Finding coefficients using dual basis

In summary, the conversation discussed finding the coefficients of a linear map in a dual basis for a finite-dimensional vector space. It was explained that the coefficients could be found by taking the dot product of the vector with each basis vector in the dual basis. This method was demonstrated using the basis vectors in the example given.
  • #1
Supreme_BiH
3
0
Let V be the space of polynomials of degree 3 or less over [tex]\Re[/tex]. For every [tex]\lambda\in\Re[/tex] the evaluation at [tex]\lambda[/tex] is the map ev[tex]_{\lambda}[/tex] such that V [tex]\rightarrow[/tex] [tex]\Re[/tex] is linear. How do we find the coefficients of ev[tex]_{2}[/tex] in the basis dual to [tex]\{1,x,x^2,x^3\}[/tex]?
 
Last edited:
Physics news on Phys.org
  • #2
Suppose you have any finite-dimentional vector space, V, with dual space V*. Suppose, for the sake of definiteness, it's 4-dimensional, like the one in your example. Let [itex]\mathbf{e}_\nu[/itex] be the nu'th vector of some basis for V. Let [itex]\pmb{\varepsilon}_\mu[/itex] be the mu'th vector of the dual basis for V* corresponding to the basis { [itex]\mathbf{e}_\nu[/itex] }. Let v be an arbitrary vector of V, and let v subscript nu be the nu'th coefficient of v in this basis. Let alpha be an arbitrary linear map from V to its field (In your case, that's the real numbers.), and let alpha subscript mu be the mu'th coefficient of alpha in this dual basis. Then

[tex]\pmb{\alpha}(\mathbf{v})= \sum_{\mu=0}^{3} \alpha_\mu \pmb{\varepsilon}_\mu(\mathbf{v}) = \sum_{\mu=0}^{3} \alpha_\mu \pmb{\varepsilon}_\mu \left ( \sum_{\nu=0}^{3}v_\nu \mathbf{e}_\nu \right ) = \sum_{\mu=0}^{1} \alpha_\mu v_\mu,[/tex]

since, by the definition of a dual basis,

[tex]\pmb{\varepsilon}_\mu(\mathbf{e}_\nu)= \delta_{\mu\nu},[/tex]

where the expression on the right is Kronecker's delta, equal to 1 if mu = nu, and 0 otherwise.

Notice what happens if v is one of your chosen basis vectors.
 
Last edited:
  • #3
thank you.
 

1. What is a dual basis?

A dual basis is a set of vectors that form a basis for the dual space of a given vector space. It is used to find coefficients for linear combinations of vectors in the original space.

2. How is the dual basis used to find coefficients?

The dual basis is used to find coefficients by taking the inner product of a vector with each vector in the dual basis. This results in a system of equations that can be solved to find the coefficients.

3. What are the benefits of using the dual basis method?

The dual basis method allows for a more efficient and systematic approach to finding coefficients, especially in higher dimensional spaces. It also provides a way to easily check for linear independence of vectors.

4. Can the dual basis be used for non-linear systems?

No, the dual basis method is specifically for finding coefficients in linear systems. For non-linear systems, other methods such as gradient descent or curve fitting may be more appropriate.

5. How does the choice of basis affect the coefficients found using the dual basis method?

The choice of basis affects the coefficients found using the dual basis method because the dual basis is dependent on the original basis. Changing the basis will result in different dual basis vectors and therefore different coefficients for linear combinations.

Similar threads

Replies
3
Views
2K
  • Linear and Abstract Algebra
Replies
1
Views
2K
  • Linear and Abstract Algebra
Replies
7
Views
251
  • Linear and Abstract Algebra
Replies
12
Views
1K
  • Linear and Abstract Algebra
Replies
9
Views
576
Replies
3
Views
2K
  • Calculus and Beyond Homework Help
Replies
0
Views
450
  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
3
Views
1K
  • Linear and Abstract Algebra
Replies
9
Views
201
Back
Top