Tensor Analysis and Curvilinear Coordinates.Pdf

Total Page:16

File Type:pdf, Size:1020Kb

Tensor Analysis and Curvilinear Coordinates.Pdf Tensor Analysis and Curvilinear Coordinates Phil Lucht Rimrock Digital Technology, Salt Lake City, Utah 84103 last update: May 19, 2016 Maple code is available upon request. Comments and errata are welcome. The material in this document is copyrighted by the author. The graphics look ratty in Windows Adobe PDF viewers when not scaled up, but look just fine in this excellent freeware viewer: http://www.tracker-software.com/pdf-xchange-products-comparison-chart . The table of contents has live links. Most PDF viewers provide these links as bookmarks on the left. Overview and Summary.........................................................................................................................7 1. The Transformation F: invertibility, coordinate lines, and level surfaces..................................12 Example 1: Polar coordinates (N=2)..................................................................................................13 Example 2: Spherical coordinates (N=3)...........................................................................................14 Cartesian Space and Quasi-Cartesian Space.......................................................................................15 Pictures A,B,C and D..........................................................................................................................16 Coordinate Lines.................................................................................................................................16 Example 1: Polar coordinates, coordinate lines .................................................................................17 Example 2: Spherical coordinates, coordinate lines ..........................................................................18 Level Surfaces.....................................................................................................................................18 2. Linear Local Transformations associated with F : scalars and two kinds of vectors .................20 2.1 Linear Local Transformations.......................................................................................................20 2.2 Scalars...........................................................................................................................................21 2.3 Contravariant vectors ....................................................................................................................22 2.4 Covariant vectors ..........................................................................................................................22 2.5 Bar notation...................................................................................................................................23 2.6 Origin of the names contravariant and covariant ..........................................................................23 2.7 Other vector types? .......................................................................................................................24 2.8 Linear transformations ..................................................................................................................25 2.9 Vectors that are contravariant by definition..................................................................................26 2.10 Vector Fields...............................................................................................................................26 2.11 Names and symbols ....................................................................................................................27 2.12 Definition of the words "scalar", "vector" and "tensor"..............................................................28 3. Tangent Base Vectors en and Inverse Tangent Base Vectors u'n ..................................................30 3.1 Differential Displacements ...........................................................................................................30 3.2 Definition of the en ; the en are the columns of S.........................................................................31 3.3 en as a contravariant vector ...........................................................................................................33 3.4 A semantic question: unit vectors ................................................................................................33 Example 1: Polar coordinates, tangent base vectors ..........................................................................34 Example 2: Spherical Coordinates, tangent base vectors...................................................................35 3.5 The inverse tangent base vectors u'n and inverse coordinate lines................................................36 Example 1: Polar coordinates: inverse tangent base vectors and inverse coordinate lines...............37 1 4. Notions of length, distance and scalar product in Cartesian Space..............................................39 5. The Metric Tensor ............................................................................................................................41 5.1 The Picture D Context ..................................................................................................................41 5.2 Definition of the metric tensor......................................................................................................41 5.3 Inverse of the metric tensor...........................................................................................................44 5.4 A metric tensor is symmetric ........................................................................................................44 5.5 det(g) and gnn of a Cartesian-generated metric tensor are non-negative.......................................45 5.6 Definition of two kinds of rank-2 tensors .....................................................................................45 5.7 Proof that the metric tensor and its inverse are both rank-2 tensors .............................................46 5.8 Metric tensor converts vector types ..............................................................................................49 5.9 Vectors in Cartesian space ............................................................................................................49 