General & First-year

Linear Algebra Lab

A matrix is just a recipe for where space goes. Drag the four entries and the whole grid shears, rotates, stretches and flips: the basis vectors î → (a, c) and ĵ → (b, d) move, the unit square becomes a parallelogram whose area is the determinant (negative means orientation flipped), and the dashed lines are the eigenvector directions — the special lines the transform only stretches and never rotates. When the matrix is a pure rotation there are no real eigenvectors, and the readout says so.

0.75

Determinant

2.00

Trace

1.50

λ₁

0.50

λ₂

The method, with your numbers

Determinant, trace, eigenvalues

  1. 1

    Read off where the basis vectors land

    î → (a, c) ĵ → (b, d)

    î → (1, 0.5) ĵ → (0.5, 1)

    The columns of the matrix ARE the landed basis vectors — that's how to read any matrix.

  2. 2

    Determinant — the area scale factor

    det = a·d − b·c

    det = 1·1 − 0.5·0.5 = 0.75

    Areas scale by |det| = 0.75× — watch the shaded parallelogram grow or shrink.

  3. 3

    Trace — sum of the diagonal

    tr = a + d

    tr = 1 + 1 = 2

    Quick self-check for later: the trace always equals λ₁ + λ₂.

  4. 4

    Discriminant of the characteristic equation

    Δ = tr² − 4·det

    Δ = 2² − 4·0.75 = 1

    Δ ≥ 0 means real eigenvalues (directions that only stretch); Δ < 0 means the map rotates every vector.

  5. 5

    Eigenvalues — the pure stretch factors

    λ₁,₂ = (tr ± √Δ) / 2

    λ₁ = (2 + 1) / 2 = 1.5 λ₂ = (2 − 1) / 2 = 0.5

    The dashed lines are the eigenvector directions — vectors on them only stretch by λ, never rotate. Check: λ₁·λ₂ = det.

Drag any control above — every number here recalculates. Want this method for any problem? Step Sheets →

a1
b0.5
c0.5
d1

The matrix is just where the basis vectors land: î → (a, c), ĵ → (b, d). The determinant is how much area is stretched (negative = flipped); the dashed lines are eigenvector directions — the ones the transform only stretches, never rotates.

How to use this simulation

A matrix is just a recipe for where space goes. Drag the four entries and the whole grid shears, rotates, stretches and flips: the basis vectors î → (a, c) and ĵ → (b, d) move, the unit square becomes a parallelogram whose area is the determinant (negative means orientation flipped), and the dashed lines are the eigenvector directions — the special lines the transform only stretches and never rotates. When the matrix is a pure rotation there are no real eigenvectors, and the readout says so.

Everything runs in your browser — no sign-up, no download. Change a value and the result updates instantly, so you can build a feel for how each input shapes the outcome. It pairs with Crameleon's practice exams and step sheets when you want to go from intuition to working the problems.