The optical light curve of GRB 221009A: the afterglow and the emerging supernova
Bibliographic record
Abstract
We present extensive optical photometry of the afterglow of GRB~221009A. Our data cover $0.9 - 59.9$\,days from the time of \textit{Swift} and \textit{Fermi} GRB detections. Photometry in $rizy$-band filters was collected primarily with Pan-STARRS and supplemented by multiple 1- to 4-meter imaging facilities. We analyzed the Swift X-ray data of the afterglow and found a single decline rate power-law $f(t) \propto t^{-1.556\pm0.002}$ best describes the light curve. In addition to the high foreground Milky Way dust extinction along this line of sight, the data favour additional extinction to consistently model the optical to X-ray flux with optically thin synchrotron emission. We fit the X-ray-derived power-law to the optical light curve and find good agreement with the measured data up to $5-6$\,days. Thereafter we find a flux excess in the $riy$ bands which peaks in the observer frame at $\sim20$\,days. This excess shares similar light curve profiles to the type Ic broad-lined supernovae SN~2016jca and SN~2017iuk once corrected for the GRB redshift of $z=0.151$ and arbitrarily scaled. This may be representative of a supernova emerging from the declining afterglow. We measure rest-frame absolute peak AB magnitudes of $M_g=-19.8\pm0.6$ and $M_r=-19.4\pm0.3$ and $M_z=-20.1\pm0.3$. If this is an SN component, then Bayesian modelling of the excess flux would imply explosion parameters of $M_{\rm ej}=7.1^{+2.4}_{-1.7}$ M$_{\odot}$, $M_{\rm Ni}=1.0^{+0.6}_{-0.4}$ M$_{\odot}$, and $v_{\rm ej}=33,900^{+5,900}_{-5,700} kms^{-1}$, for the ejecta mass, nickel mass and ejecta velocity respectively, inferring an explosion energy of $E_{\rm kin}\simeq 2.6-9.0\times10^{52}$ ergs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".