5.10 The covariant dot product A • B and norm |A| .........................................................................50 5.11 Metric tensor and tangent base vectors: scale factors and orthogonal coordinates...................52 5.12 The Jacobian J.............................................................................................................................55 5.13 Some relations between g, R and S in Pictures B and C (Cartesian x-space).............................58 Example 1: Polar coordinates: metric tensor and Jacobian...............................................................60 Example 2: Spherical coordinates: metric tensor and Jacobian ........................................................61 5.14 Special Relativity and its Metric Tensor: vectors and spinors...................................................62 5.15 General Relativity and its Metric Tensor....................................................................................65 5.16 Continuum Mechanics and its Metric Tensors............................................................................66 6. Reciprocal Base Vectors En and Inverse Reciprocal Base Vectors U'n........................................73 6.1 Definition of the En .......................................................................................................................73 6.2 The en and En Dot Products and Reciprocity (Duality) ................................................................74 6.3 Covariant partners for en and En ..................................................................................................78 6.4 Summary of the basic facts about en and En .................................................................................80 6.5 Repeat the above for the inverse transformation: definition of the U'n........................................80 6.6 Expanding vectors on different sets of basis vectors ....................................................................81 6.7 Another way to write the En..........................................................................................................84 6.8 Comparison of ¯en and En ..............................................................................................................85 6.9 Handedness of coordinate systems: the en , the sign of det(S), and Parity ..................................86 7. Translation to the Standard Notation .............................................................................................89 7.1 Outer Products ..............................................................................................................................89 7.2 Mixed Tensors and Notation Issues..............................................................................................90 7.3 The up/down bell goes off ............................................................................................................91 7.4 Some Preliminary Translations; raising and lowering tensor indices with g...............................92 7.5 Dealing with the matrices R and S ; various Rules and Theorems ...............................................96 7.6 Orthogonality Rules, Inversion Rules, Cancellation
Recommended publications
  • Quaternions and Cli Ord Geometric Algebras
    Quaternions and Cliord Geometric Algebras Robert Benjamin Easter First Draft Edition (v1) (c) copyright 2015, Robert Benjamin Easter, all rights reserved. Preface As a rst rough draft that has been put together very quickly, this book is likely to contain errata and disorganization. The references list and inline citations are very incompete, so the reader should search around for more references. I do not claim to be the inventor of any of the mathematics found here. However, some parts of this book may be considered new in some sense and were in small parts my own original research. Much of the contents was originally written by me as contributions to a web encyclopedia project just for fun, but for various reasons was inappropriate in an encyclopedic volume. I did not originally intend to write this book. This is not a dissertation, nor did its development receive any funding or proper peer review. I oer this free book to the public, such as it is, in the hope it could be helpful to an interested reader. June 19, 2015 - Robert B. Easter. (v1) [email protected] 3 Table of contents Preface . 3 List of gures . 9 1 Quaternion Algebra . 11 1.1 The Quaternion Formula . 11 1.2 The Scalar and Vector Parts . 15 1.3 The Quaternion Product . 16 1.4 The Dot Product . 16 1.5 The Cross Product . 17 1.6 Conjugates . 18 1.7 Tensor or Magnitude . 20 1.8 Versors . 20 1.9 Biradials . 22 1.10 Quaternion Identities . 23 1.11 The Biradial b/a .
    [Show full text]
  • 1 Parity 2 Time Reversal
    Even Odd Symmetry Lecture 9 1 Parity The normal modes of a string have either even or odd symmetry. This also occurs for stationary states in Quantum Mechanics. The transformation is called partiy. We previously found for the harmonic oscillator that there were 2 distinct types of wave function solutions characterized by the selection of the starting integer in their series representation. This selection produced a series in odd or even powers of the coordiante so that the wave function was either odd or even upon reflections about the origin, x = 0. Since the potential energy function depends on the square of the position, x2, the energy eignevalue was always positive and independent of whether the eigenfunctions were odd or even under reflection. In 1-D parity is the symmetry operation, x → −x. In 3-D the strong interaction is invarient under the symmetry of parity. ~r → −~r Parity is a mirror reflection plus a rotation of 180◦, and transforms a right-handed coordinate system into a left-handed one. Our Macroscopic world is clearly “handed”, but “handedness” in fundamental interactions is more involved. Vectors (tensors of rank 1), as illustrated in the definition above, change sign under Parity. Scalars (tensors of rank 0) do not. One can then construct, using tensor algebra, new tensors which reduce the tensor rank and/or change the symmetry of the tensor. Thus a dual of a symmetric tensor of rank 2 is a pseudovector (cross product of two vectors), and a scalar product of a pseudovector and a vector creates a pseudoscalar. We will construct bilinear forms below which have these rotational and reflection char- acteristics.
