Functional analysis - task on convexity and dual spaces

In summary, the closure of a subset of a real normed space satisfies the equality if and only if the subset is contained in the closure.
  • #1
TaPaKaH
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Homework Statement


Let [itex]C[/itex] be a non-empty convex subset of a real normed space [itex](X,\|\cdot\|)[/itex].
Denote [itex]H(f,a):=\{x\in X: f(x)\leq a\}[/itex] for [itex]f\in X^*[/itex] (dual space) and [itex]a\in\mathbb{R}[/itex].
Show that the closure [itex]\bar{C}[/itex] of [itex]C[/itex] satisfies [itex]\bar{C}=\bigcap_{f\in X^*,a\in\mathbb{R}: C\subseteq H(f,a)}H(f,a)[/itex].

Give an example of a real normed space [itex](X,\|\cdot\|)[/itex] and a non-convex set [itex]C[/itex] for which the equality above does not hold.

2. Relevant information
This task comes in a homeworkset which relates to the application of the Hahn-Banach (extension) theorem, but I just can't see how one could apply it to the exercise above.
 
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  • #2
One inclusion is trivial (= doesn't require Hahn-Banach). Do you see which one that is?

Also, do you know the geometric Hahn-Banach theorem?? This is an analogous formulation of Hahn-Banach that does not deal with extensions of functionals, but rather with separation of subsets with hyperplanes. This version might be handy here.
 
  • #3
The [itex]\subset[\itex] inclusion seems indeed simple as the right-hand-side is a closed set (intersection of closed sets) that contains C.

I know the (two-set) separation version of HBT but still can't see how that can be used in this case.
 
  • #4
Assume that [itex]x\notin \overline{C}[/itex], but assume that x is a member of the intersection. Try to find a contradiction. Start with applying the definition of the closure. This will give you an open set U disjoint from C. Does this give you ideas?
 
  • #5
Yes, your hint makes perfect sense now.

If [itex]x\in\bigcap_{f\in X^*,a\in\mathbb{R}: C\subseteq H(f,a)}H(f,a)[/itex] but [itex]x\notin\bar{C}[/itex] then [itex]d(x,\bar{C})=2\delta>0[/itex] so we can separate [itex]C[/itex] and [itex]U_\delta(x)[/itex] with a hyperplane [itex]\{f=a\}[/itex] (for some f and a) and get a contradiction with [itex]x\in\bigcap_{f\in X^*,a\in\mathbb{R}: C\subseteq H(f,a)}H(f,a)[/itex].

I got the idea I was looking for, thank you very much!
 

What is functional analysis?

Functional analysis is a branch of mathematics that deals with the study of vector spaces, operators, and functionals. It focuses on analyzing the properties and behavior of functions, particularly those defined on infinite-dimensional spaces.

What is convexity in functional analysis?

Convexity is a property of a function in functional analysis that describes a shape that never curves inwards. In simpler terms, it means that the line connecting any two points on the graph of a convex function always lies above the graph itself.

What is the dual space in functional analysis?

The dual space in functional analysis is the space of all continuous linear functionals on a given vector space. It is denoted by V* and is a vector space itself. The dual space is important in functional analysis as it allows us to study the properties of a vector space by analyzing its functionals.

What is the difference between a Banach space and a Hilbert space?

Both Banach spaces and Hilbert spaces are examples of infinite-dimensional vector spaces. However, the main difference between them lies in the type of norm used. Banach spaces use the concept of norm to measure distance, while Hilbert spaces use the concept of inner product, which allows for the notion of angles and orthogonality.

What are some applications of functional analysis?

Functional analysis has a wide range of applications in various fields, including physics, engineering, economics, and computer science. It is used to study and solve problems involving differential equations, optimization, and control theory. It also has applications in the study of quantum mechanics and signal processing.

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