MétaCan
Menu
Back to cohort
Record W4362588119 · doi:10.1364/ol.487172

Self-injection locking of a low-noise erbium-doped random fiber laser by a random fiber grating ring

2023· article· en· W4362588119 on OpenAlexafffund
Chen Chen, Haiyang Wang, Ping Lü, Stephen J. Mihailov, Liang Chen, Xiaoyi Bao

Bibliographic record

VenueOptics Letters · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsOpticsRelative intensity noiseFiber Bragg gratingLaser linewidthMaterials scienceFiber laserPhase noiseLasing thresholdNoise (video)JitterPhysicsOptical fiberLaserSemiconductor laser theoryTelecommunications

Abstract

fetched live from OpenAlex

We demonstrate a self-injection locking (SIL) in an Er-doped random fiber laser by a high quality factor (high-Q) random fiber grating ring (RFGR) resonator, which enables a single-mode narrow-linewidth lasing with ultra-low intensity and frequency noise. The RFGR resonator includes a fiber ring with a random fiber grating to provide random feedback modes and noise suppression filters with self-adjusted peak frequency adaptable to small perturbations allowing single longitudinal mode over 7000 s with frequency jitter below 3.0 kHz. Single-mode operation is accomplished by carefully controlling phase delays and mode coupling of resonant modes between main ring and RFGR with a side-mode suppression ratio of 70 dB and narrow linewidth of 1.23 kHz. The relative intensity noise is −140 dB/Hz above 100 kHz and the frequency noise is 1 Hz/Hz 1/2 above 10 kHz.

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 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 score0.163
Threshold uncertainty score0.984

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 head0.005
GPT teacher head0.209
Teacher spread0.204 · 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 teacher head, 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

Citations8
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueOptics LettersSame topicRandom lasers and scattering mediaFrench-language works237,207