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Record W2014897647 · doi:10.1103/physreva.84.035402

Nonperturbative time-dependent density-functional theory of ionization and harmonic generation in OCS and CS<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:msub><mml:mrow/><mml:mn>2</mml:mn></mml:msub></mml:math>molecules with ultrashort intense laser pulses: Intensity and orientational effects

2011· article· en· W2014897647 on OpenAlexaff
Emmanuel Penka Fowe, André D. Bandrauk

Bibliographic record

VenuePhysical Review A · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhysicsIonizationHigh harmonic generationAtomic physicsAtomic orbitalMolecular orbitalDensity functional theoryLaserMoleculeIonQuantum mechanicsElectron

Abstract

fetched live from OpenAlex

Molecular high-order harmonic generation (MHOHG) and molecular orbital ionization rates are calculated for the nonsymmetric OCS and symmetric CS${}_{2}$ molecules using numerical solutions of Kohn-Sham (KS) equations of time-dependent density functional theory in the nonlinear nonperturbative regime of laser-molecule interactions for different laser-molecule orientations and intensities. It is found that the ionization of inner-shell KS molecular orbitals contributes significantly to the ionization and MHOHG processes for intensities I \ensuremath{\ge} 3.5 \ifmmode\times\else\texttimes\fi{} 10${}^{14}$ W/cm${}^{2}$. Ionization rate maxima correspond to the alignment of maximum KS orbital densities with the laser pulse polarization instead of orbital ionization potentials. Furthermore, degeneracies of orbitals are removed as a function of laser-molecule angle, thus affecting ionization rates, the MHOHG spectra, and their polarizations, the latter allowing for identifying inner-orbital ionization.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.241
Teacher spread0.226 · 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

Citations42
Published2011
Admission routes1
Has abstractyes

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Same venuePhysical Review ASame topicLaser-Matter Interactions and ApplicationsFrench-language works237,207