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Why does row rank equal column rank?

5How unique are solutions of a linear system of equations?

Let’s look at the following linear systems of equations in three variables x1,x2,x3Rx_1,x_2,x_3\in\R:

System 1: Consider

It has the unique solution x1=1,x2=2,x3=10x_1=1, x_2=2, x_3 = -10.

System 2: Consider

For each x1Rx_1 \in \R it has the solution x2=53x1,x3=21+11x1x_2 = 5-3x_1, x_3 = -21+11x_1. Hence there are infinitely many solutions.

System 3: Consider

Here we can choose x2=53x1x_2=5-3x_1 and get a solution for arbitrary x1,x3Rx_1, x_3\in\R.

If there are more redundant rows then the linear system of equations has more solutions.

  • System 1: unique solution; represents a point in R3\R^3

  • System 2: solution for any x1x_1; solutions represent a straight line in R3\R^3

  • System 3: solution for any choice of x1x_1 and x3x_3; represents a plane in R3\R^3

If we have more than one solution, what do they have in common?

Let xx’ and x’’x’’ be two solutions of a linear system of equations Ax=yAx=y. What is the difference between the two solutions xx’ and x’’x’’? We apply AA to the difference xx’’x’-x’’: A(xx’’)=AxAx’’=yy=0A(x’-x’’) = Ax’ - Ax’’ = y-y = 0.

The more solutions to the system Ax=yAx=y there are, the more vectors we can find that get mapped to zero. Hence the “amount” of x with Ax=0Ax = 0 is a measure for the uniqueness of the solution Ax=yAx = y for any yy. For that reason, we give it a name: The kernel of AA. We write it as

The bigger the kernel the more solutions exist. If ker(A)=0\ker(A)=0 the solution is unique.


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