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Record W1576790267

Efficient calculations of dispersive properties of photonic crystals using the transmission line matrix method

2005· article· en· W1576790267 on OpenAlexaff
G. Romo, T. Smy

Bibliographic record

VenueOptica Applicata · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhotonic Crystals and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsMultigrid methodComputer sciencePhotonic crystalMatrix (chemical analysis)AlgorithmLine (geometry)Computational scienceMathematical optimizationOpticsMathematicsMaterials sciencePhysicsPartial differential equationGeometry
DOInot available

Abstract

fetched live from OpenAlex

In this paper, we present an analysis of the accuracy and efficiency of different approaches for the simulation of photonic crystals using the transmission line matrix method. The approaches that we present can be divided into two categories: complex- and real-valued algorithms using a uniform mesh, and complex- and real-valued algorithms using a multigrid mesh. The advantages and disadvantages of each approach are discussed and a brief comparison between these methods is made from the points of view of computational expense and accuracy. It is found that a combination of a real-valued method in a multigrid mesh results in the most efficient algorithm. However, while the complex-valued formulation is valid for the analysis of any photonic crystal, the applicability of the real-valued formulation is limited by structural constraints requiring cell symmetries. It is also found that a multigrid approach can considerably reduce the computational cost required for simulating photonic crystals and our results indicate that a good compromise between accuracy and computational cost can be found. Various photonic crystals are simulated by applying these approaches, and the results are validated using alternative methods.

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 categoriesnone
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 score0.377
Threshold uncertainty score0.346

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 integrity0.0000.000
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 head0.024
GPT teacher head0.314
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2005
Admission routes1
Has abstractyes

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