What Is the Solution Space for Ax=b in Linear Algebra?

In summary: That is, the solution set consist of a "translation" of a subspace. (That is, it is the coset of a subspace.)In summary, when studying linear algebra and encountering a system Ax=b, there are three fundamental subspaces of A: the null space (all solutions x of Ax=0), the column or domain space (all possible b for Ax=b), and the row space (all possible linear combinations of the rows of A). The "solution space" for a given b, such that Ax=b, is only a subspace when b = 0, otherwise it is a linear manifold that can be represented as a translation of a subspace.
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When studying linear algebra when encountering a system Ax=b, I always read of the fundamental subspaces of A: N (the null space, all solutions x of Ax=0), the column or domain space of A: (the space spanned by the columns of A, or in other words, all possible b for Ax=b), the row space (the space spanned by the rows of A. I have a harder time wrapping my head around this one).


But I had another question. What about all the possible vectors x for a given b, such that Ax=b ? I get that this wouldn't always work because say, some systems are inconsistent and have no solutions so it would be empty in this case. It seems like this wouldn't necessarily be a subspace because it wouldn't necessarily be closed under addition (just because x is a solution to Ax=b doesn't mean A(2x)=b is a solution). But sometimes it would be a subspace. Because for example, the nullspace would just be the special case where b = 0, the 0 vector, and we know the nullspace is a subspace. Is this "solution space" given special importance? If so what's it called? (I keep calling it a solution space and I just don't know what the proper name of it is)
 
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dumbQuestion said:
When studying linear algebra when encountering a system Ax=b, I always read of the fundamental subspaces of A: N (the null space, all solutions x of Ax=0), the column or domain space of A: (the space spanned by the columns of A, or in other words, all possible b for Ax=b), the row space (the space spanned by the rows of A. I have a harder time wrapping my head around this one).


But I had another question. What about all the possible vectors x for a given b, such that Ax=b ?
If Ax= b, then A(x+ v)= Ax+ Av= b for any v in the null space of A.

I get that this wouldn't always work because say, some systems are inconsistent and have no solutions so it would be empty in this case. It seems like this wouldn't necessarily be a subspace because it wouldn't necessarily be closed under addition (just because x is a solution to Ax=b doesn't mean A(2x)=b is a solution). But sometimes it would be a subspace. Because for example, the nullspace would just be the special case where b = 0, the 0 vector, and we know the nullspace is a subspace. Is this "solution space" given special importance? If so what's it called? (I keep calling it a solution space and I just don't know what the proper name of it is)
The only time a "solution space" (which is, in fact, a standard name for it) is a subspace is when b= 0. In the case that [itex]b\ne 0[/itex], the "solution set" is a "linear manifold"- something like a line or plane in R3 that does NOTcontain the origin. It can be shown that if v is a vector satisfying Ax= b, then any solution of Ax= b can be written as v plus a vector satisfying Ax= 0. Since Ax= 0 is a subspace, it contains a basis so any solution to Ax= 0 can be written as a linear combination of basis vectors. And so any solution of Ax= b can be written as such linear combination of basis vectors plus v.
 

Related to What Is the Solution Space for Ax=b in Linear Algebra?

What are the fundamental subspaces of A?

The fundamental subspaces of A refer to a set of subspaces that are essential for understanding the properties and behavior of a matrix A. These subspaces include the column space, null space, row space, and left null space.

What is the column space of A?

The column space of A is the set of all possible linear combinations of the columns of matrix A. It represents the span of the columns and is also known as the range of A. The dimension of the column space is equal to the number of linearly independent columns in A.

What is the null space of A?

The null space of A, also known as the kernel of A, is the set of all vectors that when multiplied by A result in a zero vector. In other words, it is the set of all solutions to the homogeneous system of linear equations Ax=0. The dimension of the null space is equal to the number of linearly independent columns in A.

What is the row space of A?

The row space of A is the set of all possible linear combinations of the rows of matrix A. It represents the span of the rows and is equivalent to the column space of the transpose of A. The dimension of the row space is equal to the number of linearly independent rows in A.

What is the left null space of A?

The left null space of A is the set of all vectors that when multiplied by the transpose of A result in a zero vector. In other words, it is the set of all solutions to the homogeneous system of linear equations xA=0. The dimension of the left null space is equal to the number of linearly independent rows in A.

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