Bibliographic record
Abstract
Abstract Population transfer from the valence to conduction band in the presence of an intense laser field is explored theoretically in semiconductors and dielectrics. Experiments performed on dielectrics exposed to an intense laser field have divulged a population dynamics between valence and conduction band that differs from that observed in semiconductors. Our paper explores two aspects of ionisation in solids. (i) Contemporary ionisation theories do not take account of the coupling between the valence and conduction bands resulting in the absence the dynamic Stark shift. Our single-particle analysis identifies the absence of the dynamic Stark shift as a possible cause for the contrasting ionisation behaviours observed in dielectric and semiconductor materials. The dynamic Stark shift results in an increased bandgap as the laser intensity is increased. This suppresses ionisation to an extent where the main population dynamics results from virtual oscillations in the conduction band population. The dynamic Stark shift mainly affects larger bandgap materials which can be exposed to decidedly higher laser intensities. (ii) In the presence of laser dressed virtual population of the conduction band, elastic collisions potentially transmute virtual into real population resulting in ionisation. This process is explored in the context of the relaxation time approximation.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".