Linear Transformations
- Interpret a 2×2 matrix as a transformation of the plane
- Identify the matrices for common reflections
- Explain the effect of the identity matrix on a vector
Matrices move the plane
Multiplying a 2×2 matrix by a column vector produces a new vector — the matrix acts as a linear transformation, sending each point of the plane to a new location. Rotations, reflections, stretches, and shears can all be encoded as a single matrix. The columns of the matrix tell you where the basis vectors ⟨1, 0⟩ and ⟨0, 1⟩ land.
Reflections and the identity
A reflection across the x-axis keeps x and negates y, encoded by [[1, 0], [0, −1]]. A reflection across the y-axis negates x instead: [[−1, 0], [0, 1]]. The identity matrix [[1, 0], [0, 1]] changes nothing — multiplying it by any vector returns that same vector, just as multiplying a number by 1 leaves it unchanged.
Apply the matrix [[1, 0], [0, −1]] to the vector ⟨3, 5⟩ and describe the transformation.
- 1.Multiply: the new x is (1)(3) + (0)(5) = 3.
- 2.The new y is (0)(3) + (−1)(5) = −5.
- 3.The image is ⟨3, −5⟩ — the x-coordinate is unchanged and the y-coordinate is negated.
- 4.Negating only y is a reflection across the x-axis.
Which matrix reflects a point across the x-axis (keeping x, negating y)?
Read a transformation matrix by its columns: the first column is the image of ⟨1, 0⟩ and the second is the image of ⟨0, 1⟩. Knowing where the two basis vectors go pins down the whole transformation.
Applying the 2×2 identity matrix [[1, 0], [0, 1]] to a vector produces:
To find the matrix of a described transformation, track where ⟨1, 0⟩ and ⟨0, 1⟩ land and place those images as columns. This construction handles rotations, reflections, and stretches uniformly on the AP exam.
Answer the 2 checkpoints as you read.
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