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Record W3208796404 · doi:10.1016/j.jfa.2021.109288

Sign-changing blow-up for the Moser–Trudinger equation

2022· article· en· W3208796404 on OpenAlex
Luca Martinazzi, Pierre-Damien Thizy, Jérôme Vétois

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

VenuePadua Research Archive (University of Padova) · 2022
Typearticle
Languageen
FieldMathematics
TopicNonlinear Partial Differential Equations
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAgence Nationale de la Recherche
KeywordsSign (mathematics)MathematicsQuantization (signal processing)Domain (mathematical analysis)BubbleZero (linguistics)Limit (mathematics)Mathematical analysisCluster analysisMathematical physicsPhysicsStatisticsMechanics

Abstract

fetched live from OpenAlex

Given a sufficiently symmetric domain Ω⋐R2, for any k∈N∖{0} and β>4πk we construct blowing-up solutions (uε)⊂H01(Ω) to the Moser–Trudinger equation such that as ε↓0, we have ‖∇uε‖Ljavax.xml.bind.JAXBElement@57b4bd332→β, uε⇀u0 in H01 where u0 is a sign-changing solution of the Moser–Trudinger equation and uε develops k positive spherical bubbles, all concentrating at 0∈Ω. These 3 features (lack of quantization, non-zero weak limit and bubble clustering) stand in sharp contrast to the positive case (uε>0) studied by the second author and Druet [8].

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.244
GPT teacher head0.376
Teacher spread0.132 · 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