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Record W2087143639 · doi:10.1364/oe.15.003531

Symmetry constraints and the existence of Bloch mode vortices in linear photonic crystals

2007· article· en· W2087143639 on OpenAlexafffund
Jeffrey F. Wheeldon, Trevor J. Hall, Henry Schriemer

Bibliographic record

VenueOptics Express · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsUniversity of Ottawa
FundersOntario Centres of Excellence
KeywordsPhysicsVortexRotational symmetryGlobal symmetrySymmetry (geometry)Symmetry groupQuantum mechanicsGravitational singularityClassical mechanicsSymmetry breakingGeometrySpontaneous symmetry breakingMathematicsMechanics

Abstract

fetched live from OpenAlex

Modal phase singularities are identified in linear photonic crystals and the vortex state is explored in detail. Using group theory and phasor geometry, in the vanishing contrast limit, the modal symmetry requirements for the existence of phase singularities are determined. The vortex states are the partner functions of the symmetry groups, and hence one has a qualitative map of these modes in reciprocal space. We find that modes of even rotational symmetry are unable to form vortex states, while modes of odd rotational symmetry may form vortex states. The latter can be further classified into symmetry and accidental vortices. The insights gained using the vanishing contrast approximation are augmented by numerically solving the Maxwell's equations for the high dielectric lattice forms using the Finite Element method; the general symmetry constraints are confirmed. In addition, symmetry vortices are found to demonstrate form and locational stability over large changes in dielectric contrast, whereas this is not so for the accidental vortices, which are more sensitive to such changes.

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)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.282
Teacher spread0.270 · 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
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

Citations6
Published2007
Admission routes2
Has abstractyes

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