Uniqueness of reduced row echelon form 2026-10-18
Here is a short proof that uses only the row space. For a vector subspace , let be the dimension of its projection map onto the first coordinates, with . In any reduced row echelon form with row space , counts the pivot columns among those first columns: later-pivot rows project to zero, while earlier-pivot rows remain linearly independent. Thus the positions where determine all pivot positions from alone.
If those positions are , the map sending to is an isomorphism : the reduced nonzero rows map to the standard basis. Its th row is therefore the unique vector of with pivot-coordinate values equal to the th standard basis vector. Any other reduced row echelon form with that row space has identical nonzero rows in identical order. At a fixed matrix size, the remaining rows must be zero. Together with existence by Gaussian elimination, this proves uniqueness.
Unit vector Created 2026-09-24 Updated 2026-10-14
A unit vector is a vector of norm one in a normed vector space. For a nonzero vector , vector normalization produces one by dividing by . In a real Euclidean space, this keeps the direction and removes the magnitude. The zero vector cannot be normalized because its norm is zero.
For with Euclidean norm , the corresponding unit vector isThe Euclidean vector can therefore be reconstructed as : size and direction are distinct pieces of information. The standard basis vectors are familiar unit vectors, but a unit vector need not point along a coordinate axis.
Normalization keeps direction and places the endpoint on the unit circle
. The original Euclidean vector has magnitude . Its vector normalization lies on the unit circle. The enlarged right panel also shows its negative, which has the same Euclidean norm and the opposite direction. Details.