Introduction to Differential Geometry with Tensor Applications. Группа авторов

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Introduction to Differential Geometry with Tensor Applications - Группа авторов

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style="font-size:15px;">      Preliminaries

      1.1 Introduction

      Some quantities are associated with their magnitude and direction, but certain quantities are associated with two or more directions. Such a quantity is called a tensor, e.g., the stress at a point of an elastic solid is an example of a tensor which depends on two directions: one is normal and the other is that of force on the area. Tensor comes from the word tension.

      In this chapter, we discuss the notation of systems of different orders, which are applied in the theory of determinants, symbols, and summation conventions. Also, results on some matrices and determinants are discussed because they will be used frequently later on.

      Let us consider the two quantities, a1, a1 or a1, a2, which are represented by ai or ai, respectively, for i = 1, 2. In such cases, the expressions ai, ai, ai j, ai j, and image are called systems. In each value of ai and ai are called systems of first order and each value of ai j, ai j, and image is called a double system or system of second order, of which a12, a22a23, a13, and image are called their respective components. Similarly, we have systems of the third order that depend on three indices shown as ai jk, aikl, ai jm, ai jn, and image and each number of their respective components are 8.

      In a system of order zero, it is shown that the quantity has no index, such as a. The upper and lower indices of a system are called its indices of contravariance and covariance, respectively. For a system of image, i and j are indices of a contravariant and k is of covariance. Accordingly, the system Aij is called a contravariant system, Aklm is called a covariant system, and is image called a mixed system.

      If in some expressions a certain index occurs twice, this means that this expression is summed with respect to that index for all admissible values of the index.

      Thus, the linear form image has an index, i, occurring in it twice. We will omit the summation symbol Σ and write aixi to mean a1x1 + a2x2 + a3x3 + a4x4. In order to avoid Σ, we shall make use of a convention used by A. Einstein which is accordingly called the Einstein Summation Convention or Summation Convention.

      Of course, the range of admissible values of the index, 1 to 4 in this case, must be specified. If the symbol i has a range of values from 1 to 3 and j ranges from 1 to 4, the expression

      represents three linear forms:

      (1.2) image

      Here, index i is the identifying (free) index and since index j, occurs twice, it is the summation index.

      We shall adopt this convention throughout the chapters and take the sum whenever a letter appears in a term once in a subscript and once in superscript or if the same two indices are in subscript or are in superscript.

      Example 1.3.1. Express the sum image.

      Solution: image

      We will assume that the summation and identifying indices have ranges of value from 1 to n.

      Thus, aixi will represent a linear form

image

      For example, image can be written as aikxixk and here, i and k both are dummy indexes.

      So, any dummy index can be replaced by any other index with a range of the same numbers.

      1.3.2 Free Index

      If in an expression an index is not a dummy, i.e., it is not repeated twice, then it is called a free index. For example, for ai jxj, the index j is dummy, but index i is free.

      A particular system of second order denoted by image, is defined as

      (1.3) image

      Such a system is called a Kronecker symbol or Kronecker delta.

      For example, image, by summation convention is expressed as

image

      We shall now consider some properties of this system.

      (1.4) image

      Property 1.4.2. From the summation convention, we get

image

      Similarly, δii = δii = n

      Property 1.4.3. From the definition of δi j, taken as an element of unit matrix I, we have

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