How to study an ODE in matrix form in a Hilbert space?

In summary, the conversation discusses the derivation of the matrix form of one ODE, which yields a complex matrix with a spiral source phase portrait. The matrix also indicates that the ODE has diffeomorphic flow and requires stringent initial conditions. The topic then shifts to studying the ODE in a Hilbert space and representing it in it, with a specific example of a 2x2 matrix given. The discussion also includes the computation of the general solution using the matrix exponential, and the role of eigenvalues and eigenvectors in determining the time evolution of the initial condition. There is also mention of a book by Hirsch, Devaney, and Smale that discusses the exponential of complex matrices. The conversation concludes with a question about the
  • #1
SeM
Hello, I have derived the matrix form of one ODE, and found a complex matrix, whose phase portrait is a spiral source. The matrix indicates further that the ODE has diffeomorphic flow and requires stringent initial conditions. I have thought about including limits for the matrix, however the diffeomorphism already indicates that we deal with infinity unless some conditions are applied.

I am however unaware on how to study the ODE in a Hilbert space, or simply represent it in it. I have the matrix: [ 2, i4; i5, 6] . Is there any particular thing that I have missed here? I.e. The Poincare map?

Thanks!
 
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  • #2
Quite a number of different terms appear in your post.

Firstly, although ##\mathbb{C}^n## is also a Hilbert space, to me the term "Hilbert space" suggests infinite dimensionality.

As far as I see, you have a ##2 \times 2## complex matrix ##A## corresponding to an autonomous linear system of two complex ODEs. The time evolution of an initial condition ##\mathbf{z}_0 \in \mathbb{C}^2## is given by the matrix exponential ##e^{tA}## acting on ##\mathbf{z}_0##, which in turn can be computed from the eigenvalues and eigenvectors of ##A##.
 
  • #3
Thanks Krylov.

I have looked at your suggestion, and I have computed already the general solution:

\begin{equation}
X_1(t) = \alpha e^{\lambda_1 t} \binom{a}{b}+ \beta e^{\lambda_2 t} \binom{c}{d}
\end{equation}

Is this what you had in mind?

Thanks!
 
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  • #4
SeM said:
The initial condition is z_0 = cos(phi)
I think the initial condition should have two components, i.e. ##\mathbf{z}_0 = (z_{0,1}, z_{0,2})## with ##z_{0,1}## and ##z_{0,2}## in ##\mathbb{C}##.
SeM said:
was not aware of the time-dimension in this.
For definiteness, I understood that you like to solve
$$
\frac{d\mathbf{z}(t)}{dt} = A\mathbf{z}(t), \quad A =
\begin{bmatrix}
2& 4i\\
5i& 6\end{bmatrix}, \quad
\mathbf{z}(t) = \mathbf{z}_0,
$$
where "time" ##t## is thought of as the independent variable.
SeM said:
How does an example of the matrix exponential in the time dimension computed for the eigenvalues and vectors look like? In a book a I have "Diff Eqns, Dynamical Syst and Intro to Chaos", it gives a description of the exponential matrix. Is it this you refer to?
Yes, is this the book by Hirsch, Devaney and Smale? I believe that there this is indeed discussed, but for for matrices with real entries only. (This is relevant for most applications. Of course, there may still be complex eigenvalue and eigenvectors, but ##A## itself is assumed real.) You would need a treatment that discusses the similar - but not identical - case of complex matrices.

Perhaps it is in the 1974 edition by Hirsch and Smale (a lot of linear algebra was unfortunately removed in subsequent editions), but otherwise you will find it in almost every linear algebra text that does not restrict itself to vector spaces over ##\mathbb{R}##.
 
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  • #5
I changed the reply because I realized I may have understood you right in the first place, however, what you wrote now is new to me.

You mention definiteness, which appears as a time-evolution behavior of the matrix components. I have initial conditions for the analytical solution, which is x_0 = cos(theta), however, in order to study this from a Hilbert space perspective, this condition would not apply as you write.

Does the general solution I wrote above answer the time evolution point you mentioned? In case not, the respective chapter by Hirsch, Devaney and Smale discussed some more terms, such as A -¹ and I in this context. How can this approach be simplified in the given case? (Unless the general solution does not answer that):

PS: I have used the exponential of the matrix by multiplying it with the eigenvectors. The exponential term is the eigenvalue. However, you included A in your exponential term. Is this a different story?
 
  • #6
PS: I have computed the exponential of the matrix, which is:

[ e^2, e^4i; e^5i, e^6]

However, how can this be applied to say something about the matrix, which the phase-plane portrait hasn't already?

Thanks
 
  • #7
Dear Krylov, can the divergence or convergence of the eigenvectors say something about the general solution? I can't find anyting on divergence and convergence of eigenvectors on the web that says that.

Thanks!
 

Related to How to study an ODE in matrix form in a Hilbert space?

1. What is an ODE?

An ODE, or Ordinary Differential Equation, is a mathematical equation that describes the relationship between a function and its derivatives. In other words, it shows how a function changes over time.

2. What is a matrix form of an ODE?

A matrix form of an ODE represents the ODE using a matrix, which is a rectangular array of numbers. This form is often used in solving systems of ODEs, as it allows for easier manipulation and computation.

3. What is a Hilbert space?

A Hilbert space is a mathematical concept that represents an infinite-dimensional vector space. It is a generalization of the Euclidean space, which we are familiar with in three dimensions. Hilbert spaces are often used in functional analysis and quantum mechanics.

4. How do you study an ODE in matrix form in a Hilbert space?

To study an ODE in matrix form in a Hilbert space, we use techniques from functional analysis and linear algebra. This involves representing the ODE as a matrix equation, finding the eigenvalues and eigenvectors of the matrix, and using these to solve the ODE.

5. What are some applications of studying ODEs in matrix form in a Hilbert space?

Studying ODEs in matrix form in a Hilbert space has many applications in physics, engineering, and other fields. It can be used to model and understand complex systems, such as fluid flow, electrical circuits, and chemical reactions. It also has applications in control theory, signal processing, and optimization problems.

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