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Record W4285007075 · doi:10.1364/oe.461873

Optical time domain backscattering of antiresonant hollow core fibers

2022· article· en· W4285007075 on OpenAlexaff
Radan Slavı́k, Eric Numkam Fokoua, Thomas D. Bradley, Austin Taranta, Matěj Komanec, Stanislav Zvánovec, Vincent Michaud-Belleau, Francesco Poletti, David J. Richardson

Bibliographic record

VenueOptics Express · 2022
Typearticle
Languageen
FieldEngineering
TopicPhotonic Crystal and Fiber Optics
Canadian institutionsUniversité Laval
FundersEuropean Research CouncilEngineering and Physical Sciences Research CouncilRoyal Academy of Engineering
KeywordsOpticsMaterials scienceCore (optical fiber)Optical fiberPhysics

Abstract

fetched live from OpenAlex

Today's lowest-loss hollow core fibers are based on antiresonance guidance. They have been shown both theoretically and experimentally to have very low levels of backscattering arising from the fiber structure - 45 dB below that of traditional optical fibers with a solid silica glass core. This makes their longitudinal characterization using conventional reflectometric techniques very challenging. However, it was recently estimated that when filled with air, their backscattering coefficient increases to about 30 dB below that of standard solid core fibers. This level should be measurable with commercially available high performance optical time domain reflectometers (OTDR). Here we demonstrate - for the first time to the best of our knowledge - the measurement of backscattering from the air inside a hollow core fiber. We show that the characterization of multi-km long hollow core fibers with 15 m spatial resolution is possible using a commercial OTDR instrument. To benefit from its full dynamic range, we strongly suppress the 4% back-reflections that ordinarily occur at the OTDR's standard fiber output when directly-connected to a hollow core fiber. Furthermore, low coupling loss into the hollow core fiber (0.3 dB in our experiment) also helps to maximize the achievable OTDR signal-to-noise ratio. This approach enables distributed characterization and fault-finding in low-loss hollow core fibers, a topic of increasing importance as these fibers are now starting to be installed in commercial optical communication networks.

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 score0.003

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 communication0.0000.000
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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

Citations43
Published2022
Admission routes1
Has abstractyes

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