MétaCan
Menu
Back to cohort
Record W4415134902 · doi:10.1364/ol.576854

High peak intensity characterization and optimization with a tight-focusing transmission parabola

2025· article· en· W4415134902 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

VenueOptics Letters · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDigital Holography and Microscopy
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du CanadaCanada Foundation for Innovation
KeywordsWavefrontParabolaIntensity (physics)LaserLaser beam qualityParabolic reflectorDeformable mirrorBeam (structure)Transmission (telecommunications)Cardinal point

Abstract

fetched live from OpenAlex

A transmission parabola is a tight-focusing on-axis parabolic reflector that potentially enables ultra-high intensities when combined with high-power laser pulses. We propose a method to characterize the peak intensity generated with this optic by measuring the laser beam wavefront after reflection. The focused electromagnetic field and the corresponding peak intensity at the focal plane are calculated using the Stratton-Chu formulation. Without wavefront corrections, the measured intensity is strongly degraded due to alignment constraints and the quality of the manufactured optic. The intensity reached is at most 6% of the ideal case, where the beam wavefront is perfectly flat and aberration-free. However, we demonstrate that the focused peak intensity can be improved substantially by correcting the laser beam wavefront with a deformable mirror. An intensity approaching 70% of the ideal case is obtained, thus showing the relevance of the transmission parabola for high-intensity applications.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.003
GPT teacher head0.192
Teacher spread0.189 · 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