MétaCan
Menu
Back to cohort
Record W2022469148 · doi:10.1103/physreva.62.031401

Intense-laser-field-enhanced ionization of two-electron molecules: Role of ionic states as doorway states

2000· article· en· W2022469148 on OpenAlexaff
Isao Kawata, Hirohiko Kono, Y. Fujimura, André D. Bandrauk

Bibliographic record

VenuePhysical Review A · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhysicsAtomic physicsIonizationExcited stateGround stateIonic bondingElectronAdiabatic processPopulationIonQuantum mechanics

Abstract

fetched live from OpenAlex

We investigate the mechanism of enhanced ionization in two-electron molecules by solving exactly the time-dependent Schr\"odinger equation for a one-dimensional ${\mathrm{H}}_{2}$ in an ultrashort, intense $(I>~{10}^{14}{\mathrm{W}/\mathrm{c}\mathrm{m}}^{2})$ laser pulse $(\ensuremath{\lambda}=1064\mathrm{nm}).$ Enhanced ionization in two-electron systems differs from that in one-electron systems in that the excited ionic state ${\mathrm{H}}^{\mathrm{\ensuremath{-}}}{\mathrm{H}}^{+}$ regarded as the dominant doorway state to ionization crosses the covalent ground state HH in field-following time-dependent adiabatic energy. An analytic expression for the crossing condition obtained in terms of the lowest three states agrees with the numerical results. The gap at the avoided crossing decreases the initial covalent component and promotes electron transfer to ${\mathrm{H}}^{\mathrm{\ensuremath{-}}}{\mathrm{H}}^{+}.$ As the internuclear distance R decreases, the population of the ${\mathrm{H}}^{\mathrm{\ensuremath{-}}}{\mathrm{H}}^{+}$ created increases, whereas the ionization rate from a ${\mathrm{H}}^{\mathrm{\ensuremath{-}}}{\mathrm{H}}^{+}$ decreases owing to the stronger attraction by the distant nucleus. As a result, the rate has a peak at $R\ensuremath{\approx}6\mathrm{a}.\mathrm{u}.,$ where most adiabatic states avoid each other with considerable gaps.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.004
GPT teacher head0.293
Teacher spread0.289 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations78
Published2000
Admission routes1
Has abstractyes

Explore more

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