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Record W3035302554 · doi:10.1063/5.0008544

Thin plate compression of a sub-petawatt Ti:Sa laser pulses

2020· article· en· W3035302554 on OpenAlexaff
Sergey Mironov, S. Fourmaux, Philippe Lassonde, Vladislav Ginzburg, S. Payeur, J. C. Kieffer, Е. А. Хазанов, G. Mourou

Bibliographic record

VenueApplied Physics Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsInstitut National de la Recherche Scientifique
FundersMinistry of Science and Higher Education of the Russian Federation
KeywordsOpticsBarium borateMaterials scienceLaserCompression (physics)Nonlinear opticsPulse compressionThin filmSecond-harmonic generationCrystal (programming language)Substrate (aquarium)OptoelectronicsPhysicsComposite material

Abstract

fetched live from OpenAlex

By extending the concept of thin film compression [Mourou et al., Eur. Phys. J. Spec. Top. 223(6), 1181 (2014)] to a thin plate, nonlinear post-compression from 24 fs to 13 fs of sub-petawatt laser pulses is demonstrated experimentally using a 1 mm-thick silica plate and chirped mirrors with a total anomalous dispersion of −50 fs2. The measurements were implemented with a specially designed dispersionless vacuum frequency-resolved optical gating, which is based on second harmonic generation of tested pulses in a 10 μm β-barium borate crystal glued on a 1 mm fused silica substrate. The used compression scheme is implemented in a geometry compatible with high power on-target experiment realization.

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 score0.002
Threshold uncertainty score0.007

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.223
Teacher spread0.211 · 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

Citations30
Published2020
Admission routes1
Has abstractyes

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