MétaCan
Menu
Back to cohort
Record W4214538315 · doi:10.1002/cpa.22043

Local Minimizers with Unbounded Vorticity for the 2D <scp>Ginzburg‐Landau</scp> Functional

2022· article· en· W4214538315 on OpenAlexaff
Andrés Contreras, Robert L. Jerrard

Bibliographic record

VenueCommunications on Pure and Applied Mathematics · 2022
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsVortexVorticityMathematicsBounded functionEnergy functionalDomain (mathematical analysis)Ginzburg–Landau theoryVector fieldMathematical analysisLimit (mathematics)Mathematical physicsMagnetic fieldPhysicsGeometryQuantum mechanicsMechanics

Abstract

fetched live from OpenAlex

Abstract A central focus of Ginzburg‐Landau theory is the understanding and characterization of vortex configurations. On a bounded domain global minimizers, and critical states in general, of the corresponding energy functional have been studied thoroughly in the limit where is the inverse of the Ginzburg‐Landau parameter. A notable open problem is whether there are solutions of the Ginzburg‐Landau equation for any number of vortices below for external fields of up to superheating field strength. In this paper, we prove that there are constants such that given natural numbers satisfying local minimizers of the Ginzburg‐Landau functional with this many vortices exist, for fields such that Our strategy consists of combining: the minimization over a subset of configurations for which we can obtain a very precise localization of vortices; expansion of the energy in terms of a modified vortex interaction energy that allows for a reduction to a potential theory problem; and a quantitative vortex separation result for admissible configurations. Our results provide detailed information about the vorticity and refined asymptotics of the local minimizers that we construct. © 2021 Wiley Periodicals LLC.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.834
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.044
GPT teacher head0.269
Teacher spread0.226 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCommunications on Pure and Applied MathematicsSame topicGas Dynamics and Kinetic TheoryFrench-language works237,207