Non-thermal radio emission from colliding flows in classical nova V1723 Aql
Bibliographic record
Abstract
The importance of shocks in nova explosions has been highlighted by Fermi's discovery of γ-ray-producing novae. Over three years of multiband Very Large Array radio observations of the 2010 nova V1723 Aql show that shocks between fast and slow flows within the ejecta led to the acceleration of particles and the production of synchrotron radiation. Soon after the start of the eruption, shocks in the ejecta produced an unexpected radio flare, resulting in a multipeaked radio light curve. The emission eventually became consistent with an expanding thermal remnant with mass 2 × 10−4 M⊙ and temperature 104 K. However, during the first two months, the ≳106 K brightness temperature at low frequencies was too high to be due to thermal emission from the small amount of X-ray-producing shock-heated gas. Radio imaging showed structures with velocities of 400 km s−1 (d/6 kpc) in the plane of the sky, perpendicular to a more elongated 1500 km s−1 (d/6 kpc) flow. The morpho-kinematic structure of the ejecta from V1723 Aql appears similar to nova V959 Mon, where collisions between a slow torus and a faster flow collimated the fast flow and gave rise to γ-ray-producing shocks. Optical spectroscopy and X-ray observations of V1723 Aql during the radio flare are consistent with this picture. Our observations support the idea that shocks in novae occur when a fast flow collides with a slow collimating torus. Such shocks could be responsible for hard X-ray emission, γ-ray production, and double-peaked radio light curves from some classical novae.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".