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Mathematics · Ch 2 — Matrices

Elementary Transformation

2.1

Elementary Transformation

The six elementary transformations. An elementary transformation of a matrix is one of six operations -- three acting on rows, and three (their mirror images) acting on columns:

  1. Interchange of any two rows or any two columns. If the ii-th row and the jj-th row of a matrix are interchanged, the original matrix is transformed into a new matrix. This is written Ri↔RjR_i \leftrightarrow R_j (or RijR_{ij} for short); the column version is Ci↔CjC_i \leftrightarrow C_j (or CijC_{ij}). For example, if A=[1234]A=\begin{bmatrix}1&2\\3&4\end{bmatrix} then R1↔R2R_1\leftrightarrow R_2 gives the new matrix [3412]\begin{bmatrix}3&4\\1&2\end{bmatrix}, and C1↔C2C_1\leftrightarrow C_2 gives the new matrix [2143]\begin{bmatrix}2&1\\4&3\end{bmatrix}. Note carefully that A≠[3412]A \neq \begin{bmatrix}3&4\\1&2\end{bmatrix} and A≠[2143]A \neq \begin{bmatrix}2&1\\4&3\end{bmatrix} -- the transformed matrix is a genuinely different matrix, not equal to AA. Instead the relationship is written using the symbol ∼\sim (read "is equivalent to"): A∼[3412]A \sim \begin{bmatrix}3&4\\1&2\end{bmatrix} and A∼[2143]A \sim \begin{bmatrix}2&1\\4&3\end{bmatrix}.
  2. Multiplication of the elements of any row or column by a non-zero scalar. If kk is a non-zero scalar, multiplying every element of row RiR_i by kk is written Ri→kRiR_i \to kR_i (and Cl→kClC_l \to kC_l for a column). For example, if A=[0234]A = \begin{bmatrix}0&2\\3&4\end{bmatrix} then R2→4R2R_2 \to 4R_2 gives A∼[021216]A \sim \begin{bmatrix}0&2\\12&16\end{bmatrix}; and C1→−3C1C_1 \to -3C_1 on the same AA gives A∼[02−94]A \sim \begin{bmatrix}0&2\\-9&4\end{bmatrix}. In both cases the result is only equivalent to AA, never equal to it.
  3. Adding the scalar multiples of all the elements of any row (column) to the corresponding elements of any other row (column). If kk is a non-zero scalar, adding the kk-multiples of the elements of RiR_i (or CiC_i) to the elements of RjR_j (or CjC_j) is written Rj→Rj+kRiR_j \to R_j + kR_i, Cj→Cj+kCiC_j \to C_j + kC_i. For example, if A=[−1425]A = \begin{bmatrix}-1&4\\2&5\end{bmatrix} and k=2k=2, then R1→R1+2R2R_1 \to R_1 + 2R_2 gives A∼[−1+2(2)4+2(5)25]=[31425]A \sim \begin{bmatrix}-1+2(2)&4+2(5)\\2&5\end{bmatrix} = \begin{bmatrix}3&14\\2&5\end{bmatrix}. Two bookkeeping notes on transformation (c):
  1. After Rj→Rj+kRiR_j \to R_j + kR_i, the row RiR_i that supplied the multiple is left completely unchanged in the new matrix -- only RjR_j is overwritten. The same holds for columns: after Cj→Cj+kCiC_j \to C_j + kC_i, column CiC_i is unchanged.
  2. After any elementary transformation, the matrix obtained is said to be equivalent to the original matrix (never equal, except in the trivial case where the transformation happens to have no effect). …
Misc 2.1aWorked Examples 1-3 -- applying single and chained row/column transformations

Worked out. Three short worked examples applying named transformations to small matrices one after another: Example 1 swaps two rows of a 2x2 matrix (R1↔R2R_1 \leftrightarrow R_2); Example 2 adds a scalar multiple of column 3 to column 1 of a 2x3 matrix (C1→C1+2C3C_1 \to C_1+2C_3); Example 3 chains a row interchange followed by a column addition on a 2x3 matrix, showing that the second transformation is applied to the matrix already produced by the first, not to the original matrix. …