Einstein Constraints and Ricci Flow - A Geometrical Averaging of Initial Data Sets (Hardcover, 1st ed. 2023)

This book contains a self-consistent treatment of a geometric averaging technique, induced by the Ricci flow, that allows comparing a given (generalized) Einstein initial data set with another distinct Einstein initial data set, both supported on a given closed n-dimensional manifold. This is a case study where two vibrant areas of research in geometric analysis, Ricci flow and Einstein constraints theory, interact in a quite remarkable way. The interaction is of great relevance for applications in relativistic cosmology, allowing a mathematically rigorous approach to the initial data set averaging problem, at least when data sets are given on a closed space-like hypersurface. The book does not assume an a priori knowledge of Ricci flow theory, and considerable space is left for introducing the necessary techniques. These introductory parts gently evolve to a detailed discussion of the more advanced results concerning a Fourier-mode expansion and a sophisticated heat kernel representation of the Ricci flow, both of which are of independent interest in Ricci flow theory. This work is intended for advanced students in mathematical physics and researchers alike.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Mathematical Physics Studies
Release date:	2023
First published:	2023
Authors:	Mauro Carfora • Annalisa Marzuoli
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	173
Edition:	1st ed. 2023
ISBN-13:	978-981-19-8539-3
Categories:	Books > Science & Mathematics > Physics > General Books > Science & Mathematics > Mathematics > Geometry > Differential & Riemannian geometry Books > Science & Mathematics > Mathematics > Applied mathematics > General Promotions
LSN:	981-19-8539-1
Barcode:	9789811985393

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