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Record W2062150926 · doi:10.1109/mwsym.2014.6848408

Overcoming the FDTD stability limit via model order reduction and eigenvalue perturbation

2014· article· en· W2062150926 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFinite-difference time-domain methodLimit (mathematics)Eigenvalues and eigenvectorsPerturbation (astronomy)Applied mathematicsMathematicsModel order reductionStability (learning theory)Reduction (mathematics)Mathematical analysisComputer sciencePhysicsAlgorithmGeometryQuantum mechanics

Abstract

fetched live from OpenAlex

In the Finite Difference Time Domain (FDTD) method, the time-step is constrained by the Courant-Friedrichs-Lewy (CFL) limit. The CFL limit is particularly restrictive in the presence of fine geometrical details, since it imposes a very small time-step. We propose an efficient method for overcoming this constraint via model order reduction, coupled with an eigenvalue perturbation method that ensures stability even for time-steps beyond the CFL limit. Two numerical examples demonstrate that the proposed method is faster than FDTD as well as existing alternative techniques for overcoming the CFL barrier.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.211

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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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