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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image

       Property 1.4.4.

      (1.6) image

      (1.7) image

image

      Also, by definition, image

      In particular, when i = k, we get image

      Remark 1.4.1. If we multiply xk by image, we simply replace index k of xk with index i and for this reason, image is called a substitution factor.

      Example 1.4.1. Evaluate (a) image and (b) image where the indices take all values from 1 to n.

      (1.8a) image

      (1.8b) image

      (b) image by 1.8b

      Example 1.4.2. If xi and yi are independent coordinates of a point, it is shown that

image

      Since xj is independent of, image when j i

      Let us consider n linear equations such that

      where x1, x2, …. xn are n unknown variables.

      Let us consider:

      For the expansion of det |ai j| in terms of cofactors we have

      where a = |ai j| and the cofactor of ai j is Ai j.

      We can derive Cramer’s Rule for the solution of the system of n linear equations:

image

      From here, we can easily get

image

      Solution: By expansion of determinants, we have:

image

      Which can be written as a1jA1j = a a1jA2j = 0 and a1jA3j = 0 [we know aijAij = a].

      Similarly, we have

image

      Using Kronecker Delta Notation, these can be combined into a single equation:

image

      All nine of these equations can be combined into image.

      It is known that if the range of the indices of a system of second order are from 1 to n, the number of components is n2. Systems of second order are organized into three types: ai j, ai j, image and their matrices, image

image

      each of which is an n × n matrix.

      We shall now establish the following results:

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