Beyond Born–Oppenheimer theory for spectroscopic and scattering processes
Bibliographic record
Abstract
We review our development on beyond Born–Oppenheimer (BBO) theory and its implementation on various models and realistic molecular processes as carried out over the last 15 years. The theoretical formulation leading to the BBO equations are thoroughly discussed with ab initio calculations. We have employed first principle based BBO theory not only to formulate single surface extended Born–Oppenheimer equation to understand the nature of nonadiabatic effect but also to construct accurate diabatic potential energy surfaces (PESs) for important spectroscopic systems, namely, NO2 radical, Na3 and K3 clusters, NO3 radical, benzene and 1,3,5-trifluorobenzene radical cations (C6H6+ and C6H3F3+) as well as triatomic reactive scattering systems like H++H2 and F+H2. The nonadiabatic phenomena like Jahn–Teller (JT), Renner–Teller, pseudo Jahn–Teller effects and the accidental conical intersections are the key players in dictating spectroscopic and reactive scattering profiles. The nature of diabatic coupling elements derived from ab initio data with BBO theory for molecular processes in Franck-Condon region has been analysed in the context of linearly and bilinearly coupled JT model Hamiltonian. The results obtained from quantum dynamical calculations on BBO based diabatic PESs of the above molecular systems are found to be in accord with available experimental outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".