Strong field ionization of many electron systems: A quantum chemical challenge
Bibliographic record
Abstract
A non-variational Time-Dependent Multiconfiguration Self-Consistent Field (TDMCSCF) scheme has been developed [Nguyen-Dang T.T., Peters M., Wang S.-M., Sinelnikov E., and Dion F., J. Chem. Phys. 127, 174107 (2007)] to describe, by an ab-initio approach, the time-resolved electron dynamics of a laser-driven many-electron atomic or molecular system. As an L 2 method, this approach faces severe challenges when ionization and large-amplitude electronic motions are addressed. We present here an extension of this TDMCSCF scheme to include multiple ionization processes, using a Feschbach state-partitioning formalism, allowing the bound electrons’ dynamics to be treated by the L 2-TDMCSCF method, while the ionized electrons can be treated separately by an alternative approach. We present results of proof-of-principle calculations pertaining to the single and double ionizations of H 2 and discuss methodological issues such as the systematic corrections that could be brought, using this approach, to the strong field approximation (SFA).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".