Linear transformations & determinants

composition of transformations

Composition just means doing one transformation and then feeding its output into another: first rotate, then stretch. The combined effect is itself a single linear transformation, so a whole chain of steps can be bundled into one map.

And here is the punchline of the entire subject: composing transformations corresponds exactly to multiplying their matrices. If S has matrix A and T has matrix B, then doing T first and then S has matrix A*B. The order reads right to left, matching how the vector flows through B before reaching A. This is the real reason matrix multiplication is defined the way it is, with its peculiar row-times-column rule.

It also explains why matrix multiplication is usually not commutative: A*B and B*A need not agree. Rotating then reflecting is generally not the same as reflecting then rotating, and the matrices honestly record that difference in order.

Apply B then A to vector v: A*(B*v) = (A*B)*v. Generally A*B != B*A.

Chaining two maps equals multiplying their matrices; swapping the order usually changes the result.

Mind the order. The matrix written rightmost acts on the vector first. So A*B means: apply B, then A. It feels backward at first, but it lines up with how functions are written.

Also called
composing mapschaining transformations变换的复合映射的复合變換的複合映射的複合