Bibliographic record
Abstract
A highly flexible optical packet compressor is presented. The compressor is capable of providing various compression ratios using the same hardware. It is composed of three parts: a chirped packet generator, a signal compressor, and a wavelength converter. In the chirped packet generator, the modulator intensity-modulates a series of supercontinuum chirped optical carriers and generates a series of chirped optical packets. The signal compressor compresses the chirped packets. The wavelength converter then transforms the compressed wideband optical packets into single-wavelength signals. We numerically demonstrate that using dispersive devices (chirped Bragg grating array or dispersion compensation fiber), we can compress both the width of pulses and the distance among pulses at the same time. This results in an increase of the bit rate. We also show that during the compression, the optical packet suffers distortion in the time domain, which can be defined as an extinction ratio. The distortion can be minimized by control parameters such as carrier chirping and modulating bandwidth. We present a highly flexible optical packet compressor, which is capable of compressing hundreds of bits packets from low speed (mega- or gigabits per second) to very high speed (up to 40 Gbits/s).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".