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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.

168,695 papers · 148 categories

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2845698531,137 · Jun 202019922001200920172026
48 results for base manifolds

We study the (2+2)(2+2)-Einstein warped product manifolds, where the scalar curvature of the Base is a multiple of the warping function, and we called this condition (inside a warped product manifold) ff-curvature-Base (RfBR_{f_B}).The aim of this paper is to check if there are Base-manifolds with non-flat metrics that sa…

2019-05-04abs ↗pdf ↗

The paper studies Riemannian maps with Ricci soliton base manifolds.

problem Analyzing Riemannian maps with specific properties of base manifolds.
method Analyzing Riemannian curvature tensor, Ricci tensor, scalar curvature, and necessary conditions for Ricci soliton leaves.
result Necessary and sufficient conditions for harmonicity and biharmonicity of Riemannian maps.

An almost Clifford and an almost Cliffordian manifold is a GG--structure based on the definition of Clifford algebras. An almost Clifford manifold based on $\mathcal O:= \cc l (s,t)$ is given by a reduction of the structure group GL(km,R)GL(km, \mathbb R) to GL(m,O)GL(m, {\mathcal O}), where k=2s+tk=2^{s+t} and mNm \in \mathbb N. An…

2012-05-28abs ↗pdf ↗

RSGMs extend SGMs to Riemannian manifolds for better data modeling.

problem Current SGMs are limited to Euclidean spaces; RSGMs handle Riemannian manifolds.
method RSGMs use a noising stage with a diffusion process and a denoising model approximating the time-reversal of the diffusion on Riemannian manifolds.
result RSGMs improve generative modeling for data on Riemannian manifolds.

Develop intrinsic consensus-based optimization framework on Riemannian manifolds with bounded curvature.

problem Nonconvex optimization on manifolds
method Intrinsic consensus-based optimization on Riemannian manifolds with bounded curvature
result Global convergence of the mean-field equation toward a global minimizer of the objective function.

In this paper we give a method to construct Heegaard splittings of oriented graph manifolds with orientable bases. A graph manifold is a closed 33-manifold admitting only Seifert-fibered pieces in its Jaco-Shalen decomposition; for technical reasons, we restrict our attention to the fully oriented case, i.e. both the …

2018-02-20abs ↗pdf ↗

Isomorphic cosymplectomorphism groups imply diffeomorphic manifolds.

problem Determining when cosymplectic manifolds are diffeomorphic based on their cosymplectomorphism groups.
method Characterized Reeb flow, used to descend isomorphism to symplectic base manifolds, preserved monodromy class ensuring bundle equivalence.
result Isomorphic cosymplectomorphism groups imply diffeomorphic manifolds.

The paper studies maps between Riemannian and Kähler manifolds, focusing on Clairaut semi-invariant Riemannian maps.

problem Analyzing maps between Riemannian and Kähler manifolds, particularly Clairaut semi-invariant Riemannian maps.
method Recalled and defined Clairaut semi-invariant Riemannian maps, derived necessary and sufficient conditions for geodesic curves and maps, and explored foliations and product manifolds.
result Necessary and sufficient conditions for various properties of Clairaut semi-invariant Riemannian maps were derived.

We study the geometric properties of the base manifold for the unit tangent bundle satisfying the ηη-Einstein condition with the standard contact metric structure. One of the main theorems is that the unit tangent bundle of 4-dimensional Einstein manifold, equipped with the canonical contact metric structure, is ηη-E…

2007-08-10abs ↗pdf ↗

Study graph-based algorithms for multi-manifold clustering with sufficient conditions.

problem Clustering data from a union of manifolds with different dimensions and intersections.
method Investigate sufficient conditions for similarity graphs to capture geometric information.
result High probability error bounds for spectral approximation of tensorized Laplacian.

Paper proposes methods to learn sub-manifolds and estimate densities in normalizing flows.

problem Normalizing flows struggle with finding sub-manifolds in high-dimensional data.
method Introduces per-pixel penalized log-likelihood and hierarchical training approaches.
result Validated superior performance in manifold learning and density estimation.

The paper investigates geometrical aspects of static spacetime with almost gradient Ricci solitons.

problem Geometrical properties of static spacetime with almost gradient Ricci solitons.
method Analyzing conditions and properties of static spacetime with almost gradient Ricci solitons.
result Conditions and properties of static spacetime with almost gradient Ricci solitons are determined.

