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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.

168,657 papers · 148 categories

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15304459 · May 202619922001200920172026
48 results for spherical harmonics

Study spherical Fourier transform on hypergeometric type harmonic manifolds.

problem Spherical Fourier transform on harmonic Hadamard manifolds.
method Representation of spherical functions by Gauss hypergeometric functions.
result Inversion formula, convolution rule, and Plancherel theorem are derived.

Revisits Gaussian process model with spherical harmonics for scalable deep learning.

problem Scaling Gaussian process models to large input dimensions with high frequency learning.
method Introduces new kernels related to deep models, variational learning of spherical harmonic phases, and sparseness in eigenbasis.
result Enables scaling to larger input dimensions and learning of high frequency variations.

A spherical topological manifold of dimension n-1 forms a prototile on its cover, the (n-1)-sphere. The tiling is generated by the fixpoint-free action of the group of deck transformations. By a general theorem, this group is isomorphic to the first homotopy group. Multiplicity and selection rules appear in the form of…

2008-10-19abs ↗pdf ↗

A new method using spherical harmonics approximates the Sliced-Wasserstein distance.

problem Approximating the Sliced-Wasserstein distance between probability measures.
method Spherical Harmonics Control Variates (SHCV) method for Monte Carlo approximation of the SW distance.
result SHCV method provides an improved rate of convergence compared to Monte Carlo for general measures.

We show that real and imaginary parts of equivariant spherical harmonics on S3S^3 have almost surely a single nodal component. Moreover, if the degree of the spherical harmonic is NN and the equivariance degree is mm, then the expected genus is proportional to m(N2m22+N)m \left(\frac{N^2 - m^2}{2} + N\right) . Hence if $\fra…

2019-08-02abs ↗pdf ↗

DELIMIT is a framework extension for deep learning in diffusion imaging, which extends the basic framework PyTorch towards spherical signals. Based on several novel layers, deep learning can be applied to spherical diffusion imaging data in a very convenient way. First, two spherical harmonic interpolation layers are a…

2018-08-04abs ↗pdf ↗

New algorithms learn multi-index models via harmonic analysis, achieving statistical and computational trade-offs.

problem Learning multi-index models with unknown projections of input data.
method Exploiting the equivariance of the problem under the orthogonal group, we derive lower bounds and construct spectral algorithms based on harmonic tensor unfolding.
result Achieve statistical and computational trade-offs between sample and runtime complexity.

Paper studies Laplace operator estimates in harmonic map heat flows.

problem Estimating Laplace operator in harmonic map heat flows outside singularities.
method Investigates estimates using spherical coordinates for T2\mathbb{T}^2 and T3\mathbb{T}^3 boundary conditions.
result Provides higher-order estimates for the Ericksen--Leslie system.

In this article we study various analytic aspects of interpolating sesqui-harmonic maps between Riemannian manifolds where we mostly focus on the case of a spherical target. The latter are critical points of an energy functional that interpolates between the functionals for harmonic and biharmonic maps. In the case of …

2019-07-09abs ↗pdf ↗

The paper explores eigenfunctions of spherical conical metrics using harmonic maps to spheres.

problem Existence and properties of eigenfunctions for spherical conical metrics.
method Application of multivalued harmonic maps to spheres and algebraic constructions.
result New criteria and examples of metrics with many 2-eigenfunctions.

New method uses spherical harmonics to simplify learning single-index models.

problem Learning single-index models with unknown one-dimensional projections.
method Proposes using spherical harmonics instead of Hermite polynomials to capture rotational symmetry.
result Characterizes the complexity of learning single-index models under arbitrary spherically symmetric input distributions.

Research proves limits on harmonic map orders into Euclidean buildings.

problem Limits on the possible orders of harmonic maps from surfaces to Euclidean buildings.
method Direct analysis of homogeneous maps and related spherical billiards problem.
result The order of harmonic maps is of the form mk\frac mk where kk divides W|W|.

The behavior of geodesic curves on even seemingly simple surfaces can be surprisingly complex. In this paper we use the Hamiltonian formulation of the geodesic equations to analyze their integrability properties. In particular, we examine the behavior of geodesics on surfaces defined by the spherical harmonics. Using t…

2011-12-14abs ↗pdf ↗

Identifies conjugate points in spherical harmonics solutions of quasi-geostrophic equations.

problem Locating conjugate points in spherical harmonics solutions.
method Utilizing structure constants and quasi-geostrophic equations on the sphere, identifying conjugate points.
result Existence and location of conjugate points along spherical harmonics solutions.

Developed a diffusion model on spherical data, addressing geometric and stochastic challenges.

problem Diffusion models on spherical data face unique geometric and stochastic issues.
method Extended spectral diffusion to spherical harmonics, introducing modified stochastic differential equations.
result Introduced a geometry-dependent inductive bias in spectral diffusion models.

In this note, we consider a fixed vector field VV on S2S^2 and study the distribution of points which lie on the nodal set (of a random spherical harmonic) where VV is also tangent. We show that the expected value of the corresponding counting function is asymptotic to the eigenvalue with a leading coefficient that i…

2018-09-05abs ↗pdf ↗

Bayesian framework for sphere regression using Gaussian fields.

problem Nonparametric regression on the sphere with Gaussian priors.
method Isotropic Gaussian field priors, harmonic structure, exact posterior distributions, optimal spectral truncation, posterior contraction rates.
result Sharp posterior contraction rates for Gaussian priors with polynomially decaying angular power spectra.

