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Theorem - Uniqueness of the Reduced Echelon Form

Each matrix is row equivalent to one and only one reduced echelon matrix.

Proof:

Let A A be some matrix, we want to prove that every matrix is row equivalent to exactly one reduced echelon matrix.

Let us assume that a matrix A A is row equivalent to more than one reduced echelon matrix. Specifically, suppose there exist two reduced echelon matrices B B and C C such that both are row equivalent to A A .

Since both B B and C C are row equivalent to A A , there exist sequences of row operations that transform A A into B B and A A into C C .

Since row operations preserve the pivot positions, the pivot positions in B B must be the same as those in A A . Similarly, the pivot positions in C C must also match those in A A .

Since both B B and C C are in reduced echelon form and have the same pivot positions, they must be identical. This contradicts our assumption that B B and C C are distinct reduced echelon matrices. Therefore, the assumption that a matrix can be row equivalent to more than one reduced echelon matrix is false. It follows that every matrix is row equivalent to exactly one reduced echelon matrix.

Theorem - Existence and Uniqueness Theorem

A linear system is consistent if and only if the rightmost column of the augmented matrix is not a pivot column.

Important:

For this proof, since it is an "if and only if," we need to prove both the forward phase (denoted as ⇒\Rightarrow) and the backward phase (denoted as ⇐\Leftarrow) of the theorem.

Lets first do the forward phase of the proof: A linear system is consistent if the rightmost column of the augmented matrix is not a pivot column.

Proof ⇒\Rightarrow (By contradiction):

Lets assume that a linear system is consistent if the rightmost column of the augmented matrix is a pivot column. Now, let AA be the augmented matrix for this system, and let AA be in reduced echelon form. We can denote the columns of AA as [x1x2x3…xn∣b][x_{1} x_{2} x_{3} \dots x_n \mid b], where bb is the augmented column. Recall that all values above and below a pivot position are zeroed out, and since we have a pivot position in our augmented column, we have a row in the form [0 0 … 0∣b][0\, 0\, \dots\, 0 \mid b], where bb is the pivot position.

Looking at this system as an equation, we get 0x1+0x2+0x3+⋯+0xn=b0x_{1} + 0x_{2} + 0x_{3} + \dots + 0x_{n} = b, where bb is non-zero (by the definition of pivot position). Since bb is non-zero, we have 0+0+0+⋯+0=b0 + 0 + 0 + \dots + 0 = b, which is an inconsistent system since 0+0+⋯+00 + 0 + \dots + 0 cannot equal a non-zero number. This is a contradiction to our original assumption that a linear system is consistent if the rightmost column of the augmented matrix is a pivot column.

Now, lets do the backward phase: If the rightmost column of the augmented matrix is not a pivot column, then the linear system is consistent.

Proof ⇐\Leftarrow (By contradiction):

Assume that if the rightmost column of the augmented matrix is not a pivot column, then the linear system is inconsistent. In reduced echelon form, this implies that there will never be a row in the form [0 0 … 0∣b][0\, 0\, \dots\, 0 \mid b] with b≠0b \neq 0, because we originally stated that the rightmost column of the augmented matrix is not a pivot column. Since no contradictions arise from this, the system must be consistent. Therefore, if the rightmost column is not a pivot column, then the system is consistent.

Theorem

A nonzero matrix can be row reduced (via elementary row operations) into an infinite number of echelon forms

Proof:

Suppose we have a non-zero matrix A, let U be an echelon form of A and let c,d∈Rc,d \in \mathbb{R} be non-zero scalars such that c≠dc \ne d. Let U′U' be obtained by mutiplying a pivot row in UU by a non-zero scalar cc and let U′′U'' be obtained by multiplying a pivot row in UU by some scalar dd. Since the scalars cc and dd can never be equal then the matrix U′≠U′′U' \ne U''. Since we are scaling by different numbers we can generate an infinite number of echelon forms of A.