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Record W4290653020 · doi:10.1063/5.0088367

Quasi-homogeneous two-body problem

2022· article· en· W4290653020 on OpenAlexafffund
Yanxia Deng, Slim Ibrahim, Lingjun Qian

Bibliographic record

VenueJournal of Mathematical Physics · 2022
Typearticle
Languageen
FieldEngineering
TopicSpacecraft Dynamics and Control
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsHomogeneousSchwarzschild radiusSingularityPhysicsObservablen-body problemPhase spaceMathematicsMathematical analysisMathematical physicsClassical mechanicsQuantum mechanicsStatistical physicsSpacetime

Abstract

fetched live from OpenAlex

The quasi-homogeneous two-body problem aims at studying the interaction between two point particles under a prescribed potential in the form of W(r)=−Ara−Brb, where A, B > 0 are constants and r is the mutual distance between two particles. Important examples include the Manev potential (a = 1, b = 2) and the Schwarzschild potential (a = 1, b = 3). It is well known that power two serves as a threshold value for the homogeneous potential: One is able to observe significant differences regarding the solution dynamics as the power of the homogeneous potential exceeds two from below. This phenomenon remains observable for quasi-homogeneous potentials. In this paper, we shall provide a complete characterization of the whole phase space of the quasi-homogeneous two-body problem in terms of global existence and singularity for all the possible b > a > 0. In particular, one is able to generalize the result of the Manev and Schwarzschild two-body problem to all the quasi-homogeneous potentials. Two techniques are presented in this paper: One is the variational method based on the energy, and the other is a direct computation of collision time based on the integrability of two-body systems.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.006
GPT teacher head0.207
Teacher spread0.202 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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Same venueJournal of Mathematical PhysicsSame topicSpacecraft Dynamics and ControlFrench-language works237,207