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Record W4391474260 · doi:10.1038/s41377-023-01364-3

Stable, intense supercontinuum light generation at 1 kHz by electric field assisted femtosecond laser filamentation in air

2024· article· en· W4391474260 on OpenAlexafffund
Yaoxiang Liu, Fukang Yin, Tie Jun Wang, Yuxin Leng, Ruxin Li, Zhizhan Xu, See Leang Chin

Bibliographic record

VenueLight Science & Applications · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité LavalInstitut National d'Optique
FundersNSAF Joint FundState Key Laboratory of High Field Laser PhysicsUniversity of Chinese Academy of SciencesShanghai Science and Technology Development FoundationChinese Academy of SciencesBureau of International Cooperation, Chinese Academy of SciencesNational Safety Academic FundShanghai Institute of Optics and Fine Mechanics, Chinese Academy of SciencesNational Natural Science Foundation of ChinaUniversité Laval
KeywordsFilamentationSupercontinuumFemtosecondElectric fieldLaserOpticsMaterials scienceOptoelectronicsPhysicsWavelength

Abstract

fetched live from OpenAlex

Supercontinuum (SC) light source has advanced ultrafast laser spectroscopy in condensed matter science, biology, physics, and chemistry. Compared to the frequently used photonic crystal fibers and bulk materials, femtosecond laser filamentation in gases is damage-immune for supercontinuum generation. A bottleneck problem is the strong jitters from filament induced self-heating at kHz repetition rate level. We demonstrated stable kHz supercontinuum generation directly in air with multiple mJ level pulse energy. This was achieved by applying an external DC electric field to the air plasma filament. Beam pointing jitters of the 1 kHz air filament induced SC light were reduced by more than 2 fold. The stabilized high repetition rate laser filament offers the opportunity for stable intense SC generation and its applications in air.

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 score0.001

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 studies0.0000.000
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 head0.009
GPT teacher head0.267
Teacher spread0.259 · 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

Citations29
Published2024
Admission routes2
Has abstractyes

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