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Record W2119991573 · doi:10.1364/ol.39.001038

Suppression of thermal frequency noise in erbium-doped fiber random lasers

2014· article· en· W2119991573 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 · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOpticsRayleigh scatteringFiber laserNoise (video)Phase noiseMaterials scienceRelative intensity noiseLaserPhysicsLaser linewidthSemiconductor laser theoryComputer science

Abstract

fetched live from OpenAlex

Frequency and intensity noise are characterized for erbium-doped fiber (EDF) random lasers based on Rayleigh distributed feedback mechanism. We propose a theoretical model for the frequency noise of such random lasers using the property of random phase modulations from multiple scattering points in ultralong fibers. We find that the Rayleigh feedback suppresses the noise at higher frequencies by introducing a Lorentzian envelope over the thermal frequency noise of a long fiber cavity. The theoretical model and measured frequency noise agree quantitatively with two fitting parameters. The random laser exhibits a noise level of 6 Hz²/Hz at 2 kHz, which is lower than what is found in conventional narrow-linewidth EDF fiber lasers and nonplanar ring laser oscillators (NPROs) by a factor of 166 and 2, respectively. The frequency noise has a minimum value for an optimum length of the Rayleigh scattering fiber.

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 score0.248
Threshold uncertainty score0.483

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 head0.205
Teacher spread0.200 · 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