EUR 102,25
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: new.
EUR 97,52
Quantità: 10 disponibili
Aggiungi al carrelloCondizione: new.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9811985391 ISBN 13: 9789811985393
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 129,38
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition.
Condizione: New. 1st ed. 2023 edition NO-PA16APR2015-KAP.
Da: Buchpark, Trebbin, Germania
EUR 72,43
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | 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.
Da: Revaluation Books, Exeter, Regno Unito
EUR 182,67
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 185 pages. 9.25x6.10x0.63 inches. In Stock.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 134,41
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.
Lingua: Inglese
Editore: Springer Verlag, Singapore, Singapore, 2023
ISBN 10: 9811985391 ISBN 13: 9789811985393
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 189,33
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Da: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Germania
EUR 199,90
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: gut. 2023. Einstein Constraints and Ricci Flow In deutscher Sprache. pages.
Da: Revaluation Books, Exeter, Regno Unito
EUR 132,85
Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 185 pages. 9.25x6.10x0.63 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Springer Nature Singapore Jan 2023, 2023
ISBN 10: 9811985391 ISBN 13: 9789811985393
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 128,39
Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 188 pp. Englisch.
Da: moluna, Greven, Germania
EUR 109,83
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Deals with the application of Ricci flow to the comparison and averaging of Einstein s initial data setsIntroduces Ricci flow conjugation between two distinct Einstein initial data sets, providing analysis of its propertiesProves Fourier mo.
Da: Majestic Books, Hounslow, Regno Unito
EUR 182,52
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Jan 2023, 2023
ISBN 10: 9811985391 ISBN 13: 9789811985393
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
EUR 128,39
Quantità: 1 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 188 pp. Englisch.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 181,75
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.