Observation of thermodynamic phase noise using a slow-light resonance in a fiber Bragg grating
Bibliographic record
Abstract
Thermodynamic phase noise in passive fiber devices is generally so weak that in most devices, in particular fiber sensors, it has only been observed in fiber lengths in the range of 1 meter or much longer. Here we present a passive fiber strain sensor only 4.5 mm in length in which the noise in the frequency range of 1 kHz to ~12 kHz is limited by thermal phase noise in the fiber. The phase noise could be measured in such a short fiber by utilizing a slow-light fiber Bragg grating (FBG) resonator in which the phase noise is magnified by the resonator's slowing-down factor ng/n ≈ 370, where ng is the group index. At the same time, the usually dominant laser frequency noise was brought below the level of the phase noise by using a short fiber and a low-noise laser with a linewidth under 200 Hz. At 4 kHz, the total measured noise expressed in units of strain is 110 fε/√Hz, and the phase noise accounts for 77% of it. This sensor resolves a single-pass thermodynamic length fluctuation of only 5 x10-16 m/√Hz. These measurements provide experimental support for the dependencies of the phase noise on the fiber resonator length and group index predicted by a recent model.
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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 | 0.000 |
| 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".