The GRASP atomic structure code - current status, the CompAS collaboration and hopes for the future
Bibliographic record
Abstract
The quality and resolution of solar, stellar, and other types of astrophysical spectra have improved to the extent that the accuracy and availability of atomic data is frequently a limiting factor in the interpretation of observations in astronomy. With the new generation of ground-based spectrographs and space missions, such as the recent CRIRES+ upgrade on the Very Large Telescope (VLT) and the James Webb Space Telescope (JWST), new demands are put on complete and accurate atomic data in the relatively unexplored infrared (IR) spectral regime. In particular, data on heavy, complex atomic species such as the various ionization stages of the Lanthanide and Actinide group of elements are needed for the interpretation of more exotic astrophysical events involving neutron-capture elements such as the Kilonova (KN) ejecta following the neutron-star merger observed in 2017. Analyses of such events require not only data of spectroscopic accuracy, e.g. for element identifications, but also complete data for accurate opacities in the radiative-transfer modeling to track e.g. the brightness evolution. Laboratory measurements, e.g. using ion/traps, beam-foil, or laser techniques, have been performed for isolated transitions and atoms, but no systematic laboratory studies exist or are currently in progress. Instead, the bulk of these atomic data must be calculated. To solve these new challenges, multiconfigurational (Dirac-) Hartree-Fock methods, either non-relativistic with Breit-Pauli corrections or fully relativistic, could be considered a promising way forward. The main advantage of these approaches is their general applicability to excited and open-shell systems, including open f- and g-shells, across the whole periodic table, thus allowing for the production of extensive atomic data sets with transition energies and probabilities. Additional physical properties of interest can readily be determined from the obtained wavefunctions. The accuracy of such calculations depends on the complexity of the shell structure and on the underlying adopted model for describing electron correlation. By systematically increasing the basis in large-scale calculations, as well as exploring different models for electron correlation, it is often possible to provide an estimate of the accuracy. In this talk I will describe our current, [open-source](https://github.com/compas ), community effort within the Computational Atomic Physics ([CompAS](https://compas.github.io )) collaboration, to build upon the important and acclaimed work on state-of-the-art multiconfigurational codes by Profs. Charlotte F Fischer and Ian P Grant, with a particular focus on the relativistic variant: the general-purpose relativistic atomic structure package, [GRASP](https://doi.org/10.1016/j.cpc.2018.10.032 ).
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".