MétaCan
Menu
Back to cohort
Record W1965638376 · doi:10.1017/s0956792501004442

Asymmetric spike patterns for the one-dimensional Gierer–Meinhardt model: equilibria and stability

2002· article· en· W1965638376 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEuropean Journal of Applied Mathematics · 2002
Typearticle
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEigenvalues and eigenvectorsPhysicsThermal diffusivitySpike (software development)AmplitudeDomain (mathematical analysis)Mathematical analysisStatistical physicsMathematical physicsMathematicsThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

Equilibrium solutions to the one-dimensional Gierer–Meinhardt model in the form of sequences of spikes of different heights are constructed asymptotically in the limit of small activator diffusivity ε. For a pattern with k spikes, the construction yields k 1 spikes that have a common small amplitude and k 2 = k − k 1 spikes that have a common large amplitude. A k - spike asymmetric equilibrium solution is obtained from an arbitrary ordering of the small and large spikes on the domain. It is shown that such solutions exist when the inhibitor diffusivity D is less than some critical value D m that depends upon k 1 , on k 2 , and on other parameters associated with the Gierer–Meinhardt model. It is also shown that these asymmetric k -spike solutions bifurcate from the symmetric solution branch s k , for which k spikes have equal height. These asymmetric solutions provide connections between the branch s k and the other symmetric branches s j , for j = 1,…, k − 1. The stability of the asymmetric k -spike patterns with respect to the large O (1) eigenvalues and the small O (ε 2 ) eigenvalues is also analyzed. It is found that the asymmetric patterns are stable with respect to the large O (1) eigenvalues when D > D e , where D e depends on k 1 and k 2 , on certain parameters in the model, and on the specific ordering of the small and large spikes within a given k -spike sequence. Numerical values for D e are obtained from numerical solutions of a matrix eigenvalue problem. Another matrix eigenvalue problem that determines the small eigenvalues is derived. For the examples considered, it is shown that the bifurcating asymmetric branches are all unstable with respect to these small eigenvalues.

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)0.002
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.050
GPT teacher head0.230
Teacher spread0.181 · 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