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Record W3150334259 · doi:10.48550/arxiv.1902.00384

Spontaneous periodic orbits in the Navier-Stokes flow

2019· article· en· W3150334259 on OpenAlexafffund
Jan Bouwe van den Berg, Maxime Breden, J. LESSARD, Lennaert van Veen

Bibliographic record

VenuearXiv (Cornell University) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicQuantum chaos and dynamical systems
Canadian institutionsOntario Tech UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk OnderzoekVolkswagen Foundation
KeywordsMathematical proofMathematicsForcing (mathematics)Homogeneous spaceBanach spaceConstructiveNavier–Stokes equationsTorusMathematical analysisGeometryPhysicsComputer science

Abstract

fetched live from OpenAlex

In this paper, a general method to obtain constructive proofs of existence of\nperiodic orbits in the forced autonomous Navier-Stokes equations on the\nthree-torus is proposed. After introducing a zero finding problem posed on a\nBanach space of geometrically decaying Fourier coefficients, a\nNewton-Kantorovich theorem is applied to obtain the (computer-assisted) proofs\nof existence. The required analytic estimates to verify the contractibility of\nthe operator are presented in full generality and symmetries from the model are\nused to reduce the size of the problem to be solved. As applications, we\npresent proofs of existence of spontaneous periodic orbits in the Navier-Stokes\nequations with Taylor-Green forcing.\n

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)0.002
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.158
Teacher spread0.139 · 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

Citations24
Published2019
Admission routes2
Has abstractyes

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