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Record W2063501753 · doi:10.1103/physreva.64.023408

Total ionization rates and ion yields of atoms at nonperturbative laser intensities

2001· article· en· W2063501753 on OpenAlexaff
Andreas Becker, Luis Plaja, Pablo Moreno, Muhammad Nurhuda, F. H. M. Faisal

Bibliographic record

VenuePhysical Review A · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité Laval
FundersConsejería de Educación, Junta de Castilla y LeónDeutsche ForschungsgemeinschaftMinisterio de Educación y CulturaEuropean CommissionAlexander von Humboldt-Stiftung
KeywordsPhysicsIonizationAtomic physicsWavelengthIonFloquet theoryLaserAdiabatic processPulse (music)Atom (system on chip)Intensity (physics)OpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We investigate a simply corrected Keldysh-Faisal-Reiss (KFR) rate formula for laser-induced ionization of atoms in the nonperturbative intensity domain. Predictions of the formula are compared, first, with ab initio Floquet calculations, which show good agreement in the nonperturbative intensity domain for not too short wavelengths. Second, they are found to agree with the results of numerical simulations for the H atom, provided the pulse lengths are not shorter than three field cycles, so that the adiabatic rate becomes a valid parameter. Finally, total single-ionization yields predicted by the present model are compared with 36 different experimental data sets for He, Ne, Ar, Kr, and Xe, covering both linear and circular polarizations, and different wavelengths, pulse durations, and intensities; the results show a remarkable overall agreement with the data.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.297
Teacher spread0.284 · 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 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

Citations88
Published2001
Admission routes1
Has abstractyes

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