Why do these functions form complete orthogonal systems in the Hilbert space?

In summary, the conversation discusses two functions, ##\psi^o_k## and ##\psi^e_k##, which form complete orthogonal systems in two mutually orthogonal subspaces, composing a Hilbert space. The basis functions depend on two variables, but are only integrated over one variable. The conversation also discusses the requirements for a set of basis functions to form a Hilbert space, including orthogonality and completeness. It is mentioned that even if the basis functions are not initially orthogonal, they can be made orthogonal using the Gramm-Schmidt procedure. The conversation ends with a discussion on the role of these basis functions in approximating eigenvalues for a differential equation.
  • #1
member 428835
Hi PF!

A text states that the following two functions
$$
\psi^o_k = \sin(\pi(k-1/2)x)\cosh(\pi(k-1/2)(z+h)): k\in\mathbb{N},\\
\psi^e_k = \cos(\pi kx)\cosh(\pi k(z+h)): k\in\mathbb{N}
$$
each form complete orthogonal systems in two mutually orthogonal subspaces, which compose the Hilbert space.

Can someone explain this to me? Why are these orthogonal systems? Specifically, ##\int_0^1 \psi^e_k \psi^o_k \, dx \neq 0##. And why is it that each by itself does not form a Hilbert space but together they do (is it because they are orthogonal systems, one cannot form a Hilbert space unless at least the other is present too)?
 
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  • #2
What is ##z##? It seems like the basis functions depend on two variables. In that case I don't understand why you only integrate over ##x##.
 
  • #3
eys_physics said:
What is ##z##? It seems like the basis functions depend on two variables. In that case I don't understand why you only integrate over ##x##.
Yes, ##z## is a variable with domain ##z\in[-h,0]##. Evaluating the double integral in this domain for ##z## and ##[0,1]## for ##x## still doesn't equal zero. Any ideas?
 
  • #4
joshmccraney said:
Yes, ##z## is a variable with domain ##z\in[-h,0]##. Evaluating the double integral in this domain for ##z## and ##[0,1]## for ##x## still doesn't equal zero. Any ideas?

It is not an requirement that your basis functions are orthogonal. You need to have a well-defined scalar product. Additionally, your set of basis functions has to complete. I guess that this second point explains why you need both ##\psi^o_k## and ##\psi^e_k## to have a Hilbert space. The functions ##\psi^e_k## are for example even with respect to ##x##. So you cannot expand an odd function in this subspace.
 
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  • #5
eys_physics said:
It is not an requirement that your basis functions are orthogonal. You need to have a well-defined scalar product. Additionally, your set of basis functions has to complete. I guess that this second point explains why you need both ##\psi^o_k## and ##\psi^e_k## to have a Hilbert space. The functions ##\psi^e_k## are for example even with respect to ##x##. So you cannot expand an odd function in this subspace.
Cool, this is what I was thinking too, regarding the even/odd argument. So chalk it up to Fourier series theory that these two together are complete?

Why are these orthogonal though?
 
  • #6
I think the issue here is that the range of ##x## is between 0 and 1. That is, not a full period. If your limits would be ##x\in [-1,1]## your basis functions would be orthogonal. This is also what you would have in Fourier series theory, where your range is a full period.
 
  • #7
eys_physics said:
I think the issue here is that the range of ##x## is between 0 and 1. That is, not a full period. If your limits would be ##x\in [-1,1]## your basis functions would be orthogonal. This is also what you would have in Fourier series theory, where your range is a full period.
In this case the domain of ##z## wouldn't matter, right, since sine times cosine is odd, integrated over a symmetric domain, always gives zero.
 
  • #8
joshmccraney said:
In this case the domain of ##z## wouldn't matter, right, since sine times cosine is odd, integrated over a symmetric domain, always gives zero.

Yes, you are correct.
 
  • #9
So to summarize: ##\psi^o## and ##\psi^e## are both orthogonal systems ##\int_{-1}^1 \psi^e\psi^o\,dx = 0## in two mutually orthogonal subspaces (even and odd). Since they are orthogonal, at least both are required to form a Hilbert space (possibly more). Since these two are systems essentially Fourier modes, it is well documented that both are complete and form a Hilbert space without extra systems.