    [Show full text]
  • A.7 Orthogonal Curvilinear Coordinates
    ~NSORS Orthogonal Curvilinear Coordinates 569 )osition ated by converting its components (but not the unit dyads) to spherical coordinates, and 1 r+r', integrating each over the two spherical angles (see Section A.7). The off-diagonal terms in Eq. (A.6-13) vanish, again due to the symmetry. (A.6-6) A.7 ORTHOGONAL CURVILINEAR COORDINATES (A.6-7) Enormous simplificatons are achieved in solving a partial differential equation if all boundaries in the problem correspond to coordinate surfaces, which are surfaces gener­ (A.6-8) ated by holding one coordinate constant and varying the other two. Accordingly, many special coordinate systems have been devised to solve problems in particular geometries. to func­ The most useful of these systems are orthogonal; that is, at any point in space the he usual vectors aligned with the three coordinate directions are mutually perpendicular. In gen­ st calcu­ eral, the variation of a single coordinate will generate a curve in space, rather than a :lrSe and straight line; hence the term curvilinear. In this section a general discussion of orthogo­ nal curvilinear systems is given first, and then the relationships for cylindrical and spher­ ical coordinates are derived as special cases. The presentation here closely follows that in Hildebrand (1976). ial prop­ Base Vectors ve obtain Let (Ul, U2' U3) represent the three coordinates in a general, curvilinear system, and let (A.6-9) ei be the unit vector that points in the direction of increasing ui• A curve produced by varying U;, with uj (j =1= i) held constant, will be referred to as a "u; curve." Although the base vectors are each of constant (unit) magnitude, the fact that a U; curve is not gener­ (A.6-1O) ally a straight line means that their direction is variable.
    [Show full text]
  • Geometrical Tools for Embedding Fields, Submanifolds, and Foliations Arxiv
    Geometrical tools for embedding fields, submanifolds, and foliations Antony J. Speranza∗ Perimeter Institute for Theoretical Physics, 31 Caroline St. N, Waterloo, ON N2L 2Y5, Canada Abstract Embedding fields provide a way of coupling a background structure to a theory while preserving diffeomorphism-invariance. Examples of such background structures include embedded submani- folds, such as branes; boundaries of local subregions, such as the Ryu-Takayanagi surface in holog- raphy; and foliations, which appear in fluid dynamics and force-free electrodynamics. This work presents a systematic framework for computing geometric properties of these background structures in the embedding field description. An overview of the local geometric quantities associated with a foliation is given, including a review of the Gauss, Codazzi, and Ricci-Voss equations, which relate the geometry of the foliation to the ambient curvature. Generalizations of these equations for cur- vature in the nonintegrable normal directions are derived. Particular care is given to the question of which objects are well-defined for single submanifolds, and which depend on the structure of the foliation away from a submanifold. Variational formulas are provided for the geometric quantities, which involve contributions both from the variation of the embedding map as well as variations of the ambient metric. As an application of these variational formulas, a derivation is given of the Jacobi equation, describing perturbations of extremal area surfaces of arbitrary codimension. The embedding field formalism is also applied to the problem of classifying boundary conditions for general relativity in a finite subregion that lead to integrable Hamiltonians. The framework developed in this paper will provide a useful set of tools for future analyses of brane dynamics, fluid arXiv:1904.08012v2 [gr-qc] 26 Apr 2019 mechanics, and edge modes for finite subregions of diffeomorphism-invariant theories.
