JOURNAL ARTICLE

Applying of the surface theory of non-Euclidean spaces to the solution of the Monge-Ampere equation of elliptic type.

  • Published In: Uzbek Mathematical Journal, 2025, v. 69, n. 2. P. 23 1 of 3

  • Database: Mathematics Source 2 of 3

  • Authored By: A., Artykbaev; G. N., Kholmurodova 3 of 3

Abstract

Solutions of many geometry problems in the whole are related to solutions of differential equations. A.D. Alexandrov's problem of recovering a surface from a given extrinsic curvature function leads to the solution of the Dirichlet problem for the Monge-Ampere equation in a convex domain. The paper presents a method for generalizing the problem of recovering a convex surface from extrinsic curvature in non-Euclidean spaces. For this purpose, a cylindrical mapping is defined, which is a generalization of the spherical mapping, and a method is given for determining the extrinsic curvature of a convex surface in non-Euclidean spaces. Formulas for the extrinsic curvature of convex surfaces in some specific non-Euclidean spaces are calculated. It has been proven that in non-Euclidean spaces it is possible to generalize the problem of A.D. Alexandrov, which makes it possible to prove the existence of a solution to the Monge-Ampere equation in non-convex and non-simply connected domains with different boundary conditions. The problem of A.D. Alexandrov will lead to the solution of the Monge-Ampere equation, which is a special case of solutions to the equation proved by I.Ya. Bakelman. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Uzbek Mathematical Journal. 2025/04, Vol. 69, Issue 2, p23
  • Document Type:Article
  • Subject Area:History
  • Publication Date:2025
  • ISSN:2010-7269
  • DOI:10.29229/uzmj.2025-2-2
  • Accession Number:185879248
  • Copyright Statement:Copyright of Uzbek Mathematical Journal is the property of Uzbekistan Academy of Sciences, Institute of Mathematics named after V.I. Romanovskiy and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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