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Record W2968632791 · doi:10.1103/physreva.100.023404

Vibrationally resolved above-threshold ionization in NO molecules by intense ultrafast two-color laser pulses: An experimental and theoretical study

2019· article· en· W2968632791 on OpenAlexaff
Yong Liu, Hu Wen-Hui, Sizuo Luo, Kai‐Jun Yuan, Zhigang Sun, André D. Bandrauk, Dajun Ding

Bibliographic record

VenuePhysical review. A/Physical review, A · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
FundersChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsPhotoionizationIonizationAtomic physicsPhysicsAbove threshold ionizationPhotoelectric effectLaserUltrashort pulseFemtosecondElectronSpectral lineIonOptics

Abstract

fetched live from OpenAlex

We present above-threshold ionization (ATI) in the molecule nitric oxide, NO, by intense (${10}^{12}--{10}^{13}\phantom{\rule{0.28em}{0ex}}\mathrm{W}/{\mathrm{cm}}^{2}$) two-color femtosecond laser pulses. Vibrationally resolved coherent interference phenomena of multiphoton and multipathway ionization processes have been investigated by measuring experimentally and modeling theoretically the molecular photoionization yields. We find that the ATI photoelectron distribution of NO, initiated from degenerate electronic and vibrational states, depends on the relative phase of the two pulses, the kinetic energy, and emission angle of the photoelectrons. This dependence codes the information of interference effects of molecular electronic states. AC Stark effects modulate interference patterns in ATI spectra. Moreover, the ATI spectra exhibit peak energy dependencies that illustrate interference effects from coherent couplings between various ionization channels. These features reflect the molecular property and the multiple channel ionization interference effects in ATI processes. The results allow to explore coherent electron-vibration processes in ultrafast molecular photoionization.

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 categoriesMeta-epidemiology (narrow)
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 score0.204
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.342
Teacher spread0.335 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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