    [Show full text]
  • Arxiv:2012.13347V1 [Physics.Class-Ph] 15 Dec 2020
    KPOP E-2020-04 Bra-Ket Representation of the Inertia Tensor U-Rae Kim, Dohyun Kim, and Jungil Lee∗ KPOPE Collaboration, Department of Physics, Korea University, Seoul 02841, Korea (Dated: June 18, 2021) Abstract We employ Dirac's bra-ket notation to define the inertia tensor operator that is independent of the choice of bases or coordinate system. The principal axes and the corresponding principal values for the elliptic plate are determined only based on the geometry. By making use of a general symmetric tensor operator, we develop a method of diagonalization that is convenient and intuitive in determining the eigenvector. We demonstrate that the bra-ket approach greatly simplifies the computation of the inertia tensor with an example of an N-dimensional ellipsoid. The exploitation of the bra-ket notation to compute the inertia tensor in classical mechanics should provide undergraduate students with a strong background necessary to deal with abstract quantum mechanical problems. PACS numbers: 01.40.Fk, 01.55.+b, 45.20.dc, 45.40.Bb Keywords: Classical mechanics, Inertia tensor, Bra-ket notation, Diagonalization, Hyperellipsoid arXiv:2012.13347v1 [physics.class-ph] 15 Dec 2020 ∗Electronic address: [email protected]; Director of the Korea Pragmatist Organization for Physics Educa- tion (KPOP E) 1 I. INTRODUCTION The inertia tensor is one of the essential ingredients in classical mechanics with which one can investigate the rotational properties of rigid-body motion [1]. The symmetric nature of the rank-2 Cartesian tensor guarantees that it is described by three fundamental parameters called the principal moments of inertia Ii, each of which is the moment of inertia along a principal axis.
    [Show full text]
  • Symmetry and Tensors Rotations and Tensors
    Symmetry and tensors Rotations and tensors A rotation of a 3-vector is accomplished by an orthogonal transformation. Represented as a matrix, A, we replace each vector, v, by a rotated vector, v0, given by multiplying by A, 0 v = Av In index notation, 0 X vm = Amnvn n Since a rotation must preserve lengths of vectors, we require 02 X 0 0 X 2 v = vmvm = vmvm = v m m Therefore, X X 0 0 vmvm = vmvm m m ! ! X X X = Amnvn Amkvk m n k ! X X = AmnAmk vnvk k;n m Since xn is arbitrary, this is true if and only if X AmnAmk = δnk m t which we can rewrite using the transpose, Amn = Anm, as X t AnmAmk = δnk m In matrix notation, this is t A A = I where I is the identity matrix. This is equivalent to At = A−1. Multi-index objects such as matrices, Mmn, or the Levi-Civita tensor, "ijk, have definite transformation properties under rotations. We call an object a (rotational) tensor if each index transforms in the same way as a vector. An object with no indices, that is, a function, does not transform at all and is called a scalar. 0 A matrix Mmn is a (second rank) tensor if and only if, when we rotate vectors v to v , its new components are given by 0 X Mmn = AmjAnkMjk jk This is what we expect if we imagine Mmn to be built out of vectors as Mmn = umvn, for example. In the same way, we see that the Levi-Civita tensor transforms as 0 X "ijk = AilAjmAkn"lmn lmn 1 Recall that "ijk, because it is totally antisymmetric, is completely determined by only one of its components, say, "123.
    [Show full text]
  • Area and Volume in Curvilinear Coordinates 1 Overview
    Area and Volume in curvilinear coordinates 1 Overview There are several reasons why we need to have a way of measuring ares and volumes in general relativity. the gravitational field of a point mass m will be singular at the location of the mass, so we typically compute the field of a mass density; i.e., the mass contained in a unit volume. If we are dealing with the Gauss law of electrodynamics (and there will be a similar law for gravity) then we need to compute the flux through an area. How should areas and volumes be defined in general metrics? Let us start in flat 3-dimensional space with Cartesian coordinates. Consider two vectors V;~ W~ . These vectors describe the sides of a parallelogram, whose area can be written as A~ = V~ × W~ (1) The cross-product has magnitude jA~j = jV~ jjW~ j sin θ (2) and is seen to equal the area of the parallelogram. The direction of the cross product also serves a useful purpose: it gives the normal direction to the area spanned by the vectors. Note that there are two normal directions to the area { pointing above the plane and below the plane { and the `right hand rule' for cross products is a convention that picks out one of these over the other. Thus there is a choice of convention in the choice of normal; we will see this fact again later. The cross product can be written in terms of a determinant 0 x^ y^ z^ 1 V~ × W~ = @ V x V y V z A (3) W x W y W z A determinant is computed by computing a product of numbers, taking one number from each row, while making sure that we also take only one number from each column.
