Interpreting the dynamics of HCl<sup>+</sup>dissociation in a strong laser field at = 10.3 µm
Bibliographic record
Abstract
The strong field dissociation of HCl + at a wavelength of λ = 10.3 µm is examined in detail, using quantum wavepacket and trajectory methods. A three-potential-curve treatment, which currently offers the most theoretically complete description of the molecular dynamics, is used to simulate the dissociation process, and provides predictions of the dissociation probability, electronic branching ratios and kinetic energy distributions. Classical trajectory simulations on a single potential curve (ground state of HCl + ) are used to increase understanding of simulations performed using three potential curves. The impact on predicted product properties of using two potential curves (ground and first excited states) versus three potential curves is also explored. The fragment's kinetic energy distributions are discussed extensively and quantum simulation results interpreted with the aid of classical trajectories as well as simple models such as a wagging potential tail model, developed by Thachuk and Wardlaw (1995 J. Chem. Phys. 102 7462). A tunnelling variant of a barrier suppression model, used for predicting the dissociation threshold, is developed, and shown to be more accurate than previous models.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".