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Record W2525504558 · doi:10.3934/dcdsb.2016.21.959

Oscillations of many interfaces in the near-shadow regime of two-component reaction-diffusion systems

2015· article· en· W2525504558 on OpenAlexaff
Shuangquan Xie, Théodore Kolokolnikov

Bibliographic record

VenueDiscrete and Continuous Dynamical Systems - B · 2015
Typearticle
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComponent (thermodynamics)DiffusionDomain (mathematical analysis)Dimension (graph theory)Reaction–diffusion systemInterface (matter)Phase (matter)Motion (physics)Limit (mathematics)Class (philosophy)PhysicsStatistical physicsComputer scienceMathematical analysisClassical mechanicsThermodynamicsMathematicsPure mathematicsSurface tensionQuantum mechanics

Abstract

fetched live from OpenAlex

We consider the general class of two-component reaction-diffusion systems on afinite domain that admit interface solutions in one of the components, and westudy the dynamics of $n$ interfaces in one dimension. In the limit where thesecond component has large diffusion, we fully characterize the possiblebehaviour of $n$ interfaces. We show that after the transients die out, themotion of $n$ interfaces is described by the motion of a singleinterface on the domain that is $1/n$ the size of the original domain.Depending on parameter regime and initial conditions, one of the followingthree outcomes results: (1) some interfaces collide; (2) all $n$ interfacesreach a symmetric steady state; (3) all $n$ interfaces oscillateindefinitely. In the latter case, the oscillations are described by a simpleharmonic motion with even-numbered interfaces oscillating in phase whileodd-numbered interfaces are oscillating in anti-phase. This extends a recentwork by [McKay, Kolokolnikov, Muir, DCDS B(17), 2012] from two to any numberof interfaces.

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)0.000
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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Same venueDiscrete and Continuous Dynamical Systems - BSame topicNonlinear Dynamics and Pattern FormationFrench-language works237,207