It shows that V is the dual space of V*?

In summary, the conversation discusses the concept of dual spaces and how they are related to vector spaces. The main point is that if V is finite dimensional, then V is isomorphic to its dual space V*, meaning they have the same basis. This is because there is a bijection between elements of V and linear functions on V*. This bijection is also an isomorphism, meaning it preserves the structure and operations of the vector space.
  • #1
Mr.M
6
0
Not my homework
It's in the textbook - lectures of diff geo by s.s.chern
Just put them down in a clearer way
Could anybody explain the questions in the pic ?
http://x7d.xanga.com/be6d931344030137094065/z100635368.jpg"
 
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  • #2
This is only true if V is finite dimensional. Hint just write down bases.
 
  • #3
actually i don't understand the last step
Phi is taken out of the sum because it is linear in the 2nd variable ?
And "V is the dual space of V*"looks very confusing
The dual space of V is the set linear functions on V
Now the dual space of V* is the set linear functions on V*?
how can i see that ?
 
  • #4
i just got another idea
since <v,v*> just depends on v*
so we just treat it as a function of v* and then we have the last step ?
 
  • #5
If V is a finite dimensional vector space, then V the only invariant of V is its dimension. ALL vector spaces of a given dimension (over the same field) are isomorphic. Since V is clearly isomorphic to V* by picking a basis and corresponding dual basis, this shows that (V*)* must be isomorphic to V since they have the same basis. (This fails in infinite dimensions.)

What I presume you're looking at is a 'nice' bijection that sends v in V to the function on V* that sends f to f(v). Notice how an element of v can be sent to a function, call it e_v, and think of it as evaluation at v. This is a linear functional on the space of linear functionals:

e_v(f)=f(v).

This defines a map from V to the space of linear functionals on V*

v--->e_v

it is straight foward to show this is an isomorphism.
 
  • #6
if f(x) is a number, then f sends x to a number, and x sends f to a number. so f is a function of x, and x is a function of f. so points of the domain are functions on functions.
 

1. What is the dual space of V*?

The dual space of V* is the space of all linear functionals on V. In other words, it is a space of linear transformations from V to the underlying field.

2. How is the dual space of V* related to V?

The dual space of V* is the algebraic dual space of V, meaning it is the space of all linear functionals on V. This means that every element in the dual space of V* is a linear map from V to the underlying field.

3. What does it mean for V to be the dual space of V*?

When V is the dual space of V*, it means that every element in the dual space of V* can be uniquely represented as a linear combination of elements in V. In other words, V and V* are isomorphic as vector spaces.

4. How do you show that V is the dual space of V*?

To show that V is the dual space of V*, you must prove that every element in the dual space of V* can be uniquely represented as a linear combination of elements in V. This can be done using linear algebra techniques such as matrix representation and basis transformations.

5. Why is it important to understand the concept of the dual space of V*?

The dual space of V* is important in many areas of mathematics and physics, including functional analysis, differential geometry, and quantum mechanics. It allows us to understand the relationship between a vector space and its algebraic dual space, and has applications in areas such as optimization, differential equations, and signal processing.

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