A geometric application of Lagrange multipliers: extremal compatible linear connections
Csaba Vincze, M\'ark Ol\'ah

TL;DR
This paper extends the concept of extremal Levi-Civita connections to more general geometric spaces by using Lagrange multipliers to characterize compatible linear connections and their torsion tensors.
Contribution
It introduces a method to determine extremal compatible linear connections in generalized Finsler spaces using Lagrange multipliers and intrinsic geometric quantities.
Findings
Established Riemann metrizability of compatible connections.
Derived necessary and sufficient conditions for the existence of extremal connections.
Provided explicit solutions in terms of intrinsic geometric quantities.
Abstract
The L\'evi-Civita connection of a Riemannian manifold is a metric (compatible) linear connection, uniquely determined by its vanishing torsion. It is extremal in the sense that it has minimal torsion at each point. We can extend this idea to more general spaces with more general (not necessarily quadratic) indicatrix hypersurfaces in the tangent spaces. Here, the existence of compatible linear connections on the base manifold is not guaranteed anymore, which needs to be addressed along with the intrinsic characterization of the extremal one. The first step is to provide the Riemann metrizability of the compatible linear connections. This Riemannian environment establishes a one-to-one correspondence between linear connections and their torsion tensors, also giving a way of measuring the length of the latter. The second step is to solve a hybrid conditional extremum problem at each point…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Differential Equations and Dynamical Systems · Optimization and Variational Analysis · Advanced Optimization Algorithms Research
