Arbitrary-order all-fiber temporal differentiator based on a fiber Bragg grating: design and experimental demonstration
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.
Bibliographic record
Abstract
A new technique to design an all-fiber temporal differentiator that has a large bandwidth and an arbitrary differentiation order is proposed and investigated. The proposed temporal differentiator is a special fiber Bragg grating (FBG) that is designed by controlling its magnitude and phase responses with the discrete layer peeling (DLP) method. There are three important features of this technique: 1) the temporal differentiator has an arbitrary magnitude response and a controllable bandwidth; 2) the temporal differentiator can be designed and fabricated with an arbitrary differentiation order that is realized in a single FBG; 3) the required maximum index modulation of the FBG-based differentiator is largely decreased by using a Gaussian windowing function. The use of the proposed technique to design temporal differentiators with a differentiation order up to the fourth and with a bandwidth up to 500 GHz is studied. A proof-of-concept experiment is then carried out. A first- and a second-order temporal differentiator with a bandwidth of 25 GHz are experimentally demonstrated.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it