MétaCan
Menu
Back to cohort
Record W1966916382 · doi:10.1103/physreva.81.051802

Revealing molecular structure and dynamics through high-order harmonic generation driven by mid-IR fields

2010· article· en· W1966916382 on OpenAlexaff
Ricardo Torres, T. Siegel, Leonardo Brugnera, I. Procino, Jonathan G. Underwood, C. Altucci, Raffaele Velotta, Emma Springate, C. A. Froud, I. C. E. Turcu, S. Patchkovskii, Misha Ivanov, Olga Smirnova, J. P. Marangos

Bibliographic record

VenuePhysical Review A · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsSteacie Institute for Molecular Sciences
FundersScience and Technology Facilities CouncilCentral Laser Facility, Science and Technology Facilities CouncilEngineering and Physical Sciences Research Council
KeywordsPhysicsHigh harmonic generationAttosecondLaserMaxima and minimaHarmonic spectrumElectronField (mathematics)InfraredSpectral lineHarmonicElectronic structureAtomic physicsOpticsMolecular physicsUltrashort pulseCondensed matter physicsQuantum mechanics

Abstract

fetched live from OpenAlex

High-order harmonic generation (HHG) from molecules produces spectra that are modulated by interferences that encode both the static structure and the electron dynamics initiated by interaction with the laser field. Using a midinfrared (mid-IR) laser at $1300$ nm, we are able to study the region of the harmonic spectrum containing such interferences in ${\mathrm{CO}}_{2}$ over a wide range of intensities. This allows for isolation and characterization of interference minima arising due to subcycle electronic dynamics triggered by the laser field, which had previously been identified but not systematically separated. Our experimental and theoretical results demonstrate important steps toward combining attosecond temporal and angstrom-scale spatial resolution in molecular HHG imaging.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.289
Teacher spread0.282 · 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

Citations102
Published2010
Admission routes1
Has abstractyes

Explore more

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