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Record W2039801050 · doi:10.1103/physreva.70.011404

High-order harmonic generation from two-center molecules: Time-profile analysis of nuclear contributions

2004· article· en· W2039801050 on OpenAlexaff
G. Lagmago Kamta, André D. Bandrauk

Bibliographic record

VenuePhysical Review A · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhysicsHarmonicsHigh harmonic generationPolarization (electrochemistry)Atomic physicsNucleusPerpendicularElectronLaserHarmonic spectrumIonizationLinear polarizationQuantum mechanicsIonGeometry

Abstract

fetched live from OpenAlex

We solve the exact three-dimensional time-dependent Schr\"odinger equation for ${{\mathrm{H}}_{2}}^{+}$ (with fixed nuclei) interacting with an intense laser pulse with an arbitrary oriented linear polarization. We find that at equilibrium internuclear distance, the ionization probability of ${{\mathrm{H}}_{2}}^{+}$ is maximum for the parallel orientation of the molecule with respect to the laser polarization, and is minimum for the perpendicular orientation. The contribution of each nucleus to the harmonic spectrum is evaluated, so that interference effects between the two contributions are assessed unambiguously. We show that every half-cycle, high order harmonics are emitted by each nucleus when the electron wave packet returns for a recollision with both nuclei, and that the resulting harmonic emission is predominant for the nucleus that experiences the first recollision. In general, each nucleus emits both even and odd harmonics, but even harmonics are destroyed by interferences between contributions from each nucleus. In general, this destructive interference occurs over a large spread of harmonic orders, which depends on the angle between the molecular axis and the laser polarization.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.010
GPT teacher head0.300
Teacher spread0.290 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations72
Published2004
Admission routes1
Has abstractyes

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