Clairaut Pointwise Slant Submersion from Locally Product Riemannian Manifolds
نویسندگان
چکیده
The goal of the present paper is to analyze some geometric features Clairaut pointwise slant submersions whose total manifold a locally product Riemannian manifold. We describe from onto study by providing consequent which defines geodesics on space this type submersions. also give non-trivial example manifolds are Riemannian.
منابع مشابه
Semi-slant Pseudo-riemannian Submersions from Indefinite Almost Contact 3-structure Manifolds onto Pseudo-riemannian Manifolds
In this paper, we introduce the notion of a semi-slant pseudoRiemannian submersion from an indefinite almost contact 3-structure manifold onto a pseudo-Riemannian manifold. We investigate the geometry of foliations determined by horizontal and vertical distributions and provide a non-trivial example. We also find a necessary and sufficient condition for a semi-slant submersion to be totally geo...
متن کاملWarped Product Submanifolds of Riemannian Product Manifolds
and Applied Analysis 3 where TX and NX are the tangential and normal components of FX, respectively, and for V ∈ T⊥M,
متن کاملLocally adaptive density estimation on Riemannian manifolds
In this paper, we consider kernel type estimator with variable bandwidth when the random variables belong in a Riemannian manifolds. We study asymptotic properties such as the consistency and the asymptotic distribution. A simulation study is also considered to evaluate the performance of the proposal. Finally, to illustrate the potential applications of the proposed estimator, we analyse two r...
متن کاملLower Bounds of the Dirac Eigenvalues on Compact Riemannian Spin Manifolds with Locally Product Structure
We study some similarities between almost product Riemannian structures and almost Hermitian structures. Inspired by the similarities, we prove lower eigenvalue estimates for the Dirac operator on compact Riemannian spin manifolds with locally product structures. We also provide some examples (limiting manifolds) for the limiting case of the estimates. MSC(2000): 53C25, 53C27, 58B20
متن کاملA Geometry Preserving Kernel over Riemannian Manifolds
Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data to high dimensional feature space without considering the intrinsic geometry of data points. ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International electronic journal of geometry
سال: 2023
ISSN: ['1307-5624']
DOI: https://doi.org/10.36890/iejg.1108703