The paper examines curvature and stability in quasi-geostrophic motions using spherical harmonics.

problem Analyzing the curvature and stability of quasi-geostrophic motions.
method Utilizing spherical harmonics and structure constants, the curvature of the L2L^2 metric on the central extension is computed.
result A lower bound for weather prediction error in a simplified model is suggested.

Solves wave equation on non-flat harmonic manifolds using Abel transform and Fourier analysis.

problem Wave equation on non-flat harmonic manifolds with specific curvature conditions.
method Explicit representation using inverse dual Abel transform and Fourier transform.
result Shows asymptotic Huygens principle and equidistribution of energy.

We prove boundedness and polynomial decay statements for solutions to the spin ±1\pm1 Teukolsky-type equation projected to the =1\ell=1 spherical harmonic on Reissner-Nordström spacetime. The equation is verified by a gauge-invariant quantity which we identify and which involves the electromagnetic and curvature tensor…

2018-12-06abs ↗pdf ↗

The absence of interesting harmonic sections for the Sasaki and Cheeger-Gromoll metrics has led to the consideration of alternatives, for example in the form of a two-parameter family of natural metrics shown to relax existence conditions for harmonicity. This article investigates harmonic Killing vector fields, proves…

2007-03-02abs ↗pdf ↗

Harmonic functions on compact symmetric spaces exhibit strong convexity properties.

problem Understanding the convexity of harmonic functions on compact symmetric spaces.
method Analyzing the nonnegativity of the Laplacian powers of harmonic functions.
result Harmonic functions on compact symmetric spaces have nonnegative Laplacian powers, demonstrating strong convexity.

We study singularities of constant positive Gaussian curvature surfaces and determine the way they bifurcate in generic 1-parameter families of such surfaces. We construct the bifurcations explicitly using loop group methods. Constant Gaussian curvature surfaces correspond to harmonic maps, and we examine the relations…

2017-09-04abs ↗pdf ↗

Study of harmonic maps into principal bundles with applications to magnetic interactions.

problem Understanding harmonic mappings from Riemannian manifolds into principal bundles.
method Characterization and analysis of Kaluza-Klein harmonic maps and generalized magnetic maps.
result Existence and properties of generalized magnetic maps, including non-trivial examples.

We develop a solution theory for a generalized electro-magneto static Maxwell system in an exterior domain with anisotropic coefficients converging at infinity with a certain rate towards the identity. Our main goal is to treat right hand side data from some polynomially weighted Sobolev spaces and obtain solutions whi…

2011-05-20abs ↗pdf ↗

In this work, we study the pseudo-Riemannian submanifolds of a pseudo-sphere with 1-type pseudo-spherical Gauss map. First, we classify the Lorentzian surfaces in a 4-dimensional pseudo-sphere Ss4(1)\mathbb{S}^4_s(1) with index s, s=1,2s=1, 2, and having harmonic pseudo-spherical Gauss map. Then we give a characterization the…

2015-10-28abs ↗pdf ↗

Paper identifies key function spaces for ReLU networks based on Fisher information.

problem Understanding the structure of Fisher information matrices in ReLU networks.
method Spectral decomposition of Fisher information matrices, focusing on the first three eigenspaces.
result The first three eigenspaces account for 97.7% of the trace of the Fisher information matrix, corresponding to spherical harmonic functions of order ≤2.

We demonstrate that it is conceptually and computationally favorable to regard spin-weighted spherical harmonics as vector valued functions on the total space SO(3)SO(3) of the Hopf bundle, satisfying a covariance condition with respect to the gauge group U(1)U(1) of this bundle. A key role is played by the invariant connec…

2014-03-03abs ↗pdf ↗

QC-SPHARM detects Alzheimer's Disease early using hippocampal surface geometry.

problem Early detection of Alzheimer's Disease (AD) using hippocampal surface geometry.
method Spherical harmonics registration, conformality and curvature distortions quantification, t-test feature selection, SVM classification.
result 85.2% testing accuracy on ADNI data, 81.2% on aMCI progression data.

Inspired by work of Colding-Minicozzi on mean curvature flow, Zhang introduced a notion of entropy stability for harmonic map flow. We build further upon this work in several directions. First we prove the equivalence of entropy stability with a more computationally tractable F\mathcal F-stability. Then, focusing on t…

2015-06-24abs ↗pdf ↗

Classifies low-energy harmonic maps from curved surfaces to spheres.

problem Classifying harmonic maps from curved surfaces to spheres under low energy conditions.
method Classifies maps via bubble scales and centers, focusing on degree-one maps as α approaches 1.
result Degree-one αα-harmonic maps blow a bubble based at a critical point of a function J\mathcal{J}, which is the sum of squares of holomorphic one-forms.

Polynomial networks converge to Gaussian processes at a rate of O(n^(-1/2)).

problem Understanding the convergence rate of polynomial networks to Gaussian processes.
method Examined one-hidden-layer neural networks with random weights, focusing on polynomial activations and their convergence rate in the 2-Wasserstein metric.
result The rate of convergence for polynomial networks to Gaussian processes is $O(n^{- rac{1}{2}})$.

New method solves PDEs on spheres using physics-informed convolutional neural networks.

problem Solving PDEs on surfaces, especially spheres, with high accuracy and efficiency.
method Physics-informed convolutional neural networks (PICNN) with theoretical analysis and approximation results.
result Established fast convergence rates for PICNN solving PDEs on spheres.

We study surfaces of constant positive Gauss curvature in Euclidean 3-space via the harmonicity of the Gauss map. Using the loop group representation, we solve the regular and the singular geometric Cauchy problems for these surfaces, and use these solutions to compute several new examples. We give the criteria on the …

2015-06-04abs ↗pdf ↗