Bibliographic record
Abstract
We study the controllability of the control system describing the rolling motion, without slipping nor spinning, of two n-dimensional Riemannian manifolds, one against the other.This model is closely related to the concepts of development and holonomy of the manifolds, and it generalizes to the case of affine manifolds.The main contributions are those given in four articles attached to the the thesis.First of them "Rolling manifolds and Controllability: the 3D case"deal with the case where the two manifolds are 3-dimensional. We give the listof all the possible cases for which the system is not controllable.In the second paper "Rolling manifolds on space forms"one of the manifolds is assumed to have constant curvature.We can then reduce the study of controllability to the study of the holonomy groupof a certain vector bundle connection and we show, for example, thatif the manifold with the constant curvature is an n-sphere and ifthis holonomy group does not act transitively,then the other manifold is in fact isometric to the sphere.The third paper "A Characterization of Isometries between Riemannian Manifolds by using Development along Geodesic Triangles"describes, by using the rolling motion (or development) along the loops,an alternative version of the Cartan-Ambrose-Hicks Theorem,which characterizes, among others, the Riemannian isometries.More precisely, we prove that if one starts from a certain initial orientation,and if one only rolls along loops based at the initial point (associated to this orientation),then the two manifolds are isometric if (and only if) the pathstraced by the rolling motion on the other manifolds, are all loops.Finally, the fourth paper "Rolling Manifolds without Spinning"studies the rolling motion, and its controllability, when slipping is allowed.We characterize the structure of all the possible orbits in terms of the holonomy groupsof the manifolds in question. It is also shown that there does not exist anyprincipal bundle structure such that the related distribution becomes a principal distribution,a fact that is to be compared especially to the results of the second article.Furthermore, in the third chapter of the thesis, we construct carefully the rolling modelin the more general framework of affine manifolds, as well as that of Riemannian manifolds,of possibly different dimensions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".