    [Show full text]
  • Multilinear Algebra
    Appendix A Multilinear Algebra This chapter presents concepts from multilinear algebra based on the basic properties of finite dimensional vector spaces and linear maps. The primary aim of the chapter is to give a concise introduction to alternating tensors which are necessary to define differential forms on manifolds. Many of the stated definitions and propositions can be found in Lee [1], Chaps. 11, 12 and 14. Some definitions and propositions are complemented by short and simple examples. First, in Sect. A.1 dual and bidual vector spaces are discussed. Subsequently, in Sects. A.2–A.4, tensors and alternating tensors together with operations such as the tensor and wedge product are introduced. Lastly, in Sect. A.5, the concepts which are necessary to introduce the wedge product are summarized in eight steps. A.1 The Dual Space Let V be a real vector space of finite dimension dim V = n.Let(e1,...,en) be a basis of V . Then every v ∈ V can be uniquely represented as a linear combination i v = v ei , (A.1) where summation convention over repeated indices is applied. The coefficients vi ∈ R arereferredtoascomponents of the vector v. Throughout the whole chapter, only finite dimensional real vector spaces, typically denoted by V , are treated. When not stated differently, summation convention is applied. Definition A.1 (Dual Space)Thedual space of V is the set of real-valued linear functionals ∗ V := {ω : V → R : ω linear} . (A.2) The elements of the dual space V ∗ are called linear forms on V . © Springer International Publishing Switzerland 2015 123 S.R.
    [Show full text]
  • Curvilinear Coordinate Systems
    Appendix A Curvilinear coordinate systems Results in the main text are given in one of the three most frequently used coordinate systems: Cartesian, cylindrical or spherical. Here, we provide the material necessary for formulation of the elasticity problems in an arbitrary curvilinear orthogonal coor- dinate system. We then specify the elasticity equations for four coordinate systems: elliptic cylindrical, bipolar cylindrical, toroidal and ellipsoidal. These coordinate systems (and a number of other, more complex systems) are discussed in detail in the book of Blokh (1964). The elasticity equations in general curvilinear coordinates are given in terms of either tensorial or physical components. Therefore, explanation of the relationship between these components and the necessary background are given in the text to follow. Curvilinear coordinates ~i (i = 1,2,3) can be specified by expressing them ~i = ~i(Xl,X2,X3) in terms of Cartesian coordinates Xi (i = 1,2,3). It is as- sumed that these functions have continuous first partial derivatives and Jacobian J = la~i/axjl =I- 0 everywhere. Surfaces ~i = const (i = 1,2,3) are called coordinate surfaces and pairs of these surfaces intersects along coordinate curves. If the coordinate surfaces intersect at an angle :rr /2, the curvilinear coordinate system is called orthogonal. The usual summation convention (summation over repeated indices from 1 to 3) is assumed, unless noted otherwise. Metric tensor In Cartesian coordinates Xi the square of the distance ds between two neighboring points in space is determined by ds 2 = dxi dXi Since we have ds2 = gkm d~k d~m where functions aXi aXi gkm = a~k a~m constitute components of the metric tensor.
    [Show full text]
  • 1.3 Cartesian Tensors a Second-Order Cartesian Tensor Is Defined As A
    1.3 Cartesian tensors A second-order Cartesian tensor is defined as a linear combination of dyadic products as, T Tijee i j . (1.3.1) The coefficients Tij are the components of T . A tensor exists independent of any coordinate system. The tensor will have different components in different coordinate systems. The tensor T has components Tij with respect to basis {ei} and components Tij with respect to basis {e i}, i.e., T T e e T e e . (1.3.2) pq p q ij i j From (1.3.2) and (1.2.4.6), Tpq ep eq TpqQipQjqei e j Tij e i e j . (1.3.3) Tij QipQjqTpq . (1.3.4) Similarly from (1.3.2) and (1.2.4.6) Tij e i e j Tij QipQjqep eq Tpqe p eq , (1.3.5) Tpq QipQjqTij . (1.3.6) Equations (1.3.4) and (1.3.6) are the transformation rules for changing second order tensor components under change of basis. In general Cartesian tensors of higher order can be expressed as T T e e ... e , (1.3.7) ij ...n i j n and the components transform according to Tijk ... QipQjqQkr ...Tpqr... , Tpqr ... QipQjqQkr ...Tijk ... (1.3.8) The tensor product S T of a CT(m) S and a CT(n) T is a CT(m+n) such that S T S T e e e e e e . i1i2 im j1j 2 jn i1 i2 im j1 j2 j n 1.3.1 Contraction T Consider the components i1i2 ip iq in of a CT(n).
