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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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4589134178 · Jun 202019922001200920172026
48 results for Riemannian distances

In infinite dimensional Heisenberg group, degenerate distances linked to unbounded curvature.

problem Degenerate distances and unbounded curvature in infinite dimensional Heisenberg group.
method Construct left invariant weak Riemannian and sub-Riemannian metrics, adapt sectional curvature definition.
result Degenerate distances coincide with unbounded sectional curvature.

Maps on Sasakian manifolds limit to sub-Riemannian distance bounds.

problem Understanding sub-Riemannian distances on Sasakian manifolds.
method Parallel and mirror maps along geodesics of a taming Riemannian metric.
result Limits of transport maps outside sub-Riemannian cut-locus provide bounds on sub-Riemannian distance.

Laplacian of distance function shows negative infinity at cut locus points.

problem Understanding the Laplacian of distance functions on Riemannian manifolds.
method Analyzing the Laplacian of the distance function to a point on a smooth Riemannian manifold.
result The Laplacian of the distance function is -\infty at points of the cut locus.

The paper establishes Sobolev inequalities between Riemannian metrics and their distance functions.

problem Establishing a theory of Sobolev inequalities for Riemannian metrics and distance functions.
method Analyzing the sub-critical case $p < rac{m}{2}$, proving a Sobolev inequality linking $L^{ rac{p}{2}}$ bounds on metrics to LqL^q bounds on distance functions.
result A Sobolev inequality exists between Riemannian metrics and their distance functions, leading to a convergence theorem.

Study proves finiteness for distance functions on curved surfaces with controlled curvature.

problem Understanding distance functions on curved surfaces with Hölder continuous curvature.
method Proves a finiteness principle using Whitney extension theory for geodesics and points on Riemannian surfaces with Hölder continuous curvature.
result Establishes a finiteness principle for isometric embedding of metric spaces into Riemannian surfaces with controlled curvature.

Study on estimating distances between covariance operators and Gaussian processes.

problem Estimating distances between covariance operators and Gaussian processes.
method Riemannian distances, concentration results for Hilbert space-valued random variables, RKHS covariance and cross-covariance operators.
result Both distances converge in the Hilbert-Schmidt norm and can be consistently and efficiently estimated.

Study on surfaces of genus g≥1 in 3D contact sub-Riemannian manifolds, proving finiteness or infiniteness of induced distance.

problem Determining the finiteness of the induced distance on surfaces of genus g≥1 in 3D contact sub-Riemannian manifolds.
method Analyzing the structural stability of the finiteness/not-finiteness of the induced distance on closed surfaces of genus g≥1.
result Closed surfaces of genus g≥1 can be embedded in such a way that the induced distance is either always finite or always infinite.

Inequalities linking entropy, Fisher info, Stein discrepancy, and Wasserstein distance on Riemannian manifolds.

problem Linking entropy, Fisher info, Stein discrepancy, and Wasserstein distance on Riemannian manifolds.
method Deriving inequalities linking these measures on Riemannian manifolds.
result Strengthening and extending existing inequalities to Riemannian manifolds.

Study validates Michor-Mumford conjecture in infinite dimensional Hilbertian H-type groups.

problem Validation of Michor-Mumford conjecture in infinite dimensional Hilbertian H-type groups.
method Introduced infinite dimensional Hilbertian H-type groups with weak, graded, left invariant Riemannian metrics and proved the vanishing of geodesic distance and local unboundedness of sectional curvature.
result Validation of Michor-Mumford conjecture linking geodesic distance vanishing to local unboundedness of sectional curvature.

The paper converts metric bounds to distance function Hölder bounds and proves compactness theorems.

problem Proving geometric stability results with scalar curvature bounds.
method Transforming LpL^p bounds to Hölder bounds for distance functions.
result Compactness theorems and convergence guarantees for Riemannian manifolds.

The paper describes distances on Sol-type groups using novel geometric techniques.

problem Understanding distances on Sol-type groups.
method New technique of Euclidean curve surgery to describe uniformly roughly geodesic paths.
result The rough isometry type of distances on Sol-type groups is determined by a specific metric restriction.

Study on volume of tubes and concentration in Riemannian geometry.

problem Understanding concentration loci in Riemannian manifolds and their relation to tube volumes.
method Provided a general formula for tube volumes, specialized to totally geodesic submanifolds, and investigated concentration loci.
result Explicitly proved concentration for codimension one cases and explored characterizations in Wasserstein and Box distances.

