Dielectronic recombination and satellite line spectra of highly charged tungsten ions<sup>1</sup>This article is part of a Special Issue on the 10th International Colloquium on Atomic Spectra and Oscillator Strengths for Astrophysical and Laboratory Plasmas.
Bibliographic record
Abstract
We present our recent progress on theoretical studies that involve auto-ionizing states of highly charged tungsten ions. Such auto-ionizing states have two channels for decay, which requires that both radiative and auto-ionization atomic data be calculated and combined in a detailed study of the dielectronic recombination (DR). Three atomic codes are used to produce relativistic atomic data (energy levels, radiative transition probabilities, and auto-ionization rates). These are the relativistic many-body perturbation theory (RMBPT) code, the multiconfiguration relativistic Hebrew University Lawrence Livermore atomic code (HULLAC), and the Hartree–Fock relativistic (Cowan) code. Branching ratios relative to the first threshold and intensity factors are calculated for satellite lines, and DR rate coefficients are determined for the excited states. The total DR rate coefficient is derived as a function of electron temperature, and it is shown that the contribution of the highly excited states is very important for the calculation of the total DR rates. Synthetic dielectronic satellite spectra are constructed, and the atomic properties specific to the relevant tungsten ions are highlighted. First, we will consider the results for Na-like tungsten (W 63+ ) and Mg-like tungsten (W 62+ ) using all three codes. Then, we move to even higher ionization states and present the results in Li-like W (W 71+ ). For this we use the RMBPT code as well as the quasi-relativistic many-body perturbation theory (MZ) code. The inclusion of the DR process is essential for correct identification of the lines in impurity spectra and for understanding the main contributions to the total radiation losses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".