It is proven that a local Lie algebra in the sense of A. A. Kirillov determines the base manifold up to a diffeomorphism provided the anchor map is nowhere-vanishing. In particular, the Lie algebras of nowhere-vanishing Poisson or Jacobi brackets determine manifolds. This result has been proven for different types of d…

2005-06-28abs ↗pdf ↗

SBMs learn manifold-like structures by mixing samples with a non-conservative field.

problem How SBMs learn data distributions on low-dimensional manifolds.
method Investigating linear approximations and subspaces of local feature vectors during diffusion.
result SBMs mix samples by a non-conservative field within the manifold, maintaining manifold-like structure.

Study fiber-preserving, orientation-reversing involutions on Seifert fibered 3-manifolds.

problem Characterize fiber-preserving, orientation-reversing involutions on Seifert fibered 3-manifolds.
method Construct a class of involutions, extend product involutions, and use double covering.
result Any fiber-preserving, orientation-reversing involution factors as a product of an orientation-preserving and a specific class of involutions.

Establishes a link between heat diffusion and manifold distances in data.

problem No theoretical link between diffusion-based manifold learning and geodesic distances.
method Formulates heat geodesic embeddings based on Riemannian geometry.
result Method outperforms state-of-the-art in preserving manifold distances and cluster structure.

We present a simple combinatorial method to encode 3-dimensional manifolds, based on their Heegaard diagrams. The notion of a Gauss diagram of a 3-manifold is introduced. We check the conditions for a Gauss diagram to represent a closed manifold and a manifold with boundary.

2003-08-06abs ↗pdf ↗

This paper is a sequel to arXiv:1108.0967. We further study Gromov-Hausdorff collapsing limits of Ricci-flat Kähler metrics on abelian fibered Calabi-Yau manifolds. Firstly, we show that in the same setup as arXiv:1108.0967, if the dimension of the base manifold is one, the limit metric space is homeomorphic to the bas…

2013-04-05abs ↗pdf ↗

The paper calculates curvature formulas for stable Higgs bundles.

problem Investigating the geometry of stable Higgs bundles over complex manifolds.
method Applying curvature formulas from Schumacher-Toma and Biswas-Schumacher to calculate and analyze the curvature of the base manifold.
result Explicit calculation of holomorphic sectional curvature for a complex Finsler metric.

By a classical theorem of Gallot (1979), a Riemannian cone over a complete Riemannian manifold is either flat or has irreducible holonomy. We consider metric cones with reducible holonomy over pseudo-Riemannian manifolds. First we describe the local structure of the base of the cone when the holonomy of the cone is dec…

2007-07-20abs ↗pdf ↗

We prove positive mass theorems on ALF manifolds, i.e. complete noncompact manifolds that are asymptotic to a circle fibration over a Euclidean base, with fibers of asymptotically constant length.

2008-03-19abs ↗pdf ↗

A new graph-based approach for estimating complex data with manifold structure.

problem Regression of large-scale, complex data with underlying geometric structure and noises.
method Constructing a skeleton graph to capture geometric structure, defining metrics, and applying nonparametric regression.
result Statistical guarantees and effectiveness demonstrated through simulations and real data examples.

We propose a new framework for manifold denoising based on processing in the graph Fourier frequency domain, derived from the spectral decomposition of the discrete graph Laplacian. Our approach uses the Spectral Graph Wavelet transform in order to per- form non-iterative denoising directly in the graph frequency domai…

2016-11-29abs ↗pdf ↗

A method to fix radius distortion in generative models on curved spaces.

problem Distortion in geodesic radius measurements across different charts on Riemannian manifolds.
method Radial Compensation (RC) adjusts the tangent-space base distribution to match the geodesic radius law, improving model stability and interpretability.
result RC ensures that the model's geodesic radius matches the intended distribution, improving numerical stability and curvature interpretation.

We show that all versions of Heegaard Floer homology, link Floer homology, and sutured Floer homology are natural. That is, they assign concrete groups to each based 3-manifold, based link, and balanced sutured manifold, respectively. Furthermore, we functorially assign isomorphisms to (based) diffeomorphisms, and show…

2012-10-18abs ↗pdf ↗

A new spline method for manifold learning using Hessian-based curvature penalties.

problem Learning manifolds with curvature penalties in high dimensions.
method Generalizes thin-plate splines to flat manifolds using Hessian matrices, minimizing square error with curvature constraints.
result Existence and uniqueness of the spline solution, expressed as Green's functions and Hessian approximations.