Bounds on geodesic distances on Stiefel manifold derived from new metrics.

problem Improving geodesic computation algorithms and understanding Stiefel manifold.
method New geometric insights and Lipschitz constants for geodesic distances.
result Explicit bounds on geodesic distances and conditions for attaining bounds.

New method calculates Ricci curvature from distances between weighted volumes.

problem Calculating Ricci curvature for weighted Riemannian manifolds.
method Asymptotic retrieval of generalized Ricci tensor from scaled metric derivatives of Wasserstein 1-distances.
result Limiting coarse curvature of random graphs converges to generalized Ricci tensor.

The Heston model is a popular stock price model with stochastic volatility that has found numerous applications in practice. In the present paper, we study the Riemannian distance function associated with the Heston model and obtain explicit formulas for this function using geometrical and analytical methods. Geometric…

2013-02-10abs ↗pdf ↗

Rigidity theorem for discrete metric spaces embedded in Riemannian surfaces.

problem Understanding the rigidity of discrete metric spaces embedded in Riemannian surfaces.
method Proving that certain discrete metric spaces are rigidly embedded in the Euclidean plane or other Riemannian surfaces.
result Riemannian embeddings of certain discrete metric spaces are rigid, meaning they cannot be deformed without changing distances.

We consider reconstruction of a manifold, or, invariant manifold learning, where a smooth Riemannian manifold MM is determined from intrinsic distances (that is, geodesic distances) of points in a discrete subset of MM. In the studied problem the Riemannian manifold (M,g)(M,g) is considered as an abstract metric space w…

2019-05-17abs ↗pdf ↗

The aim of this paper is the study of the geodesic distance in operator groups with several Riemannian metrics. More precisely we study the geodesic distance in self-adjoint operator groups with the left invariant Riemannian metric induced by the infinite trace and extend known results about the completeness of some cl…

2015-09-04abs ↗pdf ↗

Paper presents efficient computation of robust Wasserstein distance using Riemannian optimization.

problem Intractability of optimizing Projection Robust Wasserstein (PRW) distance due to non-convexity and non-smoothness.
method Riemannian optimization to efficiently compute PRW/Wasserstein Projection Pursuit (WPP) distance.
result The original formulation of PRW/WPP can be efficiently computed in practice, providing better behavior than its convex relaxation.

We introduce a notion of geodesic curvature kζk_ζ for a smooth horizontal curve ζζ in a three-dimensional contact sub-Riemannian manifold, measuring how much a horizontal curve is far from being a geodesic. We show that the geodesic curvature appears as the first corrective term in the Taylor expansion of the sub-Riem…

2019-10-29abs ↗pdf ↗

Length metrics can be closely approximated by conformally flat metrics.

problem Approximating length metrics with conformally flat metrics.
method Uniform approximation of length metrics by conformally flat Riemannian metrics.
result Any length metric on \(\mathbb{R}^d\) can be uniformly approximated by conformally flat Riemannian metrics.

Paper reconstructs compact Riemannian manifolds from travel time data.

problem Reconstructing compact Riemannian manifolds from partial travel time data.
method Embedding in function space, studying distance function regularity.
result Reconstruction of compact Riemannian manifolds from travel time data.

A new model encodes distances and topology in latent variables.

problem Modeling dissimilarity data with latent variables and invariances.
method Isometric Gaussian Process Latent Variable Model using Riemannian geometry and variational inference.
result The model can encode invariances in learned manifolds.

Research shows that certain metric spaces cannot contain rigid structures and provides evidence for loose embeddings into Euclidean spaces.

problem The inability of certain metric spaces to contain rigid structures like regular simplices or equidistant sequences.
method Proof of non-embeddability of certain metric spaces into finite-dimensional Euclidean spaces and a local-to-global principle for loose embeddability.
result Compact Riemannian manifolds cannot contain arbitrarily large regular simplices or long equidistant sequences, suggesting loose embeddings into Euclidean spaces.

We introduce Gaussian-type measures on the manifold of all metrics with a fixed volume form on a compact Riemannian manifold of dimension 3\geq 3. For this random model we compute the characteristic function for the L2L^2 (Ebin) distance to the reference metric. In the Appendix, we study Lipschitz-type distance betwee…

2013-09-05abs ↗pdf ↗

Proposes ridge regression on Riemannian manifolds for time-series prediction.

problem Time-series prediction on Riemannian manifolds.
method Combines Riemannian least-squares fitting via Bézier curves, empirical covariance on manifolds, and Mahalanobis distance regularization.
result Significant error reduction in synthetic spherical experiments and hurricane forecasting.