Optical time domain backscattering of antiresonant hollow core fibers
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".