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Record W2765749019 · doi:10.1073/pnas.1719346115

Geometric hydrodynamics via Madelung transform

2018· article· en· W2765749019 on OpenAlexafffund
Boris Khesin, Gerard Misiołek, Klas Modin

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldMathematics
TopicGeometric Analysis and Curvature Flows
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Colorado BoulderWeizmann Institute of ScienceStiftelsen för Strategisk Forskning
KeywordsMetric (unit)Partial differential equationSymplectomorphismPhase spaceSpace (punctuation)Mathematical analysisDifferential geometryMathematicsPhysicsClassical mechanicsSymplectic geometryComputer scienceQuantum mechanics

Abstract

fetched live from OpenAlex

Significance Geometry has always played a fundamental role in theoretical physics via symmetries and conservation laws. We present a geometric framework revealing a closer link between hydrodynamics and quantum mechanics than previously recognized. Newton’s equations, generalized to infinite-dimensional spaces of fluid flow maps (diffeomorphisms), are used to develop a unified setting and uncover new connections between many equations of mathematical physics. These include equations of compressible fluids, motion of particles on spheres in quadratic potentials, and the Klein–Gordon and nonlinear Schrödinger equations, as well as their relation to information geometry and optimal mass transport. This work contributes toward a better understanding of geometric structures arising in hydrodynamics and quantum mechanics.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.047
GPT teacher head0.321
Teacher spread0.274 · 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

Citations31
Published2018
Admission routes2
Has abstractyes

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