V* ≠ {0}: Exploring Non-Zero Continuous Linear Functionals in Normed Spaces

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In summary, the conversation discusses the existence of a non-zero continuous linear functional on a normed space V, specifically whether V*≠{0}. It is mentioned that for finite-dimensional spaces, V* is always nonempty, but for infinite-dimensional spaces, the Hahn-Banach theorem must be used. The norm is also discussed as a possible linear functional, but it is pointed out that it is not linear.
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Fredrik
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Is there an easy way to see that if V is a (non-empty and non-trivial) normed space, there exists a non-zero continuous linear functional on V? To put it another way: Is there an easy way to see that V*≠{0}?. Do we have to use the Hahn-Banach theorem for this?
 
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  • #2


If V is finite dimensional, then V* is always nonempty.
But for infinite-dimensional space, you will have to use Hahn-Banach. This theorem will give you a nontrivial bounded functional.
 
  • #3


Sorry if this is nonsense, it's been a while, but isn't the norm continuous by definition?
I.e. isn't
[tex]|| \cdot || : V \to \mathbb{R}, f \mapsto ||f||[/tex]
a linear functional on V?
Clearly it is non-zero, because ||f|| = 0 iff f = 0.
 
  • #4


Norm is not linear because for [itex]v\neq 0[/itex]

[tex]||-v||\neq -||v||[/tex]
 
  • #5


Good point.
Never mind I said something.

* whistles and shuffles away innocently *
 
  • #6


Thanks, that's what I thought. I got a little confused by the fact that immediately before stating the Hahn-Banach theorem, the book suggested that I think about why V*≠{0}. It's hard to know if I'm supposed to try and succeed, or try and fail just to see that we need a fancy theorem.
 

1. What does V* ≠ {0} mean?

V* ≠ {0} is a mathematical notation that represents a vector space without the zero vector. In other words, it means that there are no vectors in the vector space that have all components equal to zero.

2. Why is it important for V* to not equal {0}?

If V* = {0}, then the vector space would only contain the zero vector and no other vectors. This would make the vector space trivial and not very useful for mathematical calculations and applications. By not including the zero vector, we ensure that the vector space is non-trivial and can accommodate a wide range of vectors with different components.

3. What are some examples of vector spaces where V* ≠ {0}?

An example of a vector space where V* ≠ {0} is the set of all 2-dimensional vectors (x, y) where x and y are real numbers. Another example is the set of all polynomials of degree 2 or higher with real coefficients.

4. Can V* = {0} for certain vector spaces?

Yes, there are some vector spaces where V* can equal {0}. For example, the set of all vectors with only one component (x) where x is a real number. In this case, the only vector in the vector space would be the zero vector (0).

5. How does V* ≠ {0} affect vector operations?

V* ≠ {0} does not affect vector operations in any significant way. All the usual vector operations such as addition, scalar multiplication, and dot product can still be performed. The only difference is that the zero vector will not be included in the set of vectors that these operations are performed on.

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