however computed the synthetic light curves in R, I from the NMMA best-fitting parameters constrained from the Xray+UV+griz+radio analysis, and confirmed their consistency with our data sets.

Below, in sequence, we here provide the start time (relative to T₀) of the first observation for each telescope and the filters/bands used during the entire campaign: GMG (0.78 d in R, g', r', i', z') at Lijiang station of Yunnan Observatories, UBAI-AZT-22 (0.91 d in R band) at

Maidanak Observatory, AC-32 telescope at Abastumani observatory (0.94 d in R), KAO (0.96 d in g', r', i') at Kottamia Observatory, Lisnyky-Schmidt (0.98 d in R) at Kyiv Observatory, NAO-50/70 cm Schmidt (1.03 d in I) at Rozhen National Astronomical Observatory, CAHA (1.049 d in g', r', i') at Calar Alto Astronomical Observatory, T193/MISTRAL (1.050 d in r') at Haute-Provence Observatory, the 2-m telescope (1.08 d in R) at Shamakhy Astrophysical Observatory of Azerbaijan, FRAM-CTA-N (1.12 d in R) at Roque de los Muchachos Observatory, NOWT (2.09 d in BVR) at Xinjiang Astronomical Observatory, NOT (2.185 d in g', r', i') at Roque de los Muchachos
<table><caption>Table A2 – continued</caption><thead><tr><th rowspan="2">T<sub>start</sub><br>UT<br>(1)</th><th colspan="2">T<sub>start</sub> (d)</th><th rowspan="2">Filter<br>(3)</th><th rowspan="2">Exposure<br>(4)</th><th rowspan="2">Magnitude<br>Apparent (5)</th><th rowspan="2">Corrected Magnitude<br>AG + SN (6)</th><th rowspan="2">Telescope</th><th rowspan="2">Analysis<br>(7)</th></tr><tr><th>MJD<br>(2)</th><th>T-T<sub>GRB</sub><br>(1)</th></tr></thead><tbody><tr><td>2023-08-18T20:55:50</td><td>60174.872</td><td>6.081</td><td>r'</td><td>1 x 600 s</td><td>21.90 ± 0.04</td><td>22.45 ± 0.10</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-18T21:22:09</td><td>60174.890</td><td>6.100</td><td>r'</td><td>3 x 300 s</td><td>21.71 ± 0.14</td><td>22.14 ± 0.22</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-19T17:11:42</td><td>60175.716</td><td>6.926</td><td>r'</td><td>15 x 200 s</td><td>21.59 ± 0.07</td><td>21.95 ± 0.11</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-21T16:41:57</td><td>60177.696</td><td>8.905</td><td>r'</td><td>16 x 100 s</td><td>21.55 ± 0.07</td><td>21.90 ± 0.11</td><td>NOWT</td><td>x</td></tr><tr><td>2023-08-21T18:37:20</td><td>60177.776</td><td>8.986</td><td>r'</td><td>18 x 180 s</td><td>21.40 ± 0.13</td><td>21.69 ± 0.18</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T21:32:28</td><td>60177.898</td><td>9.107</td><td>r'</td><td>1 x 600 s</td><td>21.76 ± 0.04</td><td>22.21 ± 0.09</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-22T21:10:00</td><td>60178.882</td><td>10.092</td><td>r'</td><td>15 x 300 s</td><td>21.62 ± 0.06</td><td>22.00 ± 0.1</td><td>C2PU</td><td>x</td></tr><tr><td>2023-08-26T22:45:58</td><td>60182.949</td><td>14.158</td><td>r'</td><td>1 x 600 s</td><td>21.64 ± 0.09</td><td>22.03 ± 0.14</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-04T15:23:48</td><td>60191.642</td><td>22.850</td><td>r'</td><td>2 x 600 s</td><td>> 21.7</td><td>> 21.65</td><td>GMG</td><td>-</td></tr><tr><td>2023-09-05T14:33:44</td><td>60192.607</td><td>23.816</td><td>r'</td><td>16 x 100 s</td><td>> 21.9</td><td>> 21.85</td><td>NOWT</td><td>-</td></tr><tr><td>2023-09-07T22:14:52</td><td>60194.927</td><td>26.136</td><td>r'</td><td>3 x 1800 s</td><td>22.12 ± 0.03</td><td>22.86 ± 0.13</td><td>NOT</td><td>x</td></tr><tr><td>2023-09-09T19:30:00</td><td>60196.813</td><td>28.022</td><td>r'</td><td>5 x 600 s</td><td>22.35 ± 0.10</td><td>23.41 ± 0.33</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-09-11T19:14:55</td><td>60198.802</td><td>30.012</td><td>r'</td><td>11 x 600 s</td><td>22.18 ± 0.10</td><td>23.00 ± 0.26</td><td>NAO-2m</td><td>-</td></tr><tr><td>2023-09-12T06:31:48</td><td>60199.272</td><td>30.482</td><td>r'</td><td>3 x 40 s</td><td>22.33 ± 0.05</td><td>23.36 ± 0.22</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td>2023-09-12T19:30:18</td><td>60199.813</td><td>31.023</td><td>r'</td><td>11 x 600 s</td><td>22.31 ± 0.10</td><td>23.31 ± 0.31</td><td>NAO-2m</td><td>-</td></tr><tr><td>2023-09-19T19:58:00</td><td>60206.832</td><td>38.042</td><td>r'</td><td>9 x 600 s</td><td>22.45 ± 0.1</td><td>23.72 ± 0.41</td><td>T193/MISTRAL</td><td>x</td></tr><tr><td colspan="10" style="text-align: center;">i band</td></tr><tr><td>2023-08-13T19:28:23</td><td>60169.811</td><td>1.021</td><td>i'</td><td>2 x 150 s</td><td>20.16 ± 0.05</td><td>20.25 ± 0.06</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-13T20:46:19</td><td>60169.865</td><td>1.705</td><td>i'</td><td>3 x 240 