New radiative and collisional atomic data for Sr <scp>ii</scp> and Y <scp>ii</scp> with application to Kilonova modelling
Bibliographic record
Abstract
ABSTRACT The spectra of singly ionized Strontium and Yttrium (Sr ii and Y ii) have been proposed as identifications of certain spectral features in the AT2017gfo spectrum. With the growing demand for non-local-thermodynamic-equilibrium (NLTE) simulations of Kilonovae, there is an increasing need for atomic data for these and other r-process elements. Our goal is to expand upon the current set of atomic data for r-process elements, by presenting transition probabilities and Maxwellian-averaged effective collision strengths for Sr ii and Y ii. The Breit–Pauli and darcR-matrix codes are employed to calculate the appropriate collision strengths, which are thermally averaged according to a Maxwellian distribution to calculate excitation and de-excitation rates. The tardis and ColRadPy packages are subsequently used to perform local thermodynamic equilibrium (LTE) and NLTE modelling, respectively. A complete set of transition probabilities and effective collision strengths involving levels for Sr ii and Y ii have been calculated for temperature ranges compatible with kilonova plasma conditions. Forbidden transitions were found to disagree heavily with the Axelrod approximation, an approximation which is currently employed by other models within the literature. Theoretically important spectral lines are identified with both LTE and NLTE modelling codes. LTE simulations in tardis reveal no new significant changes to the full synthetic spectra. NLTE simulations in ColRadPy provide indications of which features are expected to be strong for a range of regimes, and we include luminosity estimates. Synthetic emission spectra over kilonova densities and temperatures reveal potentially interesting spectral lines in the NIR.
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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 | 0.001 |
| 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".