Scalar multiplication scales every entry of a matrix by the same number. Type a value for k above and press k·A. Negatives, decimals and fractions all work.
What scaling does
Unlike matrix multiplication, this operation has no shape requirement at all: any matrix can be multiplied by any number, and the dimensions are unchanged. As a transformation it stretches space uniformly in every direction by a factor of k, and a negative k adds a reflection through the origin.
One consequence surprises almost everyone the first time. Scaling a matrix does not scale its determinant by k. For an n×n matrix, det(k·A) = kⁿ · det(A), because each of the n rows is being scaled and the determinant is multiplied once for each. Doubling a 3×3 matrix multiplies its determinant by eight. The trace, being a plain sum, behaves as expected: tr(k·A) = k · tr(A). And the rank is untouched for any non-zero k — scaling cannot make dependent rows independent.
Worked example
| 1 | 2 |
| 0 | 4 |
| 3 | 6 |
| 0 | 12 |
Every entry is tripled, zeros included. The determinant went from 4 to 36 — a factor of 3² = 9, not 3, exactly as the rule predicts for a 2×2.
Common mistakes
- Scaling only the diagonal. k·A multiplies every entry. Scaling the diagonal alone is a different operation entirely.
- Assuming det(k·A) = k·det(A). The exponent is the size of the matrix: det(k·A) = kⁿ·det(A).
- Confusing k·A with A + k. Adding a number to a matrix is undefined; scaling by it is not.
- Multiplying by zero and expecting the identity. 0·A is the zero matrix. The identity is what you get from A⁰.