s</td><td>20.29 ± 0.03</td><td>20.40 ± 0.04</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-14T13:09:36</td><td>60170.548</td><td>1.758</td><td>i'</td><td>1 x 600 s</td><td>21.08 ± 0.20</td><td>21.37 ± 0.27</td><td>GMG</td><td>x</td></tr><tr><td>2023-08-14T23:52:51</td><td>60170.995</td><td>2.205</td><td>i'</td><td>1 x 300 s</td><td>21.31 ± 0.06</td><td>21.69 ± 0.11</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-15T21:30:45</td><td>60171.896</td><td>3.106</td><td>i'</td><td>4 x 300 s</td><td>21.59 ± 0.11</td><td>22.14 ± 0.21</td><td>CAHA</td><td>x</td></tr><tr><td>2023-08-16T20:12:30</td><td>60172.842</td><td>4.052</td><td>i'</td><td>9 x 300 s</td><td>21.64 ± 0.07</td><td>22.22 ± 0.16</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-08-17T00:42:36</td><td>60173.030</td><td>4.239</td><td>i'</td><td>1 x 600s</td><td>21.74 ± 0.06</td><td>22.41 ± 0.16</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-17T19:12:05</td><td>60173.800</td><td>5.001</td><td>i'</td><td>14 x 300s</td><td>21.69 ± 0.09</td><td>22.31 ± 0.19</td><td>NAO-2m</td><td>x</td></tr><tr><td>2023-08-18T21:07:04</td><td>60174.880</td><td>6.089</td><td>i'</td><td>1 x 600 s</td><td>21.68 ± 0.04</td><td>22.29 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-18T21:39:40</td><td>60174.903</td><td>6.112</td><td>i'</td><td>4 x 300 s</td><td>21.64 ± 0.15</td><td>22.22 ± 0.19</td><td>CAHA</td><td>-</td></tr><tr><td>2023-08-19T19:50:40</td><td>60175.827</td><td>7.037</td><td>i'</td><td>20 x 180 s</td><td>21.95 ± 0.20</td><td>22.85 ± 0.51</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-20T18:01:44</td><td>60176.751</td><td>7.961</td><td>i'</td><td>29 x 180 s</td><td>21.51 ± 0.06</td><td>22.00 ± 0.12</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T19:41:01</td><td>60177.820</td><td>9.030</td><td>i'</td><td>20 x 180 s</td><td>21.36 ± 0.06</td><td>21.77 ± 0.11</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-21T22:27:57</td><td>60177.936</td><td>9.146</td><td>i'</td><td>1 x 600 s</td><td>21.58 ± 0.04</td><td>22.12 ± 0.11</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-22T19:30:17</td><td>60178.813</td><td>10.022</td><td>i'</td><td>20 x 180 s</td><td>21.49 ± 0.09</td><td>21.97 ± 0.16</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-23T19:56:13</td><td>60179.831</td><td>11.040</td><td>i'</td><td>19 x 180 s</td><td>21.42 ± 0.07</td><td>21.86 ± 0.13</td><td>KAO</td><td>x</td></tr><tr><td>2023-08-26T22:57:10</td><td>60182.956</td><td>14.165</td><td>i'</td><td>1 x 600 s</td><td>21.42 ± 0.08</td><td>21.86 ± 0.14</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-28T19:20:25</td><td>60184.806</td><td>16.015</td><td>i'</td><td>26 x 180 s</td><td>21.40 ± 0.11</td><td>21.83 ± 0.18</td><td>KAO</td><td>x</td></tr><tr><td>2023-09-04T15:50:00</td><td>60191.660</td><td>22.870</td><td>i'</td><td>2 x 600 s</td><td>21.51 ± 0.24</td><td>22.00 ± 0.40</td><td>GMG</td><td>x</td></tr><tr><td>2023-09-12T06:24:15</td><td>60199.267</td><td>30.476</td><td>i'</td><td>3 x 60 s</td><td>21.79 ± 0.04</td><td>22.51 ± 0.14</td><td>CFHT-MegaCAM</td><td>x</td></tr><tr><td>2023-10-07T19:44:24</td><td>60224.822</td><td>56.032</td><td>i'</td><td>1 x 3000 s</td><td>22.34 ± 0.04</td><td>24.07 ± 0.60</td><td>NOT</td><td>-</td></tr><tr><td colspan="10" style="text-align: center;">z band</td></tr><tr><td>2023-08-14T13:20:38</td><td>60170.556</td><td>1.766</td><td>z'</td><td>1 x 600 s</td><td>> 20.5</td><td>> 20.47</td><td>GMG</td><td>-</td></tr><tr><td>2023-08-14T23:30:23</td><td>60170.979</td><td>2.189</td><td>z'</td><td>1 x 600 s</td><td>20.98 ± 0.08</td><td>21.31 ± 0.12</td><td>NOT</td><td>x</td></tr><tr><td>2023-08-21T21:43:40</td><td>60177.905</td><td>9.115</td><td>z'</td><td>1 x 900 s</td><td>21.68 ± 0.10</td><td>22.49 ± 0.26</td><td>NOT</td><td>x</td></tr><tr><td colspan="10" style="text-align: center;">J band</td></tr><tr><td>2023-08-16T21:33:58</td><td>60172.899</td><td>4.108</td><td>J</td><td>20 x 50 s</td><td>21.00 ± 0.17</td><td>21.67 ± 0.43</td><td>TNG</td><td>-</td></tr><tr><td>2023-08-21T21:29:22</td><td>60177.895</td><td>9.105</td><td>J</td><td>45 x 60 s</td><td>21.26 ± 0.27</td><td>22.23 ± 0.57</td><td>TNG</td><td>-</td></tr><tr><td>2023-10-11T20:15:22</td><td>60228.844</td><td>60.054</td><td>J</td><td>45 x 80 s</td><td>21.82 ± 0.32</td><td>-</td><td>TNG</td><td>-</td></tr><tr><td colspan="10" style="text-align: center;">K band</td></tr><tr><td>2023-08-16T20:49:28</td><td>60172.868</td><td>4.077</td><td>K</td><td>30 x 50 s</td><td>21.41 ± 0.33</td><td>21.40 ± 0.33 with host</td><td>TNG</td><td>-</td></tr></tbody></table>

