Hermitian Adjoint of V & R Vector Spaces Homework

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In summary: That will also be a good check for yourself for (b), as well.For (b), you can certainly use the same method as you did for (a), in principle (the same method, that is, not the same calculations). However, the difficulty will be that the "target" space, ##\mathbb{R}##, is much simpler than the "source" space, ##V##. This will make the calculations more complicated, and you will have to be careful to keep track of what is a linear functional on ##V## and what is a linear functional on ##\mathbb{R}##.Alternatively, what the question is really asking for is a linear map ##\Phi^*\colon \math
  • #1
Doradus
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Homework Statement



Be V the set ##\{f \in \mathbb{R}[X]| deg\,f \leq 2 \}##. This becomes to an euclidic vector space through the
inner product ##\langle f,g\rangle:=\sum_{i=-1}^1f(i)g(i)## .
The same goes for ##\mathbb{R}## with the inner product ##\langle r,s\rangle :=rs\,\,\,##.

a) For ##j:\mathbb{R}\to V,r\mapsto rX##, calculate the hermitian adjoint ##j^*##.

b) Be ##\Phi :V \to \mathbb{R}## the linear map ##\sum_{i=0}^2a_iX^i \mapsto \sum_{i=0}^2a_i \,\,\,##. Calculate the hermitian adjoint ##\Phi^*\,\,\,##.

Homework Equations



The Attempt at a Solution


For a) i have the follwowing solution:

##\langle f,j(s) \rangle_V = \langle j^*(f), s \rangle_{\mathbb{R}}##
##\Rightarrow \sum_{i=-1}^1f(i) \cdot (j(s))(i)=j^*(f) \cdot s##
##\Rightarrow f(-1)\cdot -s+f(0)\cdot 0s+f(1)\cdot s = j^*(f) \cdot s##
##\Rightarrow j^*(f)=f(1)-f(-1)##

Is this solution correct?
For b), i don't find a starting point.
 
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  • #2
Can't we approach (b) the same way as (a)?
For (b), the defining equation is
$$\langle\Phi(f),s\rangle=\langle f,\Phi^*(s)\rangle$$
What happens if we expand that using the definitions given?

Your working for (a) looks broadly correct. To check that something has not gone wrong, like a missed sign, plug a polynomial ##f(x)=a_0+a_1x+a_2x^2## into it and see if the equality of the two inner products holds.
 

Related to Hermitian Adjoint of V & R Vector Spaces Homework

1. What is the definition of a Hermitian adjoint of a vector space?

The Hermitian adjoint of a vector space is a linear transformation that maps elements of the vector space to their complex conjugates. It is also known as the conjugate transpose.

2. How is the Hermitian adjoint of a vector space different from the regular transpose?

The Hermitian adjoint takes into account the complex conjugates of the elements, while the regular transpose only switches the rows and columns of a matrix. This means that the Hermitian adjoint is the more general form of the transpose for complex vector spaces.

3. Can the Hermitian adjoint of a vector space be computed for any type of vector space?

No, the vector space must be defined over a field of complex numbers in order for the Hermitian adjoint to be defined. This is because the concept of complex conjugates is only applicable to complex numbers.

4. What is the relationship between the Hermitian adjoint and the inner product of a vector space?

The Hermitian adjoint is closely related to the inner product of a vector space. In fact, the Hermitian adjoint of a linear transformation is the only transformation that preserves the inner product of the vector space.

5. How is the Hermitian adjoint of a vector space used in quantum mechanics?

In quantum mechanics, the Hermitian adjoint is used to represent the complex conjugate of a wavefunction. This is important for understanding the probability amplitudes of quantum systems and making predictions about their behavior.

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