Increasingly Complex Systems in Intense Laser Fields
Bibliographic record
Abstract
With more atoms in a system, coupling between quantum states complicates the system dynamics. We shine intense laser pulses on three systems with increasing complexity: a molecule, a dimer, and a solid. For single molecules, a 400 nm photon excites NO_2 and initiates a dissociation process. We probe the dynamics using a strong laser pulse to ionize the molecule, and detect the resulting electrons and ions. The evolution of the NO-O molecular bond was directly measured in our experiment. For dimers, a laser pulse removes three electrons from (CO)_2. The dimer breaks up into C^+, O^+ and CO^+. Compared to a monomer, CO^{2+} in the dimer has a new prompt dissociation pathway that produces fragments with higher kinetic energy. Calculation shows that the Coulomb field of the neighboring CO^+ modifies the electronic state of the dimer, giving rise to a prompt channel. Coupling between different charge state configurations results in a new dimer electronic state, which leads to dissociation with higher kinetic energy. For solids, coupling among many atoms creates bands and a bandgap that plays the role of the ionization potential and reduces the threshold for electron-hole pair generation. Thus, solids are a good medium for high-order harmonic generation at the high repetition rates needed for frequency combs. We generate up to the 7th harmonic in silicon and zinc oxide with femtosecond pulses from a thulium fiber laser.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".