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Record W3199224259 · doi:10.1002/adpr.202100113

Raman Red‐Shift Compressor: A Simple Approach for Scaling the High Harmonic Generation Cut‐Off

2021· article· en· W3199224259 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvanced Photonics Research · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsHigh harmonic generationRaman scatteringPhotonLaserScalingPhoton energyRaman spectroscopyOpticsUltravioletWavelengthPhysicsMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

The use of ultrashort laser pulses with long wavelengths as drivers is a relevant strategy for scaling high harmonic generation (HHG) to higher photon energies. Here, stimulated Raman scattering enhanced by the formation of multidimensional solitary states in a molecular gas‐filled hollow‐core fiber as the mechanism to produce a versatile HHG driver is reported on. This recently discovered method allows to red shift and to compress conventional subpicosecond laser pulses with a simple experimental apparatus, ultimately increasing the generated photon energy, while assuring a high photon flux. The adaptability, simplicity, and stability of this method make it attractive for tailoring HHG sources to individual applications at specific photon energies. Measurements of resonant magnetic scattering in a cobalt/platinum multilayer sample are presented as a demonstration of the relevance of this approach for photon‐hungry applications in the extreme ultraviolet.

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.

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 categoriesnone
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 score0.337
Threshold uncertainty score0.793

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.078
GPT teacher head0.388
Teacher spread0.310 · 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