Linear transformations & determinants

transformation matrix

Here is one of the most satisfying facts in the subject: once you fix a basis, every linear transformation on finitely many dimensions IS just a matrix. The abstract map and a concrete grid of numbers become the same thing.

The trick for building it is wonderfully simple. Watch where each basis vector lands, and write those landing spots as the columns of the matrix. To then apply the transformation to any vector, you just multiply that matrix by the vector. The columns are the answer key, and matrix multiplication fills in everything in between.

This is why linear algebra is so practical. Instead of reasoning about a mysterious function, you store a small array of numbers, and a computer multiplies. Whatever the transformation does to space is fully captured by where it sends the basis vectors.

90-deg rotation: e1=(1,0)->(0,1), e2=(0,1)->(-1,0), so A = [[0,-1],[1,0]]

Track where the two basis vectors land; those become the columns of A.

Change the basis and the same transformation gets a different-looking matrix. The map is fixed; its number-grid depends on the coordinate system you chose.

Also called
matrix of a linear transformationmatrix representation变换矩阵线性变换的矩阵變換矩陣線性變換的矩陣