Conditions for Surjective and Injective linear maps

In summary, the conversation discusses the question of whether an injective function with equal dimensions for its domain and codomain is also surjective and bijective. The concept is known as the Fredholm alternative and is true for finite-dimensional spaces. It can also be easily understood through the rank-nullity theorem. The conversation ends with a suggestion to think about the concept intuitively and an exercise to determine if the elements of the image are linearly independent.
  • #1
malexj93
2
0
Hello,

I'm not sure if this should go under the HW/CW section, since it's not really a homework question, just a curiosity about certain kinds of functions. My specific question is this:

If M: U→V is injective and dim(U)=dim(V), does that imply that M is surjective (and therefore bijective) as well? And why is that?

I believe it does, but I can't seem to justify it.
 
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  • #2
malexj93 said:
Hello,

I'm not sure if this should go under the HW/CW section, since it's not really a homework question, just a curiosity about certain kinds of functions. My specific question is this:

If M: U→V is injective and dim(U)=dim(V), does that imply that M is surjective (and therefore bijective) as well? And why is that?

I believe it does, but I can't seem to justify it.

For finite-dimensional spaces, it is true. It is called the Fredholm alternative: http://en.wikipedia.org/wiki/Fredholm_alternative

Do you know the rank-nullity theorem? It follows easily from there.
 
  • #3
Thanks, that's what I was looking for. I didn't know there was a theorem for that.
 
  • #4
Think about it intuitively too. Say [itex]V=\{v_1,v_2,...,v_k\}[/itex] is a basis for the Domain space. What is the image of [itex]V[/itex]? are the elements of [itex] M(V)[/itex] Linearly independent? It's a good exercise to figure this out. If they are, by the dimension condition you have found a basis.
 
  • #5


I can provide an answer to your question about surjective and injective linear maps. First, let's define what it means for a linear map to be injective and surjective.

A linear map M: U→V is injective if for any two elements u1 and u2 in U, M(u1) = M(u2) implies that u1 = u2. This means that each element in U has a unique corresponding image in V under M.

On the other hand, a linear map M: U→V is surjective if for every element v in V, there exists an element u in U such that M(u) = v. In other words, every element in V has at least one pre-image in U under M.

Now, to answer your question, if M is both injective and has the same dimension as U and V, then M must also be surjective. This is because if U and V have the same dimension, then they have the same number of elements. And if M is injective, each element in U has a unique image in V. Therefore, there cannot be any elements in V that do not have a corresponding pre-image in U, making M surjective.

To visualize this, imagine U and V as two different sized buckets, with U having the same number of balls as V. If M is injective, each ball in U has a unique spot in V. And if U and V have the same number of balls, there cannot be any empty spots in V, making M surjective.

I hope this explanation helps. If you have any further questions, please don't hesitate to ask. As scientists, it's important to always question and seek understanding.
 

Related to Conditions for Surjective and Injective linear maps

1. What is the difference between surjective and injective linear maps?

Surjective linear maps, also known as onto maps, map every element in the domain to an element in the codomain. Injective linear maps, also known as one-to-one maps, map each element in the domain to a unique element in the codomain.

2. How can I determine if a linear map is surjective or injective?

A linear map is surjective if and only if the rank of the map's matrix is equal to the dimension of the codomain. A linear map is injective if and only if the kernel, or null space, of the map is equal to {0}.

3. Can a linear map be both surjective and injective?

Yes, a linear map can be both surjective and injective. This type of map is called a bijective linear map, meaning it is both one-to-one and onto.

4. What are the conditions for a linear map to be surjective?

The conditions for a linear map to be surjective are: the map must be defined on a vector space, the rank of the map's matrix must be equal to the dimension of the codomain, and the map must be onto, meaning every element in the codomain is mapped to by at least one element in the domain.

5. Are there any real-world applications for surjective and injective linear maps?

Yes, surjective and injective linear maps are used in various fields such as engineering, computer science, and economics. For example, in engineering, these types of maps are used to model systems and analyze their behavior. In computer science, they are used for data compression and encryption. In economics, they are used to model supply and demand and analyze market equilibrium.

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