Results 21 to 30 of about 8,243 (102)

Connections on non-symmetric (generalized) Riemannian manifold and gravity

open access: yes, 2015
Connections with (skew-symmetric) torsion on non-symmetric Riemannian manifold satisfying the Einstein metricity condition (NGT with torsion) are considered.
Ivanov, Stefan, Zlatanovic, Milan
core   +1 more source

A Goldberg-Sachs theorem in dimension three [PDF]

open access: yes, 2015
We prove a Goldberg-Sachs theorem in dimension three. To be precise, given a three-dimensional Lorentzian manifold satisfying the topological massive gravity equations, we provide necessary and sufficient conditions on the tracefree Ricci tensor for the ...
Nurowski, Pawel, Taghavi-Chabert, Arman
core   +2 more sources

Riemannian submersions from almost contact metric manifolds

open access: yes, 2011
In this paper we obtain the structure equation of a contact-complex Riemannian submersion and give some applications of this equation in the study of almost cosymplectic manifolds with Kaehler fibres.Comment: Abh. Math. Semin. Univ.
A. Bonome   +38 more
core   +1 more source

Weighted metrics on tangent sphere bundles [PDF]

open access: yes, 2010
Natural metric structures on the tangent bundle and tangent sphere bundles $S_rM$ of a Riemannian manifold $M$ with radius function $r$ enclose many important unsolved problems. Admitting metric connections on $M$ with torsion, we deduce the equations of
Albuquerque, Rui
core   +2 more sources

Sub-Riemannian Ricci curvatures and universal diameter bounds for 3-Sasakian manifolds [PDF]

open access: yes, 2016
For a fat sub-Riemannian structure, we introduce three canonical Ricci curvatures in the sense of Agrachev-Zelenko-Li. Under appropriate bounds we prove comparison theorems for conjugate lengths, Bonnet-Myers type results and Laplacian comparison ...
Rizzi, Luca, Silveira, Pavel
core   +4 more sources

Optimization of 3D‐Printed Structured Packings—Current State and Future Developments

open access: yesChemie Ingenieur Technik, EarlyView.
This paper gives an overview about structured packing development for distillation, surveying heuristic development cycles, computational fluid dynamics simulations, and additive manufacturing techniques. The emerging application of shape optimization to improve packings is emphasized, and its benefits, impact, and limitations are discussed.
Dennis Stucke   +3 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer 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

Spinorial Characterization of CR Structures, I [PDF]

open access: yes, 2014
We characterize certain CR structures of arbitrary codimension (different from 3, 4 and 5) on Riemannian Spin$^c$ manifolds by the existence of a Spin$^c$ structure carrying a strictly partially pure spinor field.
Hererra, Rafael, Nakad, Roger
core  

On the Electromagnetic Energy Flow Along Geodesics

open access: yesRadio Science, Volume 61, Issue 1, January 2026.
Abstract We present a field‐theoretic framework for modeling electromagnetic energy propagation in heterogeneous media by introducing the concept of electromagnetic geodesics. Unlike traditional ray optics, which assumes either a straight‐line propagation or a simple bending in refractive media, our approach formulates wave propagation as geodetic ...
Jacob T. Fokkema, Peter M. van den Berg
wiley   +1 more source

Vector‐Based and Machine Learning Approaches for Pore Network Parameters Analysis

open access: yesGeophysical Prospecting, Volume 74, Issue 1, January 2026.
ABSTRACT Accurate characterization of pore structures in carbonate rocks is critical for evaluating fluid flow and storage capacity in subsurface reservoirs, a key concern in geophysical exploration and reservoir engineering. This study proposes a hybrid digital rock physics workflow that integrates deep learning–based segmentation, vectorial geometric
José Frank V. Gonçalves   +4 more
wiley   +1 more source

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