Late-time Hubble Space Telescope Observations of AT 2018cow. I. Further Constraints on the Fading Prompt Emission and Thermal Properties 50–60 days Post-discovery
Bibliographic record
Abstract
Abstract The exact nature of the luminous fast blue optical transient AT 2018cow is still debated. In this first of a two-paper series, we present a detailed analysis of three Hubble Space Telescope (HST) observations of AT 2018cow covering ∼50–60 days post-discovery in combination with other observations throughout the first two months and derive significantly improved constraints of the late thermal properties. By modeling the spectral energy distributions (SEDs), we confirm that the UV–optical emission over 50–60 days was still a smooth blackbody (i.e., optically thick) with a high temperature (T BB ∼ 15,000 K) and small radius (R BB ≲ 1000 R ⊙). Additionally, we report for the first time a break in the bolometric light curve: the thermal luminosity initially declined at a rate of L BB ∝ t −2.40 but faded much faster at t −3.06 after day 13. Reexamining possible late-time power sources, we disfavor significant contributions from radioactive decay based on the required 56Ni mass and lack of UV line blanketing in the HST SEDs. We argue that the commonly proposed interaction with circumstellar material may face significant challenges in explaining the late thermal properties, particularly the effects of the optical depth. Alternatively, we find that continuous outflow/wind driven by a central engine can still reasonably explain the combination of a receding photosphere, optically thick and rapidly fading emission, and intermediate-width lines. However, the rapid fading may have further implications on the power output and structure of the system. Our findings may support the hypothesis that AT 2018cow and other “Cow-like transients” are powered mainly by accretion onto a central engine.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".