Solution x spanning columns of A

  • Thread starter fackert
  • Start date
  • Tags
    Columns
In summary, the conversation discusses whether a specific solution to the matrix equation Ax=0 is in the set spanned by the columns of A. It is determined that this is not the case, as the columns of A represent a subspace of Rm, while the solution x must be in Rn. This solution is considered the nullspace of A, and is in the vector space U, while the columns of A are in the vector space V.
  • #1
fackert
3
0
This is a really odd question to me. Usually we talk about b (in Ax=b) spanning the columns of A but here its talking about x spanning A.

If x=<-3,4,8> (this is a vertical 3x1 matrix) is a solution to Ax=0, then is x in the set spanned by the columns of A?

I'm pretty sure it is no, but i can't explain why? (briefly). And i don't know how to change the statement so it would be true.
 
Physics news on Phys.org
  • #2
One obvious point- if A is an m by n matrix (m rows, n columns), then A maps an Rn to Rm. In order that we be able to multiply A times x, x must have n rows and so must be in Rn. But the columns each have m elements, one for each of the n rows, and so span a subspace of Rm. Members of the "column space" are vectors in the image of A, vectors of the form y= Ax for some x, not x itself.
 
  • #3
Actually if its a solution to the matrix equation Ax=0 that's considered a nullspace.
 
  • #4
Thanks, Halo31. fackert, if A maps vector space U to a subspace of vector Space V, then all solutions of Ax= 0, the "null space" of A, are in U. The columns of A, thought of as vectors (the "column space" of A), are in V. Of course, any x that A can be applied to must be in U, not V.
 
  • #5


I would first clarify the terminology used in this question. When we say "x spanning columns of A", it typically means that the vector x is a linear combination of the columns of A. In other words, x can be written as a linear combination of the columns of A, with the coefficients of the linear combination being the entries of x.

In this context, it is not correct to say that x is spanning the columns of A. Rather, the columns of A are spanning the vector space that x belongs to. Therefore, the statement "x spanning A" is not accurate.

Moving on to the question at hand, if x is a solution to Ax=0, then it means that x is in the null space of A. The null space of A is the set of all vectors that when multiplied by A, result in the zero vector. This means that x is orthogonal to all the columns of A.

Since x is orthogonal to the columns of A, it cannot be written as a linear combination of the columns of A. Therefore, x is not in the set spanned by the columns of A.

To change the statement to make it true, we could say "If x is a solution to Ax=0, then x is in the null space of A." This statement accurately reflects the relationship between x and the columns of A.
 

Related to Solution x spanning columns of A

What does it mean for a solution x to span columns of A?

When a solution x spans columns of A, it means that the values in x can be multiplied by the corresponding columns of A to produce a linear combination that equals the given solution. In other words, the columns of A are linearly dependent on the solution x.

How can I determine if a solution x spans columns of A?

To determine if a solution x spans columns of A, you can perform row reduction on the augmented matrix [A|x]. If the resulting matrix has a pivot in every column of A, then the solution x spans the columns of A. If there is a column in A without a pivot, then the solution x does not span the columns of A.

What are some real-world applications of solutions spanning columns of A?

Solutions spanning columns of A have many applications in science and engineering. For example, they can be used to model chemical reactions, analyze economic systems, and solve optimization problems in computer science.

Can a solution x span columns of A if it is not unique?

Yes, a solution x can span columns of A even if it is not unique. In fact, if there are infinitely many solutions to the system of equations represented by A, then any of those solutions can be used to span the columns of A.

What is the relationship between solutions spanning columns of A and the rank of A?

The rank of A is equal to the number of columns of A that are linearly independent. If a solution x spans all of the columns of A, then it is also a linear combination of all of the linearly independent columns of A. Therefore, the rank of A must be at least equal to the number of columns that x spans.

Similar threads

  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
7
Views
10K
  • Linear and Abstract Algebra
Replies
9
Views
4K
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
883
  • Linear and Abstract Algebra
Replies
6
Views
1K
  • Linear and Abstract Algebra
Replies
1
Views
1K
  • Linear and Abstract Algebra
Replies
2
Views
2K
  • Calculus and Beyond Homework Help
Replies
15
Views
2K
  • Calculus and Beyond Homework Help
Replies
3
Views
3K
Back
Top