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Record W4389370874 · doi:10.1109/tap.2023.3337946

Analytical Expressions for Spherical Wire Antenna Quality Factor Demonstrating Exact Agreement Between Circuit-Based and Field Integration Techniques

2023· article· en· W4389370874 on OpenAlexaff
A. Murray, Ashwin K. Iyer

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2023
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMultipole expansionAntenna (radio)PhysicsEquivalent circuitQuality (philosophy)Shape factorQ factorElectromagnetic fieldField (mathematics)Topology (electrical circuits)Mathematical analysisGeometryOpticsComputer scienceMathematicsVoltageElectrical engineeringTelecommunicationsQuantum mechanicsEngineering

Abstract

fetched live from OpenAlex

Properties of spherical wire antennas are revisited using a circuit analysis approach. This methodology yields the exact quality factor and axial ratio of coupled-mode spherical radiators as analytical expressions. The new circuit-based equations are compared to field integration predictions for quality factor, and both are found to agree for a general multipole expansion of the electromagnetic fields. These two predictions of stored energy inside a spherical wire antenna are shown to be equivalent via direct analysis, while predictions of stored energy outside the spherical wire antenna are compared by way of mathematical induction. Additionally, the circuit analysis reveals general relations between supplied current and radiated power of spherical wire antennas, resonance conditions of coupled-mode systems, and analytical quantification of the trade-off between the quality factor and axial ratio for TM1m–TE1mradiators. New and simple expressions for the minimum quality factor of circular, near-circular, linear, and general elliptical polarizations are provided.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.053
GPT teacher head0.299
Teacher spread0.246 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations5
Published2023
Admission routes1
Has abstractyes

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