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Record W2076871270 · doi:10.1139/p01-138

Nonlinear excitation and ionization of diatomic molecules by short laser pulses. Model of two active electrons in the field of a frozen core

2002· article· en· W2076871270 on OpenAlexaffvenue
A. I. Pegarkov

Bibliographic record

VenueCanadian Journal of Physics · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPhysicsDiatomic moleculeAtomic physicsIonizationElectronExcitationLaserField (mathematics)Pulse (music)PopulationIonMoleculeOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The dynamics of electron excitation and ionization of diatomic molecules in short laser pulses is studied within a model of two active 1D electrons moving in the field of a frozen core. It is shown for example for the N2 molecule that the model reproduces the spectrum of the pulse-free Σ electronic states very well. The N2 electron dynamics is examined numerically for short τ = 30 fs and ultra-short τ = 5 fs laser pulses with λ = 800 nm and intensity 1013 W/cm2 ÷ 1015 W/cm2 as well as for the resonant pulse with τ = 1 fs and λ = 147 nm, 1014 W/cm2 ÷ 1016 W/cm2. The phenomena of strong above-threshold absorption and resonant revival of electronic ground-state population in the ultra-short resonant pulse are found. Within the model, the quantum-mechanical picture of one-electron, two-electron, sequential, and nonsequential molecular ionizations is analyzed in detail in comparison with recent experimental results of Cornaggia and Hering, and Gibson et al. The model correctly explains the origin and nonlinear dynamics of the well-known "shoulder" in the N2+2 ion yield. PACS Nos.: 33.80Rv, 33.80Wz

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.261
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2002
Admission routes2
Has abstractyes

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