Definition of an operator in a vector space

In summary: In that case, the theorem is equivalent to the following theorem: "a linear operator from ##V \to V## is invertible if and only if it is injective."
  • #1
maNoFchangE
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In the book that I read, an operator is defined to be a linear map which maps from a vector space into itself. For example, if ##T## is an operator in a vector space ##V##, then ##T:V\rightarrow V##. Now, what if I have an operator ##O## such that ##T:V\rightarrow U## where ##U## is a subspace of ##V##. Can I call ##O## an operator in ##V##?
 
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  • #2
maNoFchangE said:
In the book that I read, an operator is defined to be a linear map which maps from a vector space into itself. For example, if ##T## is an operator in a vector space ##V##, then ##T:V\rightarrow V##. Now, what if I have an operator ##O## such that ##T:V\rightarrow U## where ##U## is a subspace of ##V##. Can I call ##O## an operator in ##V##?
I assume you meant ##O:V\rightarrow U##. The answer is: yes. Usually one says "operator on", reserving "in" for injective functions and "onto" for surjective functions. However, that may differ from author to author.
Surjective means ##im (O) = O(V) = U## and injective that ##O(v) = 0 ⇒ v=0## or ##O: V → U## is an embedding, e.g. if ##V ⊆ U## which of course would imply ##V=U## in the case ##U## is a sub vector space of ##V##.
 
  • #3
maNoFchangE said:
In the book that I read, an operator is defined to be a linear map which maps from a vector space into itself.

It's worth pointing out some authors drop the "into itself" or "to itself" part altogether. In fact, there are people who drop the linearity requirement as well, so "operators" and "linear operators" are different things. Wikipedia seems to be of this convention.
 
  • #4
Thanks for the answers.
Ok, if ##O## defined above is an operator, then the following theorem (which I also read in the same book) is wrong:
Suppose ##V## is finite dimensional. If ##O\in\mathcal{L}(V)##, then the following are equivalent:
a) ##O## is invertible
b) ##O## is injective
c) ##O## is surjective
It can be wrong because for the special case when ##\textrm{dim } U<\textrm{dim } V##, ##O## cannot be injective, but it can still be surjective.
 
  • #5
maNoFchangE said:
Thanks for the answers.
Ok, if ##O## defined above is an operator, then the following theorem (which I also read in the same book) is wrong:

It can be wrong because for the special case when ##\textrm{dim } U<\textrm{dim } V##, ##O## cannot be injective, but it can still be surjective.
If ##\textrm{dim } U<\textrm{dim } V## then ##O## is neither injective, nor surjective, nor invertible. E.g. surjective plus ##O\in \cal{L}(V)##means ##O(V)=V##. In the cases listed ##U=V##.

Edit: The theorem says, if one of the properties holds, then all three are valid. It doesn't say it must always be the case. But if then ##O(V) = V##.
 
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  • #6
fresh_42 said:
If ##\textrm{dim } U<\textrm{dim } V## then ##O## is neither injective, nor surjective, nor invertible. E.g. surjective plus ##O\in \cal{L}(V)##means ##O(V)=V##. In the cases listed ##U=V##.
Why can't it be surjective? I think we have defined the target space of ##O## to be ##U## not ##V##. Despite ##U## being a subspace of ##V##, if ##\textrm{range }O=U##,then it is surjective. Consider the following example. Suppose ##V = \mathbb{R}^3## and ##U = \mathbb{R}^2##, and ##O## is a projection matrix,
$$
\begin{pmatrix}
1 & 0 & 0 \\
0 & 1 & 0 \\
0 & 0 & 0
\end{pmatrix}
$$
so ##O\in \mathcal{L}(\mathbb{R}^3)##. Furthermore, ##O## is surjective because ##\textrm{range }O=\mathbb{R}^2## but it's not injective.
 
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  • #7
maNoFchangE said:
Thanks for the answers.
Ok, if ##O## defined above is an operator, then the following theorem (which I also read in the same book) is wrong:
Suppose ##V## is finite dimensional. If ##O \in \mathcal L(V)## , then the following are equivalent:
a) ##O## is invertible
b) ##O## is injective
c) ##O## is surjective
It can be wrong because for the special case when ##\textrm{dim } U<\textrm{dim } V##, ##O## cannot be injective, but it can still be surjective.
The theorem is only valid if ##\dim(V)=\dim(U)##. (Although I assume that the book meant linear operators from ##V \to V##.)
If we look at linear operators from ##V \to U##:
If ##\dim(V)<\dim(U)##, a linear operator ##O## can be injective, but can not be surjective.
If ##\dim(V)>\dim(U)##, a linear operator ##O## can be surjective, but can not be injective.
 
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  • #8
Thanks @Samy_A ,
Samy_A said:
The theorem is only valid if ##\dim(V)=\dim(U)##.
Since in one of the previous posts, I have defined ##U## to be a subspace of ##V##, this implies that the theorem is valid when ##U=V##?
 
  • #9
maNoFchangE said:
Thanks @Samy_A ,

Since in one of the previous posts, I have defined ##U## to be a subspace of ##V##, this implies that the theorem is valid when ##U=V##?
Yes, the theorem is valid if ##U=V##.
 

Related to Definition of an operator in a vector space

1. What is an operator in a vector space?

An operator in a vector space is a mathematical function that maps vectors from one vector space to another. It can be represented by a matrix or a linear transformation.

2. What is the difference between a scalar and an operator in a vector space?

A scalar is a single value, while an operator is a function that operates on vectors. Scalars can be thought of as constants, while operators can change the magnitude or direction of a vector.

3. Can an operator in a vector space be non-linear?

Yes, an operator in a vector space can be non-linear. This means that the output is not directly proportional to the input. In other words, the operator does not follow the rules of a linear transformation, where the output is a linear combination of the input.

4. What is the importance of operators in vector spaces?

Operators play a crucial role in understanding and manipulating vector spaces. They allow us to perform operations on vectors, such as rotation, scaling, and reflection. Additionally, they are used in many branches of mathematics, such as linear algebra, quantum mechanics, and functional analysis.

5. Can an operator in a vector space have more than one input?

Yes, an operator in a vector space can have multiple inputs. This is known as a multivariate operator. It takes multiple vectors as inputs and produces a single vector as output. Multivariate operators are commonly used in machine learning and data analysis.

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