Does that sound right?
 
  • #10
joshmccraney said:
So to summarize: ##\psi^o## and ##\psi^e## are both orthogonal systems ##\int_{-1}^1 \psi^e\psi^o\,dx = 0## in two mutually orthogonal subspaces (even and odd). Since they are orthogonal, at least both are required to form a Hilbert space (possibly more). Since these two are systems essentially Fourier modes, it is well documented that both are complete and form a Hilbert space without extra systems.

Does that sound right?

I agree with you except for one detail. Even if they would not be orthogonal you would need both odd and even basis functions. But, you can always use the Gramm-Schmidt procedure to construct a orthogonal basis. So, this is only a small detail.
 
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  • #11
Thanks!
 
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  • #12
I think the issue re the orthogonality is that a vector space (an inner-prod space, actually) can be expressed as the direct sum of a subspace and the Ortho complement of the subspace. Simplest example, consider the plane with the x-axis as a subspace and the y-axis as its Ortho complement so that ##\mathbb R^2= x(+)y ##. A subspace of a Hilbert space is not always itself a Hilbert space.
 
  • #13
Re your first question, were you given an explicit formula for the inner-product, or a description of the Hilbert space for which you were given these bases?A basis for a Hilbert space is a maximal orthohonal set.
 
  • #14
WWGD said:
Re your first question, were you given an explicit formula for the inner-product, or a description of the Hilbert space for which you were given these bases?A basis for a Hilbert space is a maximal orthohonal set.
I was not. I can say that these basis functions are integrated at ##z=0## over ##x\in[0,1]## to approximate eigenvalues from a differential equation. Does that help?
 
  • #15
Somewhat. I can tell it is countably-infinite dimensional from the basis. Give me some time and I will go over the paper you linked.
 
  • #16
WWGD said:
Somewhat. I can tell it is countably-infinite dimensional from the basis. Give me some time and I will go over the paper you linked.
Thanks!
 
  • #17
@joshmccraney :I was looking for the link you referred to, to look up some details. What happened to it?
 
  • #19
Got it, thanks.
 
  • #20
Yes, hi again, this is just the space ##L_2(a,b)## of square-integrable functions with the inner product you described: ## <f,g>:= \int_a^b fg ##. Remember that Hilbert spaces have the special property that the metric is generated by the inner-product. In Hilbert spaces, bases are maximal orthogonal systems. I am not clear if H is a subspace of a Hilbert space or a Hilbert space itself.
 

Related to Why do these functions form complete orthogonal systems in the Hilbert space?

1. Why are orthogonal systems important in a Hilbert space?

Orthogonal systems are important in a Hilbert space because they allow for a convenient and efficient way to represent and manipulate mathematical functions or vectors. In an orthogonal system, each function or vector is independent and does not overlap with any other function or vector, making it easier to solve complex problems.

2. What is the significance of completeness in a Hilbert space?

Completeness is a fundamental property of a Hilbert space. It means that every element in the space can be represented as a linear combination of the orthogonal basis functions. This allows for the representation and manipulation of any function or vector in the space using a finite number of basis functions, making it a powerful tool for mathematical analysis and problem-solving.

3. How are orthogonal systems related to the concept of inner product in a Hilbert space?

In a Hilbert space, the inner product is a mathematical operation that measures the similarity or difference between two functions or vectors. Orthogonal systems are closely related to the inner product because the inner product of two orthogonal functions or vectors is zero, which means they are completely independent of each other.

4. Can orthogonal systems be used in any type of Hilbert space?

Yes, orthogonal systems can be used in any type of Hilbert space, as long as the space has an inner product defined. This is because the concept of orthogonality and completeness is defined in terms of the inner product, making it applicable to any space with this property.

5. How are orthogonal systems related to the concept of basis in linear algebra?

In linear algebra, a basis is a set of linearly independent vectors that span the entire vector space. Similarly, an orthogonal system in a Hilbert space is a set of independent functions or vectors that span the entire space. This means that orthogonal systems can be seen as a generalized version of a basis in linear algebra, making it a powerful tool for solving problems in various fields of science and engineering.

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