În afara temei aiqbench
Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.
Quotient Geometry and Persistence-Stable Metrics for Swarm Configurations
arXiv:2603.18041v2 Announce Type: replace Abstract: Can temporal information recover geometry lost by a persistence diagram? For $n\ge3$ points on the unit sphere evolving under known homogeneous complete consensus, we prove generic local recovery modulo rotations and permutations from two ordinary zero-dimensional Vietoris--Rips persistence snapshots. The structural result applies to every labeled tree: its edge inner products and their first temporal derivatives have differential rank $2n-3$, exactly the dimension of the regular formation quotient. An explicit pole--equator witness proves this simultaneously for all tree types after taking a finite intersection of open dense sets. Although one snapshot has generic local fibers of dimension $n-2$, two sufficiently close snapshots are injective on a common neighborhood. The optimal inverse Lipschitz constant grows as $\Theta(1/|h|)$ when the sampling interval tends to zero. A verified left inverse, interval derivative bounds, and explicit persistence-matching margins certify neighborhoods and time intervals at rational reference formations. The results are local and model-specific; reflection ambiguity and centered rank obstructions remain.
Abstract:Can temporal information recover geometry lost by a persistence diagram? For $n\ge3$ points on the unit sphere evolving under known homogeneous complete consensus, we prove generic local recovery modulo rotations and permutations from two ordinary zero-dimensional Vietoris--Rips persistence snapshots. The structural result applies to every labeled tree: its edge inner products and their first temporal derivatives have differential rank $2n-3$, exactly the dimension of the regular formation quotient. An explicit pole--equator witness proves this simultaneously for all tree types after taking a finite intersection of open dense sets. Although one snapshot has generic local fibers of dimension $n-2$, two sufficiently close snapshots are injective on a common neighborhood. The optimal inverse Lipschitz constant grows as $\Theta(1/|h|)$ when the sampling interval tends to zero. A verified left inverse, interval derivative bounds, and explicit persistence-matching margins certify neighborhoods and time intervals at rational reference formations. The results are local and model-specific; reflection ambiguity and centered rank obstructions remain.
Machine Learning (cs.LG); Social and Information Networks (cs.SI); Systems and Control (eess.SY); Algebraic Topology (math.AT)
arXiv:2603.18041 [cs.LG]
(or arXiv:2603.18041v2 [cs.LG] for this version)
https://doi.org/10.48550/arXiv.2603.18041 Focus to learn more arXiv-issued DOI via DataCite
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