Basis and Dimension of Solution Space

In summary, the homework statement is trying to find a basis for the solution space of the homogenous system of equations. However, the second row of the matrix doesn't have a 1 in the x2 position, and this has thrown the student off. They are trying to parametrize the system, but they are not sure how to do so. After looking at the equations, it seems that if the x4 component is zero, then the first equation is x_1+ x_2= 0, and the second equation is x_5= -x_3.
  • #1
B18
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Homework Statement


Find a basis for and the dimension of the solution space of the homogenous system of equations.

2x1+2x2-x3+x5=0
-x1-x2+2x3-3x4+x5=0
x1+x2-2x3-x5=0
x3+x4+x5=0

Homework Equations

The Attempt at a Solution


I reduced the vector reduced row echelon form. However the second row doesn't have a 1 in the x2 position which has thrown me off. Do I parametrize here like I did? Something just doesn't seem correct.
Here is my work thus far:
 
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  • #2
ImageUploadedByPhysics Forums1426211853.335591.jpg
 
  • #3
Based on your final matrix, which I didn't check, you have
x1 = -x2 - x5
x2 = x2
x3 = -x5
x4 = 0
x5 = x5
If you stare at this long enough you should see that the above represents all possible linear combinations of two vectors.

BTW, it's confusing to have that last column of zeroes in your matrix. It would be better to eliminate that column since it can't possibly change.
 
  • #4
Well I got the following equations from the matrix:
x1+x2+x4=0
x3+x5=0
x4=0
Not really sure how I can parametrize these to solve for the basis of the solution space.
 
  • #5
If those are correct, since [itex]x_4= 0[/itex], your first equation is [itex]x_1+ x_2= 0[/itex] which means that [itex]x_2= -x_1[/itex]. And, of course, your second equation s the same as [itex]x_5= -x_3[/itex]. That means we can write [itex]<x_1, x_2, x_3, x_4, x_5>= <x_1, -x_1, x_3, 0, -x_3>= <x_1, -x_1, 0, 0, 0>+ <0, 0, x_3, 0, -x_3>= x_1<1, -1, 0, 0, 0>+ x_3<0, 0, 1, 0, -1>[/itex]. Now do you see what basis vectors for the solution space are?
 
  • #6
This is the solution I got. However I am a bit confused on my basis. How can the x4 slot both have zeros in the basis vectors and still span the space? Did I make a mistake along the way?
Thanks for the help everyone.

ImageUploadedByPhysics Forums1426716928.795578.jpg
 
  • #7
B18 said:
This is the solution I got. However I am a bit confused on my basis. How can the x4 slot both have zeros in the basis vectors and still span the space? Did I make a mistake along the way?
Thanks for the help everyone.

View attachment 80599
There's no reason that the x4 component shouldn't be zero. You can do a quick check by multiplying each of the two vectors by your matrix. If you don't get a zero vector for each product, that's a sign that you did something wrong.
 
  • #8
B18 said:
This is the solution I got. However I am a bit confused on my basis. How can the x4 slot both have zeros in the basis vectors and still span the space? Did I make a mistake along the way?
Thanks for the help everyone.

View attachment 80599
Have you forgotten what it is spanning? Not the original space- these vectors are to span the solution set for these equations- and as you have calculated x4 is 0!
 
  • #9
Both of your replies helped me understand what was going on here much better. Thank you.
 

FAQ: Basis and Dimension of Solution Space

1. What is the "basis" of a solution space?

The basis of a solution space refers to a set of vectors that can be used to represent all possible solutions to a system of linear equations. These vectors are linearly independent and span the entire solution space.

2. How is the basis related to the dimension of a solution space?

The dimension of a solution space is equal to the number of vectors in its basis. This means that the dimension represents the minimum number of linearly independent vectors needed to span the entire solution space.

3. Can the basis of a solution space change?

Yes, the basis of a solution space can change depending on the system of linear equations. A different set of linearly independent vectors may be needed to represent the solutions to a different system of equations.

4. How do you find the basis of a solution space?

To find the basis of a solution space, you can use the row reduction method to solve a system of linear equations and then identify the linearly independent rows in the resulting matrix. These rows will form the basis of the solution space.

5. Why is understanding the basis and dimension of a solution space important?

Understanding the basis and dimension of a solution space is important in linear algebra as it allows us to analyze the properties of a system of linear equations and determine the number of solutions it has. It also helps us to find a set of basis vectors that can be used to represent all possible solutions to the system.

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