Moving adaptive grid methods for numerical solution of the time-dependent molecular Schrödinger equation in laser fields
Bibliographic record
Abstract
We present a moving adaptive grid method for solving the time-dependent Schrödinger equation, TDSE, for molecules in intense laser fields, applicable in the nonperturbative nonlinear regime where dissociation ionization occurs. The method is based on a Lagrangian, moving coordinate system. In this representation, the reference system is moving with the laser pulse so that the classical movement of free particles in the field, i.e., in the asymptotic region where electron–molecule potentials are negligible but the laser field is still present, is exactly described. As a consequence, the asymptotic quantum wave functions are exact in presence of a laser pulse. We have tested several discrete propagator methods for the TDSE in different gauges in a Born–Oppenheimer simulation of H2+ in a short, intense laser pulse. Our comparison of convergence between the same discretization methods for different gauges have demonstrated the superiority of the present Lagrangian adaptive grid method to treat the response of molecules to intense time-dependent electromagnetic fields.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".