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Record W2005472741 · doi:10.1364/ol.30.001225

Remote transfer of a high-stability and ultralow-jitter timing signal

2005· article· en· W2005472741 on OpenAlexaff
Kevin W. Holman, Darren D. Hudson, Jun Ye, David J. Jones

Bibliographic record

VenueOptics Letters · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJitterTime transferOpticsBandwidth (computing)SIGNAL (programming language)Phase noiseNoise floorNoise (video)Optical fiberPhysicsComputer scienceTelecommunicationsAcousticsNoise reductionNoise measurement

Abstract

fetched live from OpenAlex

Transfer of a high-stability and ultralow-jitter timing signal through a fiber network via a mode-locked fiber laser is demonstrated. With active cancellation of the fiber-transmission noise, the fractional instability for transfer of a radio-frequency signal through a 6.9- (4.5-) km round-trip installed (laboratory-based) fiber network is below 9(7) x 10(-15) tau(-1/2) for an averaging time tau > or = 1 s, limited by the noise floor of the frequency-counting system. The noise cancellation reduces the rms timing jitter, integrated over a bandwidth from 1 Hz to 100 kHz, to 37 (20) fs for the installed (laboratory-based) fiber network, representing what is to our knowledge the lowest reported jitter for transfer of a timing signal over kilometer-scale distances using an installed (laboratory-based) optical-fiber network.

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)0.001
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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

Citations88
Published2005
Admission routes1
Has abstractyes

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