Radio Analysis of SN2004C Reveals an Unusual CSM Density Profile as a Harbinger of Core Collapse
Bibliographic record
Abstract
Abstract We present extensive multifrequency Karl G. Jansky Very Large Array (VLA) and Very Long Baseline Array (VLBA) observations of the radio-bright supernova (SN) IIb SN 2004C that span ∼40–2793 days post-explosion. We interpret the temporal evolution of the radio spectral energy distribution in the context of synchrotron self-absorbed emission from the explosion’s forward shock as it expands in the circumstellar medium (CSM) previously sculpted by the mass-loss history of the stellar progenitor. VLBA observations and modeling of the VLA data point to a blastwave with average velocity ∼0.06 c that carries an energy of ≈1049 erg. Our modeling further reveals a flat CSM density profile ρ CSM ∝ R −0.03±0.22 up to a break radius R br ≈ (1.96 ± 0.10) × 1016 cm, with a steep density gradient following ρ CSM ∝ R −2.3±0.5 at larger radii. We infer that the flat part of the density profile corresponds to a CSM shell with mass ∼0.021 M ☉, and that the progenitor’s effective mass-loss rate varied with time over the range (50–500) × 10−5 M ☉ yr−1 for an adopted wind velocity v w = 1000 km s−1 and shock microphysical parameters ϵ e = 0.1, ϵ B = 0.01. These results add to the mounting observational evidence for departures from the traditional single-wind mass-loss scenarios in evolved, massive stars in the centuries leading up to core collapse. Potentially viable scenarios include mass loss powered by gravity waves and/or interaction with a binary companion.
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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 | 0.000 |
| 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) | 0.001 | 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".