Proving that the solution of Ax=0 is a vector space

In summary, the conversation discusses the existence of the 0 vector in a vector space and the property of closure under vector addition and scalar multiplication. It is mentioned that the trivial solution is an indication of the 0 vector's existence and it is not the only solution. It is also discussed how to prove this property using linear transformations and the importance of understanding the properties of linear transformations. Additionally, it is clarified that u and v are not vector columns of the matrix A, but rather any vectors that can be multiplied by A.
  • #1
mohdhm
42
0
Here is my attempt to answer this guys, i'd really appreciate any corrections.


a vector space has the 0 vector
the vector space is closed under vector addition and scalar multiplication (AKA for every vector u, v in the subspace, there exists a vector u + v in the subspace)

Here we go.

The trivial solution is an indication that the 0 vector exists. I don't know how to prove that one, unless i write out the linear combination and set all the scalars to 0

The trivial solution is not the only solution: free variables and possibly 0 columns or rows exist. (also an indication that the 0 vector exists).

so if we row reduce the matrix to row echalon form and solve for [x1 ... xn] by moving the free variables to the right side of the homogenius equation then that would be the same as the additive property i mentioned above right? but how would i even know that u or v are in the vector space to begin with ? (remindeR: u and v are vector columns of the matrix A.)
 
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  • #2
You don't have to solve anything. If u and v are in the null space N={x:Ax=0} that just means Au=0 and Av=0. To show it's closed under vector addition, for example, you just need to show (u+v) is in N. That is, show A(u+v)=0. Can you do that?
 
  • #3
how can you show that when you are not given u or v, unless its super simple and just happens to be worth a lot of marks.
 
  • #4
mohdhm said:
Here is my attempt to answer this guys, i'd really appreciate any corrections.


a vector space has the 0 vector
the vector space is closed under vector addition and scalar multiplication (AKA for every vector u, v in the subspace, there exists a vector u + v in the subspace)

Here we go.

The trivial solution is an indication that the 0 vector exists. I don't know how to prove that one, unless i write out the linear combination and set all the scalars to 0
No, you can't set the scalars to 0, they are given in "A". What you want to do is the other way around: show that the 0 vector satisfies the equation A0= 0. Since A is a linear transformation, what do you know about linear transformations? In particular, what is A0?
(Think about A(v+ 0)= Av by definition of "0" and use the distributive law.)

The trivial solution is not the only solution: free variables and possibly 0 columns or rows exist. (also an indication that the 0 vector exists).

so if we row reduce the matrix to row echalon form and solve for [x1 ... xn] by moving the free variables to the right side of the homogenius equation then that would be the same as the additive property i mentioned above right? but how would i even know that u or v are in the vector space to begin with ? (remindeR: u and v are vector columns of the matrix A.)
You want to show that if u and v are in the space, (that is, they satisfy Au= 0, Av= 0) then au+ bv is also in the space, for any numbers a and b (What is A(au+ bv)?).

DON'T think about "row echelon form" or anything like that. Just use the properties of linear transformations (matrix multiplication) themselves: A(u+ v)= Au+ Av and A(bu)= b(Au).

Finally, u and v are not "vector columns of the matrix A". They are any vectors of the correct dimension to be multiplied by A
 
  • #5
thanks mate
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of elements, called vectors, and a set of operations, such as addition and scalar multiplication, that can be performed on these vectors. It is a fundamental concept in linear algebra and is used to study geometric objects such as lines, planes, and higher-dimensional spaces.

2. What is the solution of Ax=0?

The solution of Ax=0 is the set of all vectors that satisfy the equation when multiplied by the matrix A. In other words, it is the set of vectors that, when multiplied by A, result in the zero vector. This solution set is also known as the null space or kernel of A.

3. How do you prove that the solution of Ax=0 is a vector space?

To prove that the solution of Ax=0 is a vector space, we must show that it satisfies the 10 axioms, or properties, of a vector space. These include closure under addition and scalar multiplication, existence of a zero vector and additive inverse, and distributivity and associativity properties. By demonstrating that the solution set satisfies these axioms, we can prove that it is a vector space.

4. Why is it important to prove that the solution of Ax=0 is a vector space?

Proving that the solution of Ax=0 is a vector space is important because it allows us to understand the structure and properties of the solution set. This, in turn, helps us to solve systems of linear equations, find bases and dimensions of vector spaces, and perform other operations in linear algebra. Additionally, it provides a foundation for more advanced mathematical concepts and applications.

5. Can the solution of Ax=0 be a non-vector space?

No, the solution of Ax=0 must always be a vector space. This is because the axioms of a vector space are fundamental mathematical properties that must be satisfied by any set that claims to be a vector space. If the solution set does not satisfy these axioms, then it cannot be considered a vector space.

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