SimuVeda

Mathematics · Simulator 044

Linear Transformations

A 2×2 matrix moves every point of the plane. Edit its four entries, or pick a preset, and watch the grid stretch, rotate, shear or flip. The determinant tells you how areas change, and the eigenvectors are the directions that only get stretched.

How the model works

The matrix M = [[a, b], [c, d]] sends a point (x, y) to (ax + by, cx + dy). Its columns are where the basis vectors land: î = (1, 0) goes to (a, c), and ĵ = (0, 1) goes to (b, d). Everything else follows, because grid lines stay straight, parallel and evenly spaced.

  • Determinant ad − bc: the factor by which areas scale. Negative means orientation flips (a mirror image); zero means the plane collapses onto a line.
  • Eigenvectors satisfy Mv = λv: they keep their direction and scale by λ. From λ² − (a + d)λ + (ad − bc) = 0. Rotations have no real eigenvectors.

Press Play to animate smoothly from the identity matrix to M (linear interpolation of entries), which shows how each kind of transformation “moves”.

The animation interpolates matrix entries, which is not the same as rotating by a growing angle; a true rotation animation would pass through rotation matrices.

Guided experiments

  1. Rotation by 90°. M = [[0, −1], [1, 0]]. Prediction: determinant 1 (area kept), no real eigenvectors, the F shape turns a quarter-turn anticlockwise.
  2. Shear. M = [[1, 1], [0, 1]]. Prediction: area unchanged (det 1). The x-axis is the only eigen-direction (λ = 1); squares become parallelograms.
  3. Collapse. M = [[1, 2], [2, 4]]. Prediction: det 0. The whole plane is squashed onto the line y = 2x, so information is lost and there is no inverse.

Challenge

Find a matrix that doubles lengths along the line y = x and leaves the line y = −x unchanged. What is its determinant?

Reveal the explanation

Eigenvalues 2 (along (1, 1)) and 1 (along (1, −1)) give M = [[1.5, 0.5], [0.5, 1.5]], with det = 2.25 − 0.25 = 2, the product of the eigenvalues. Enter it and check the eigenvector readout.

References

  • OpenStax, Precalculus 2e, §9.5 “Matrices and Matrix Operations”; MIT OCW 18.06 Linear Algebra, lectures 21–22.
  • Strang, Introduction to Linear Algebra, ch. 6.