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Record W1508377086

Plane electromagnetic waves in layered periodic dielectric structures.

2001· article· en· W1508377086 on OpenAlexaffabout
G. V. Morozov

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2001
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsElectromagnetic radiationDielectricPhysicsPlane (geometry)AcousticsMathematical analysisGeologyGeometryOpticsMathematics
DOInot available

Abstract

fetched live from OpenAlex

Several analytic methods are used to derive and discuss analytic expressions for electromagnetic wave fields in finite one-dimensional layered structures. A new modification is obtained for the so-called multiple reflection method. Special attention is given to layered periodic dielectric structures. The systematic dependence of the reflection coefficient on the parameters characterizing this type of structure is studied in detail, using the two-layered periodic dielectric structure as a typical example. A general method for the construction of the Green's function for finite one-dimensional layered structures is developed. The sum of the total Neumann (Born) series is calculated for sufficiently simple cases of perturbations in the profile of the refractive index. Using the Green's function, the influence of fluctuations of the width of the basic layers on the reflection and transmission of electromagnetic waves propagating through the two-layered periodic dielectric structure is investigated. The results are applied to the design of optical switching systems with periodic dielectric structures as the operating medium.Dept. of Physics. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .M67. Source: Dissertation Abstracts International, Volume: 62-10, Section: B, page: 4599. Advisers: G. Drake; R. Maev. Thesis (Ph.D.)--University of Windsor (Canada), 2001.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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 designObservational
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
Published2001
Admission routes2
Has abstractyes

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