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Record W4388267179 · doi:10.21203/rs.3.rs-3482659/v1

Total collision in a four-body problem with Jacobi potential

2023· preprint· en· W4388267179 on OpenAlexafffund
Lennard F. Bakker, Manuele Santoprete, Cristina Stoica

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAngular momentumCollisionManifold (fluid mechanics)RhombusPhysicsConfiguration spacePotential energyClassical mechanicsFlow (mathematics)Space (punctuation)Plane (geometry)Function (biology)GeometryMathematical analysisMathematicsQuantum mechanicsComputer science

Abstract

fetched live from OpenAlex

Abstract We study the dynamics of a spatial four-body problem where the bodies maintain a rhombus-shape configuration at all times: two of the bodies of equal mass move in the horizontal plane symmetrically with respect to the origin while another pair of bodies of equal mass move symmetrically opposed along the vertical axis. The bodies interact via the Jacobi potential, an attractive binary potential of the form $-1/x^2$, where $x$ is the distance between the particles. We use appropriate transformations to blow up total collision into a manifold pasted onto the phase space for all levels of energy. We find that the topology of the total collision manifold changes as the angular momentum varies, and also that the dynamics on the collision manifold changes as a function of angular momentum and the mass ratio. We also give a qualitative description of the global flow of the problem for negative energy. This description utilizes knowledge concerning the flow on and near the collision manifold, the presence of an additional integral of motion, and takes advantage of the time-reversing symmetry inherent in the system of equations.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.004
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.042
GPT teacher head0.335
Teacher spread0.293 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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