MESA and NuGrid simulations of classical nova outbursts and nucleosynthesis
Bibliographic record
Abstract
Classical novae are the results of surface thermonuclear explosions of hydrogen accreted by white dwarfs (WDs) from their low-mass main-sequence or red-giant binary companions. Chemical composition analysis of their ejecta shows that nova outbursts occur on both carbon-oxygen (CO) and more massive oxygen-neon (ONe) WDs, and that there is cross-boundary mixing between the accreted envelope and underlying WD. We demonstrate that the state-of-the-art stellar evolution code MESA and post-processing nucleosynthesis tools of NuGrid can successfully be used for modeling of CO and ONe nova outbursts and nucleosynthesis. The convective boundary mixing (CBM) in our 1D numerical simulations is implemented using a diffusion coefficient that is exponentially decreasing with a distance below the bottom of the convective envelope. We show that this prescription produces maximum temperature evolution profiles and nucleosynthesis yields in good agreement with those obtained using the commonly adopted 1D nova model in which the CBM is mimicked by assuming that the accreted envelope has been pre-mixed with WD's material. In a previous paper, we have found that 3He can be produced in situ in solar-composition envelopes accreted with slow rates (Ṁ < 10–10 M⊙/yr) by cold (TWD<107 K) CO WDs, and that convection is triggered by 3He burning before the nova outburst in this case. Here, we confirm this result for ONe novae. Additionally, we find that the interplay between the 3He production and destruction in the solar-composition envelope accreted with an intermediate rate, e.g. Ṁ = 10–10 M⊙/yr, by the 1.15 M⊙ ONe WD with a relatively high initial central temperature, e.g. TWD =15×106 K, leads to the formation of a thick radiative buffer zone that separates the bottom of the convective envelope from the WD surface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".