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Record W2128940827 · doi:10.1109/lpt.2007.894942

Photonic Microwave Bandpass Filter With Negative Coefficients Using a Polarization Modulator

2007· article· en· W2128940827 on OpenAlexaff
Jianping Yao, Qing Wang

Bibliographic record

VenueIEEE Photonics Technology Letters · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBand-pass filterPolarization (electrochemistry)MicrowavePhotonicsPhysicsOpticsOptical filterOrthogonal polarization spectral imagingOptoelectronicsLaser

Abstract

fetched live from OpenAlex

A novel photonic microwave bandpass filter with negative coefficients implemented using a polarization modulator (PolM) is proposed and experimentally demonstrated. In the proposed filter, a lightwave from a tunable laser source (TLS) is sent to a PolM, with the incident lightwave adjusted to have its polarization direction aligned at an angle of plusmn45deg to the principal axes of the PolM. A microwave signal is applied to the PolM through its RF port. Thanks to the polarization modulation in the PolM, two complementary microwave signals with identical amplitudes carried by two optical carriers with orthogonal polarizations are generated. The two complementary optical microwave signals are then sent to an optical delay line consisting of one section or two sections of polarization-maintaining fiber (PMF), with the polarization directions aligned with the fast and slow axes of the PMF. A photonic microwave bandpass filter with two or four taps is obtained

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations57
Published2007
Admission routes1
Has abstractyes

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