Results 51 to 60 of about 10,692 (245)
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]
, 2014 Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Livingstone, Samuel +5 more
core +1 more source
Riemannian Geometry on Quantum Spaces [PDF]
International Journal of Modern Physics A, 1997 An algebraic formulation of Riemannian geometry on quantum spaces is presented, where Riemannian metric, distance, Laplacian, connection, and curvature have their counterparts. This description is also extended to complex manifolds. Examples include the quantum sphere, the complex quantum projective space and the two-sheeted space.
openaire +2 more sources
On Geometric Phase Model in the Theory of Curves With Myller Configuration
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT In this paper, we introduce a linearly polarized light wave in an optical fiber and rotation of the polarization plane through the Frenet‐type frame with Myller configuration. Since the geometric evaluation and interpretations of a polarized light wave are associated with geometric phase, a new type of geometric phase model has been ...
Zehra İşbilir +2 more
wiley +1 more source
Classification of Polarimetric SAR Images Based on the Riemannian Manifold
Leida xuebao, 2017 Classification is one of the core components in the interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. A new PolSAR image classification approach employs the structural properties of the Riemannian manifold formed by PolSAR ...
Yang Wen +3 more
doaj +1 more source
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source
Low Dimensional Flat Manifolds with Some Elasses of Finsler Metric
پژوهشهای ریاضی, 2020 Introduction An -dimensional Riemannian manifold is said to be flat (or locally Euclidean) if locally isometric with the Euclidean space, that is, admits a covering of coordinates neighborhoods each of which is isometric with a Euclidean domain.
Sedigheh Alavi Endrajemi +1 more
doaj
Mathematics, 2021 In this article, we discuss the global aspects of the geometry of locally conformally flat (complete and compact) Riemannian manifolds. In particular, the article reviews and improves some results (e.g., the conditions of compactness and degeneration ...
Josef Mikeš +3 more
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Lagrangian Multiplier and Riemannian Spaces [PDF]
Reviews of Modern Physics, 1949 The Riemannian geometries, which are derivable from a quadratic action principle, are generated by a new mathematical approach, based on the method of the Lagrangian multiplier. This changes the 10 differential equations of fourth order for the ${g}_{\mathrm{ik}}$ to 24 differential equations of second order for a new field quantity.
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SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
Computer Graphics Forum, EarlyView.We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier +5 more
wiley +1 more source
Kaluza–Klein reduction on a maximally non-Riemannian space is moduli-free
Physics Letters B, 2019 We propose a novel Kaluza–Klein scheme which assumes the internal space to be maximally non-Riemannian, meaning that no Riemannian metric can be defined for any subspace.
Kyoungho Cho +2 more
doaj +1 more source