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Record W2084290665 · doi:10.1117/1.2173959

Optical packet compressor

2006· article· en· W2084290665 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOptical Engineering · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChirpOpticsFiber Bragg gratingExtinction ratioComputer scienceMaterials sciencePhysicsWavelengthLaser

Abstract

fetched live from OpenAlex

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).

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.872
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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