While we took images in V, R, I, g', r', i', and z' bands, we use for this work only data in g', r', i', and z' bands for extracting the physical properties of the event. We however computed the synthetic light curves in R, I from the NMMA best-fitting parameters constrained from the Xray+UV+griz+radio analysis, and confirmed their consistency with our data sets.

Below, in sequence, we here provide the start time (relative to $T_0$) of the first observation for each telescope and the filters/bands used during the entire campaign: GMG (0.78 d in R, g', r', i', z') at Lijiang station of Yunnan Observatories, UBAI-AZT-22 (0.91 d in R band) at

Maidanak Observatory, AC-32 telescope at Abastumani observatory (0.94 d in R), KAO (0.96 d in g', r', i') at Kottamia Observatory, Lisnyky-Schmidt (0.98 d in R) at Kyiv Observatory, NAO-50/70 cm Schmidt (1.03 d in I) at Rozhen National Astronomical Observatory, CAHA (1.049 d in g', r', i') at Calar Alto Astronomical Observatory, T193/MISTRAL (1.050 d in r') at Haute-Provence Observatory, the 2-m telescope (1.08 d in R) at Shamakhy Astrophysical Observatory of Azerbaijan, FRAM-CTA-N (1.12 d in R) at Roque de los Muchachos Observatory, NOWT (2.09 d in BVR) at Xinjiang Astronomical Observatory, NOT (2.185 d in g', r', i') at Roque de los Muchachos