Results 61 to 70 of about 217,307 (157)

On Extremal Problems in Certain New Bergman Type Spaces in Some Bounded Domains in Cn

open access: yesJournal of Function Spaces, Volume 2014, Issue 1, 2014., 2014
Based on recent results on boundedness of Bergman projection with positive Bergman kernel in analytic spaces in various types of domains in Cn, we extend our previous sharp results on distances obtained for analytic Bergman type spaces in unit disk to some new Bergman type spaces in Lie ball, bounded symmetric domains of tube type, Siegel domains, and ...
Romi F. Shamoyan   +2 more
wiley   +1 more source

Conformal equivalence of visual metrics in pseudoconvex domains

open access: yes, 2020
We refine estimates introduced by Balogh and Bonk, to show that the boundary extensions of isometries between bounded, smooth strongly pseudoconvex domains in Cn are conformal with respect to the sub-Riemannian metric induced by the Levi form.
Le Donne E., Capogna L.
core   +2 more sources

An exotic calculus of Berezin–Toeplitz operators

open access: yesMathematika, Volume 71, Issue 2, April 2025.
Abstract We develop a calculus of Berezin–Toeplitz operators quantizing exotic classes of smooth functions on compact Kähler manifolds and acting on holomorphic sections of powers of positive line bundles. These functions (classical observables) are exotic in the sense that their derivatives are allowed to grow in ways controlled by local geometry and ...
Izak Oltman
wiley   +1 more source

Boundary Asymptotics for Convex and Strongly Pseudoconvex Domains [PDF]

open access: yes, 2021
We present two results. The first is a converse to a theorem first proved by Wongwhich says the ratio of intrinsic measures approaches 1 near the boundary of a strongly pseudoconvex domain; we show that for a particular type of domain the boundary is ...
Martin, Alec
core  

New estimates of Rychkov's universal extension operator for Lipschitz domains and some applications

open access: yesMathematische Nachrichten, Volume 297, Issue 4, Page 1407-1443, April 2024.
Abstract Given a bounded Lipschitz domain Ω⊂Rn$\Omega \subset \mathbb {R}^n$, Rychkov showed that there is a linear extension operator E$\mathcal {E}$ for Ω$\Omega$, which is bounded in Besov and Triebel‐Lizorkin spaces. In this paper, we introduce some new estimates for the extension operator E$\mathcal {E}$ and give some applications.
Ziming Shi, Liding Yao
wiley   +1 more source

On isometries of the Caratheodory and Kobayashi metrics on strongly pseudoconvex domains [PDF]

open access: yes, 2006
Let Ω1 and Ω2 be strongly pseudoconvex domains in Cn and f:Ω1 → Ω2 an isometry for the Kobayashi or Caratheodory metrics. Suppose that f extends as a C1 map to ¯Ω1.
Seshadri, Harish, Verma, Kaushal
core   +2 more sources

Solutions to $ar{partial}$-equations on strongly pseudo-convex domains with $L^p$-estimates

open access: yesElectronic Journal of Differential Equations, 2004
We construct a solution to the $ar{partial}$-equation on a strongly pseudo-convex domain of a complex manifold. This is done for forms of type $(0,s)$, $sgeq 1 $, with values in a holomorphic vector bundle which is Nakano positive and for complex valued ...
Osama Abdelkader, Shaban Khidr
doaj  

Closed 3‐forms in five dimensions and embedding problems

open access: yesJournal of the London Mathematical Society, Volume 109, Issue 4, April 2024.
Abstract We consider the question if a five‐dimensional manifold can be embedded into a Calabi–Yau manifold of complex dimension 3 such that the real part of the holomorphic volume form induces a given closed 3‐form on the 5‐manifold. We define an open set of 3‐forms in dimension five which we call strongly pseudoconvex, and show that for closed ...
Simon Donaldson, Fabian Lehmann
wiley   +1 more source

Optimizing Artificial Neural Network Learning Using Improved Reinforcement Learning in Artificial Bee Colony Algorithm

open access: yesApplied Computational Intelligence and Soft Computing, Volume 2024, Issue 1, 2024.
Artificial neural networks (ANNs) are widely used machine learning techniques with applications in various fields. Heuristic search optimization methods are typically used to minimize the loss function in ANNs. However, these methods can lead the network to become stuck in local optima, limiting performance.
Taninnuch Lamjiak   +5 more
wiley   +1 more source

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