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Record W4293868555 · doi:10.1109/ims37962.2022.9865430

Cryogenic Wideband Quadrature Hybrid Couplers Implemented in a Low Temperature Superconductor Multilayer Process

2022· article· en· W4293868555 on OpenAlexaff
Navjot K. Khaira, Tejinder Singh, Raafat R. Mansour

Bibliographic record

Venue2022 IEEE/MTT-S International Microwave Symposium - IMS 2022 · 2022
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsReturn lossMiniaturizationWidebandInsertion lossHybrid couplerKu bandMaterials scienceFabricationPower dividers and directional couplersOptoelectronicsCoupling (piping)Electronic circuitElectrical engineeringElectronic engineeringEngineeringNanotechnology

Abstract

fetched live from OpenAlex

This paper presents the design, fabrication and testing of two cryogenic 90° hybrid couplers operating at Ka and Ku bands. The hybrid couplers use a CPW based tandem coupled line architecture and are fabricated using a MIT Lincoln Lab multilayer process for superconducting circuits. The first quadrature hybrid demonstrates a wideband coupling performance from 26 GHz to 44 GHz, with measured return loss and isolation better than 24 dB, and insertion loss less than 0.5 dB. The second tandem coupler offers an excellent coupling performance from 8 GHz to 18 GHz. The on-chip device dimensions for the two hybrid couplers are 0.92 mm × 0.16mm and 2.43 mm × 0.16mm, respectively. For further miniaturization, an alternative compact hybrid coupler design for operation at Ku band is proposed having a footprint of only 0.41 mm × 0.35mm, a 64% reduction in device area when compared to the first Ku band design.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.046
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

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