Angle-dependent strong-field ionization of triple bonded systems calculated by time-dependent configuration interaction with an absorbing potential
Bibliographic record
Abstract
The angle dependence of strong field ionization has been studied for a set of molecules containing triple bonds: HCCH, HCN, HCC–CN, H2N–CCH, H2N–CN, and H2N–CC–CN. Time-dependent configuration interaction (TDCI) with a complex absorbing potential was used to model strong field ionization by a linearly polarized seven-cycle 800 nm cosine squared pulse. The ionization yields have been calculated as a function of the laser intensity and polarization direction and plotted as three-dimensional surfaces. At low field strengths, the angular dependence can be understood in terms of ionization from the highest occupied orbitals. At higher laser intensities, ionization occurs from lower lying orbitals as well as from the highest occupied orbitals, as indicated by changes in the angular dependence of the ionization yield and by variations in the population analysis of the TDCI wavefunction with the intensity of the laser field. The ionization yield for directions parallel to the molecular axis increases more rapidly than perpendicular to the axis as the conjugation length is increased. NH2 substitution substantially increases the ionization yield along the molecular axis but has only a small effect for perpendicular directions.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".