Convex Subsets of Topological Vector Spaces

In summary, the conversation is discussing the correctness of a proof for the theorem that states a convex subset of a vector space will also be convex when multiplied by a scalar value between 0 and 1. The proof is deemed correct and it is noted that the theorem applies to any vector space over the real or complex numbers, not just topological vector spaces.
  • #1
Edwin
162
0
I had a quick question:

Is the following proof of the theorem below correct?


Theorem: If C is a convex subset of a Topological vector space X, and the origin 0 in X is contained in C, then the set tC is a subset of C for each 0<=t<=1.

Proof: Since C is convex, then

t*x + (1-t)*y is contained in C, for every x,y in C, and for 0<=t<=1.

Since y = 0 is contained in C, then in particular,

t*x = t*x + (1-t)*0 = t*x + (1-t)*y is contained in C, for every x in C, and for 0<=t<=1.

Hence tC is a subset of C for 0<=t<=1. This completes the proof.



Is the above proof correct? Or, did I make a mistake in the proof?
 
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  • #2
Yes, the proof is correct. As a side remark, note that you did not need the vector space to be equipped with a topology. Thus the theorem is true (with the same proof) for any vector space over the real or complex numbers.
 
  • #3
Thank you for the information! I had not noticed that.

So then the essential information in the proof are the vector space axioms (where the scalar field is either the real or complex numbers), and the definition of a convex set. The case of a Topological vector space is then just a special case of the more general theorem applied to an arbitrary vector space. Interesting.
 

What is a convex subset?

A convex subset of a topological vector space is a subset that contains all the points along the straight line connecting any two points within the subset. In other words, for any two points x and y in the subset, the line segment between them is also contained within the subset.

Why are convex subsets important in topological vector spaces?

Convex subsets are important because they allow for the use of convex combination, which is a key concept in optimization and functional analysis. They also have nice geometric properties that make them useful in many mathematical and scientific applications.

Can convex subsets be unbounded?

Yes, a convex subset can be unbounded. This means that the subset extends infinitely in one or more directions. For example, the set of all positive real numbers is a convex subset of the topological vector space of real numbers, but it is unbounded.

What is the difference between a convex subset and a convex set?

A convex subset is a subset of a larger vector space that satisfies the definition of convexity. A convex set, on the other hand, is a set that is itself a vector space and satisfies the definition of convexity. In other words, a convex subset is a subset of a convex set, but a convex set is not necessarily a subset of another convex set.

Are all convex subsets also open sets?

No, not all convex subsets are open sets. A subset can be convex without being open, and it can also be open without being convex. For example, the open interval (0,1) is both convex and open in the topological vector space of real numbers, but the closed interval [0,1] is convex but not open.

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