Catálogo de publicaciones - libros
Planewaves, Pseudopotentials and the LAPW Method
David J. Singh Lars Nordström
Second Edition.
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Characterization and Evaluation of Materials; Optical and Electronic Materials; Solid State Physics; Spectroscopy and Microscopy; Metallic Materials
Disponibilidad
Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
---|---|---|---|---|
No detectada | 2006 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-0-387-28780-5
ISBN electrónico
978-0-387-29684-5
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2006
Información sobre derechos de publicación
© Springer Science+Business Media, Inc. 2006
Cobertura temática
Tabla de contenidos
Introduction
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 1-3
Density Functional Theory and Methods
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 5-21
Planewave Pseudopotential Methods
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 23-41
Introduction to the LAPW Method
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 43-52
Nitty-Gritties
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 53-106
Car-Parrinello and the LAPW Method
David J. Singh; Lars Nordström
In Chapters 7 and 8we invested a good deal of time and energy in developing the many results we need from differential geometry. The time has now come to begin to reap the benefits of our investment, while at the same time developing some themes a little further for later exploitation. This chapter focuses on the celebrated volume-of-tubes formula of Wey1 [73, 168], which expresses the Lebesgue volume of a tube of radius ρ around a set embedded in ℝ or S(ℝ{sl}) in terms of the radius of the tube1 and the Lipschitz–Killing curvatures of (see Theorem 10.5.6). It is an interesting fact, particularly in view of the fact that this is a book about probability that is claimed to have applications to statistics, and despite the fact thatWeyl’s formula is today the basis of a large literature in geometry, that the origins of the volume-of-tubes formulas were inspired by a statistical problem. This problem, along with its solution due to Hotelling [79], were related to regression analysis and involved the one-dimensional volume-of-tubes problem on a sphere, not unrelated to the computation we shall do in a moment.
Pp. 107-122