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Record W3206780838 · doi:10.2140/memocs.2021.9.423

Mean-field limit for particle systems with topological interactions

2021· article· en· W3206780838 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMathematics and Mechanics of Complex Systems · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsnot available
FundersOtto von Guericke University MagdeburgCollege of Engineering, Michigan State UniversityUniversité de LyonFreie Universität BerlinCentre National de la Recherche ScientifiqueUniversität zu KölnUniversità degli Studi di PaviaIndian National Science AcademyUniversità Politecnica delle MarcheMcGill UniversityKing Abdullah University of Science and TechnologyYork UniversityPolitecnico di TorinoMichigan State UniversityGran Sasso Science InstituteInstitut National des Sciences Appliquées de LyonUniversidad Rey Juan CarlosLouisiana State UniversityWayne State University
KeywordsLimit (mathematics)Particle systemDimension (graph theory)Mean field theoryStatistical physicsField (mathematics)Poisson distributionTopology (electrical circuits)MathematicsPhysicsMathematical analysisComputer sciencePure mathematicsQuantum mechanicsStatisticsCombinatorics

Abstract

fetched live from OpenAlex

The mean-field limit for systems of self-propelled agents with "topological interaction" cannot be obtained by means of the usual Dobrushin approach. We get results by adapting to the multidimensional case the techniques developed by Trocheris in 1986 to treat the Vlasov-Poisson equation in one dimension.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.940
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.049
GPT teacher head0.276
Teacher spread0.228 · 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