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Record W2101772871 · doi:10.1109/lpt.2007.895898

An Approach to Photonic Generation of High-Frequency Phase-Coded RF Pulses

2007· article· en· W2101772871 on OpenAlexaff
Hao Chi, Jianping Yao

Bibliographic record

VenueIEEE Photonics Technology Letters · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Fiber Laser Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOpticsRadio frequencyPhotonicsInterferometryPhase (matter)ChirpMaterials sciencePulse (music)PhysicsLaserOptoelectronicsTelecommunicationsDetectorComputer science

Abstract

fetched live from OpenAlex

A novel method to generate high-frequency phase-coded RF pulses using all-fiber components is proposed. The system consists of a mode-locked fiber laser (MLFL), a dispersive element, an unbalanced Mach-Zehnder interferometer (UMZI), an optical phase modulator (PM), and a photodetector (PD). The PM is incorporated in one arm of the UMZI. In the system, an ultrashort pulse generated by the MLFL is broadened and chirped after passing through the dispersive element, which is then sent to the UMZI, to get two time-delayed chirped pulses. By beating the time-delayed chirped pulses at the PD, an RF pulse with its frequency dependent on the time delay difference is obtained. The generated RF pulse can be phase coded if an encoding signal is applied to the PM. A theoretical model is presented which is verified by experiments. The generation of RF pulses with binary phase coding is also experimented

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.279
Teacher spread0.262 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations72
Published2007
Admission routes1
Has abstractyes

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