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Floquet calculation of harmonic generation from hydrogen molecular ions in strong monochromatic laser fields

2014· article· en· W2031314630 on OpenAlexaff
Ts. Tsogbayar, Marko Horbatsch

Bibliographic record

VenueJournal of Physics B Atomic Molecular and Optical Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsFloquet theoryHigh harmonic generationAtomic physicsIonIonizationPhysicsSchrödinger equationLaserSpectral lineHarmonicQuantum mechanicsNonlinear system

Abstract

fetched live from OpenAlex

We present Floquet calculations of high harmonic generation (HHG) for the lowest two electronic states of the ion by strong continuous-wave laser fields. We solve the non-Hermitian matrix problem to get accurate solutions to the periodic time-dependent Schrödinger equation (TDSE) by applying a pseudospectral representation combined with a complex absorbing potential method. This represents an alternative approach to direct TDSE solutions to obtain the harmonic spectra for the ion. We compare our HHG rates for the lower and upper states of , which correspond to the gerade and ungerade ground states in the field-free case, with previously obtained results in the literature. We show that the enhancement of the ionization rates at the critical internuclear separation R c ≈ 8 au plays some role in the appearance of very strong harmonic orders n = 5–11 at λ = 1064 nm and n = 5–9 at λ = 800 nm and intensity I = 10 14 W cm −2 .

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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

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 science0.0010.001
Research integrity0.0010.001
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 head0.010
GPT teacher head0.253
Teacher spread0.243 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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