MétaCan
Menu
Back to cohort
Record W1974950632 · doi:10.1117/12.839610

All-fiber, high power, rugged ultrashort-pulse laser source at 1550 nm

2009· article· en· W1974950632 on OpenAlexaff
Vincent Roy, Louis Desbiens, Yves Taillon

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsInstitut National d'Optique
Fundersnot available
KeywordsOpticsMaterials scienceLaserFiber laserAmplifierLaser power scalingLaser beam qualityUltrashort pulseBiophotonicsOptoelectronicsPhysics

Abstract

fetched live from OpenAlex

We present here the architecture of an all-fiber, high-power FCPA source emitting at 1550 nm. This system generates sub-300 fs pulses at a repetition rate of 22 MHz and with an average output power of 1.5 W after pulse compression. The power amplifier consists of a polarization-maintaining Er:Yb doped LMA fiber which results in a beam quality factor M2 < 1.2. The seed laser pulses are stretched to 240 ps using dispersion-shifted fiber before being amplified and compressed using a bulk compressor based on a diffraction grating pair. The output power of the source is not limited by the onset of detrimental nonlinear effects such as self-phase modulation or stimulated Raman scattering since the accumulated nonlinear phase-shift in the power amplifier is well below π rad. Maximum output power is rather limited by the available pump power; a likely five-fold increase, given actual state-of-the-art technology, would thus yield a laser source that may serve as a substitute for widespread solid-state lasers in various fields such as laser machining, biophotonics and nonlinear optics.

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 score0.006

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.007
GPT teacher head0.224
Teacher spread0.216 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdvanced Fiber Laser TechnologiesFrench-language works237,207