Maximal Subspaces in Vector Spaces: Using Zorn's Lemma to Prove Existence

In summary, the problem is to prove that every vector space V has a maximal subspace, which is a proper subspace that is not properly contained in any other proper subspace of V. To do this, one approach is to use Zorn's Lemma and consider the collection A of all subspaces of V that do not contain a fixed vector v in V. The upper bound of any chain in A would be a proper subspace, and the maximal element of A would be the desired maximal subspace of V. Another approach is to take a basis of V and delete one element, and the span of that set would also be a maximal subspace. However, this approach may not be applicable for infinite-dimensional vector spaces, in which
  • #1
mathboy
182
0
Maximal subspace

Problem: Prove that every vector space V has maximal subspace, i.e. a proper subspace that is not properly contained in a proper subspace of V.

I let A be the collection of all proper subspaces of V, but I can't prove that every totally ordered subcollection of A has an upper bound in A. The problem that the union of proper subspaces is not necessarily a proper subspace of V. What do I do now?
 
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  • #2
But the union of a chain of subspaces is a subspace.
 
  • #3
mathboy said:
Problem: Prove that every vector space V has maximal subspace, i.e. a proper subspace that is not properly contained in a proper subspace of V.

I let A be the collection of all proper subspaces of V, but I can't prove that every totally ordered subcollection of A has an upper bound in A. The problem that the union of proper subspaces is not necessarily a proper subspace of V. What do I do now?

Think basis elements.
 
  • #4
morphism said:
But the union of a chain of subspaces is a subspace.

But it has to be a proper subspace of V.

For example { span{1}, span{1,x}, span{1,x,x^2}, span{1,x,x^2,x^3}, ... } is a chain of proper subspaces of R[x], but its union is all of R[x], which is not a proper subspace of R[x].
 
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  • #5
JasonRox's idea is good, take a basis of V and delete one element. The span of that would have to be a maximal subspace.

But I'm assuming that mathboy wants to use Zorn's lemma. In that case choose any v in V, and let A be the collection of all subspaces not containing v. This time the upper bound of any chain will be a proper subspace. The maximal element of A would be a maximal subspace of V.
 
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  • #6
andytoh said:
But it has to be a proper subspace of V.
Oops! I should learn to read! Thanks for pointing that out. :smile:
 
  • #7
JasonRox's idea is good, take a basis of V and delete one element. The span of that would have to be a maximal subspace.

I don't think the problem implies there IS a basis of V (unless it turns out all vector spaces have a basis, and I just don't know that yet)
 
  • #8
Office_Shredder said:
I don't think the problem implies there IS a basis of V (unless it turns out all vector spaces have a basis, and I just don't know that yet)

Is V finite-dimensional? Is the book assuming that?

Do you know what finite-dimensional is?
 
  • #9
Every vector space V has a basis, whether it is finite-dimensional or not. In mathboy's problem V can be infinite-dimensional and the result is still true.

If you want to prove that V has a basis if V is infinite-dimensional, you would have to use Zorn's lemma as well. Ultimately, mathboy's problem rests on Zorn's Lemma.


My approach to mathboy's problem is: Choose any v in V, and let A be the collection of all subspaces not containing v and then use Zorn's lemma. But I'm trying to figure out if there is a better partially ordered set to use, because my A seems a little clumsy (though I believe it would still get the job done).
 
  • #10
andytoh said:
Every vector space V has a basis, whether it is finite-dimensional or not. In mathboy's problem V can be infinite-dimensional and the result is still true.

Of course I know this!

Ok, a vector space has a basis {v_1,...}, now delete one vector from there and span that that set. What do you get?

Voila!
 
  • #11
Thanks guys. I forgot to say that I have to use Zorn's Lemma. But I know how to proceed now. I will use the collection of all proper subspaces that does not contain some fixed v in V.
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of objects, called vectors, and a set of operations, such as addition and scalar multiplication, that can be performed on these vectors. These operations must follow certain rules, such as closure, commutativity, and associativity, in order for the set to be considered a vector space.

2. What are the basic properties of a vector space?

The basic properties of a vector space include closure, commutativity, associativity, existence of an identity element, existence of inverse elements, and distributivity. These properties ensure that the set of vectors and the operations performed on them behave in a consistent and predictable manner.

3. What is the difference between a vector and a scalar?

A vector is an object that has both magnitude and direction, while a scalar is an object that only has magnitude. In a vector space, vectors can be added together or multiplied by a scalar, but scalars can only be multiplied by other scalars.

4. How does a vector space relate to linear algebra?

Linear algebra is the branch of mathematics that deals with vector spaces and the operations performed on them. Vector spaces are the foundation of linear algebra, and many concepts and techniques in linear algebra, such as matrix operations and transformations, are based on the properties of vector spaces.

5. What are some real-life applications of vector spaces?

Vector spaces have many real-life applications, including in physics, engineering, computer graphics, and machine learning. For example, in physics, vectors are used to represent forces and velocities, while in computer graphics, they are used to represent the position and orientation of objects in a 3D space. In machine learning, vector spaces are used to represent and analyze data, such as text documents or images.

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