Linking the properties of accreting white dwarfs with the ionization state of their ambient medium
Bibliographic record
Abstract
ABSTRACT Steadily accreting white dwarfs (WDs) are efficient sources of ionization and thus are able to create extended ionized nebulae in their vicinity. These nebulae represent ideal tools for the detection of accreting WDs, given that in most cases the source itself is faint. In this work, we combine radiation transfer simulations with known H- and He-accreting WD models, providing for the first time the ionization state and the emission-line spectra of the formed nebulae as a function of the WD mass, the accretion rate and the chemical composition of the accreted material. We find that the nebular optical line fluxes and radial extent vary strongly with the WD’s accretion properties, peaking in systems with WD masses of 0.8–1.2 $\rm M_{\odot }$. Projecting our results on so-called BPT diagnostic diagrams, we show that accreting WD nebulae possess characteristics distinct from those of H ii-like regions, while they have line ratios similar to those in galactic low-ionization emission-line regions. Finally, we compare our results with the relevant constraints imposed by the lack of ionized nebulae in the vicinity of supersoft X-ray sources (SSSs) and Type Ia supernova remnants – sources that are related to steadily accreting WDs. The large discrepancies uncovered by our comparison rule out any steadily accreting WD as a potential progenitor of the studied remnants and additionally require the ambient medium around the SSSs to be less dense than 0.2 $\rm cm^{-3}$. We discuss possible alternatives that could bridge the incompatibility between the theoretical expectations and relevant observations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".