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Record W1974123120 · doi:10.1002/mop.25975

A Ka‐band quasi‐optical power‐divider basing on Talbot Effect of phase grating

2011· article· en· W1974123120 on OpenAlexfundno aff
Guang Li, Jian Huang, Naichang Pei

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPower dividers and directional couplersMicrowaveOpticsGratingDiffractionMillimeterDiffraction efficiencyPhysicsEngineeringElectrical engineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract A new design of quasi‐optical (QO) power divider at millimeter wave band is presented in this article. The Talbot Effect of periodical phase grating is applied to realize power dividing with high efficiency. A novel periodic phase profile was adopted to make a linear region of zero diffraction filed. Then a closed metallic cavity can be used to screen the power divider with the wall placed in this region without disturbance to field distribution and efficiency degrading, which improves electromagnetic compatibility of QO power combining system greatly. The Scalar Diffraction theory is applied to analyze the “Talbot Pattern” and then generic algorithm is used to optimize the phase profile. A 1 × 18 divider was designed and tested at 37.5GHz. The efficiency is tested to be 80.8%, which is well agreed with the simulated value of 88.7%. Since efficiency of QO power divider/combiner is essentially independent of the number of combining elements and the inter‐element spacing, this technology can be extended to power dividing or combining of large number of ways up to THz band. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:1331–1336, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25975

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 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 score0.028
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
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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