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Record W2010129358 · doi:10.1109/lpt.2012.2206580

Phase-Coded Millimeter-Wave Waveform Generation Using a Spatially Discrete Chirped Fiber Bragg Grating

2012· article· en· W2010129358 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

VenueIEEE Photonics Technology Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFiber Bragg gratingWaveformOpticsComb filterMaterials sciencePulse shapingPulse compressionOptical filterExtremely high frequencyOptical fiberGratingPhysicsComputer scienceBandwidth (computing)TelecommunicationsLaser

Abstract

fetched live from OpenAlex

An all-optical approach to generating phase-coded millimeter-wave (mm-wave) waveforms based on optical pulse shaping, using a spatially discrete chirped fiber Bragg grating (SD-CFBG) is proposed and experimentally demonstrated. Since no electro-optical modulator is used, the system is simpler and less costly. In the proposed system, the spectrum of an optical pulse is spectrally sliced by a sinusoidal comb filter. The SD-CFBG is then used as a special dispersive element to map the shaped spectrum to a temporal waveform based on dispersive Fourier transform, and at the same time, to introduce the desired time delay jumps, which are translated to phase shifts. A simplified system without using the comb filter is also studied, in which a single SD-CFBG is employed to simultaneously perform spectral slicing, frequency-to-time mapping, and temporal coding. The proposed technique is validated by two experiments in which two phase-coded mm-wave waveforms at 28.5 GHz and 47.2 GHz with, respectively, a 7-bit and 11-bit Barker code are generated.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.276
Teacher spread0.238 · 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