    [Show full text]
  • Darvas, G.: Quaternion/Vector Dual Space Algebras Applied to the Dirac
    Bulletin of the Transilvania University of Bra¸sov • Vol 8(57), No. 1 - 2015 Series III: Mathematics, Informatics, Physics, 27-42 QUATERNION/VECTOR DUAL SPACE ALGEBRAS APPLIED TO THE DIRAC EQUATION AND ITS EXTENSIONS Gy¨orgyDARVAS 1 Comunicated to the conference: Finsler Extensions of Relativity Theory, Brasov, Romania, August 18 - 23, 2014 Abstract The paper re-applies the 64-part algebra discussed by P. Rowlands in a series of (FERT and other) papers in the recent years. It demonstrates that the original introduction of the γ algebra by Dirac to "the quantum the- ory of the electron" can be interpreted with the help of quaternions: both the α matrices and the Pauli (σ) matrices in Dirac's original interpretation can be rewritten in quaternion forms. This allows to construct the Dirac γ matrices in two (quaternion-vector) matrix product representations - in accordance with the double vector algebra introduced by P. Rowlands. The paper attempts to demonstrate that the Dirac equation in its form modified by P. Rowlands, essentially coincides with the original one. The paper shows that one of these representations affects the γ4 and γ5 matrices, but leaves the vector of the Pauli spinors intact; and the other representation leaves the γ matrices intact, while it transforms the spin vector into a quaternion pseudovector. So the paper concludes that the introduction of quaternion formulation in QED does not provide us with additional physical informa- tion. These transformations affect all gauge extensions of the Dirac equation, presented by the author earlier, in a similar way. This is demonstrated by the introduction of an additional parameter (named earlier isotopic field-charge spin) and the application of a so-called tau algebra that governs its invariance transformation.
    [Show full text]
  • Appendix a Orthogonal Curvilinear Coordinates
    Appendix A Orthogonal Curvilinear Coordinates Given a symmetry for a system under study, the calculations can be simplified by choosing, instead of a Cartesian coordinate system, another set of coordinates which takes advantage of that symmetry. For example calculations in spherical coordinates result easier for systems with spherical symmetry. In this chapter we will write the general form of the differential operators used in electrodynamics and then give their expressions in spherical and cylindrical coordi- nates.1 A.1 Orthogonal curvilinear coordinates A system of coordinates u1, u2, u3, can be defined so that the Cartesian coordinates x, y and z are known functions of the new coordinates: x = x(u1, u2, u3) y = y(u1, u2, u3) z = z(u1, u2, u3) (A.1) Systems of orthogonal curvilinear coordinates are defined as systems for which locally, nearby each point P(u1, u2, u3), the surfaces u1 = const, u2 = const, u3 = const are mutually orthogonal. An elementary cube, bounded by the surfaces u1 = const, u2 = const, u3 = const, as shown in Fig. A.1, will have its edges with lengths h1du1, h2du2, h3du3 where h1, h2, h3 are in general functions of u1, u2, u3. The length ds of the line- element OG, one diagonal of the cube, in Cartesian coordinates is: ds = (dx)2 + (dy)2 + (dz)2 1The orthogonal coordinates are presented with more details in J.A. Stratton, Electromagnetic The- ory, McGraw-Hill, 1941, where many other useful coordinate systems (elliptic, parabolic, bipolar, spheroidal, paraboloidal, ellipsoidal) are given. © Springer International Publishing Switzerland 2016 189 F. Lacava, Classical Electrodynamics, Undergraduate Lecture Notes in Physics, DOI 10.1007/978-3-319-39474-9 190 Appendix A: Orthogonal Curvilinear Coordinates Fig.
    [Show full text]