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Remarks on global a priori estimates for the nonlinear Schrödinger equation

2010· article· en· W2059183346 on OpenAlexaff
J. Colliander, Manoussos G. Grillakis, Nikolaos Tzirakis

Bibliographic record

VenueProceedings of the American Mathematical Society · 2010
Typearticle
Languageen
FieldMathematics
TopicAdvanced Mathematical Physics Problems
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsA priori and a posterioriNonlinear Schrödinger equationNonlinear systemApplied mathematicsMathematicsSchrödinger equationMathematical analysisPhysicsPhilosophyEpistemologyQuantum mechanics

Abstract

fetched live from OpenAlex

We present a unified approach for obtaining global a priori estimates for solutions of nonlinear defocusing Schrödinger equations with defocusing nonlinearities. The estimates are produced by contracting the local momentum conservation law with appropriate vector fields. The corresponding law is written for defocusing equations of tensored solutions. In particular, we obtain a new estimate in two dimensions. We bound the restricted L t 4 L γ 4 L_t^4L_{\gamma }^4 Strichartz norm of the solution on any curve γ \gamma in R 2 \mathbb R^2 . For the specific case of a straight line we upgrade this estimate to a weighted Strichartz estimate valid in the full plane.

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)0.010
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.013
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.016
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0030.001
Science and technology studies0.0020.003
Scholarly communication0.0020.010
Open science0.0030.006
Research integrity0.0020.008
Insufficient payload (model declined to judge)0.0130.003

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 head0.029
GPT teacher head0.332
Teacher spread0.302 · 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 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
Published2010
Admission routes1
Has abstractyes

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