MHB Need explanation-hyperbolic system of equations

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The discussion focuses on the conditions under which a hyperbolic system of partial differential equations (PDEs) can be reduced to an ordinary differential equation (ODE) system. It establishes that the matrix A must have n distinct real eigenvalues for this reduction to occur, which allows for the identification of characteristic directions where the PDE simplifies. The participants explore the mathematical derivations involving linear combinations of the equations and the implications of eigenvalues and eigenvectors in this context. They also discuss the method of characteristics as a means to achieve this reduction and clarify the assumptions necessary for the eigenvalue conditions to hold. Ultimately, the conversation emphasizes the relationship between the structure of the matrix A and the hyperbolic nature of the system.
mathmari
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Hey! :o

I have the following in my notes:

$$u_t+A(x,t,u)u_x=b(x,t,u) \ \ \ \ \ \ \ \ \ \ (1)$$
$$u=(u_1, \dots, u_n), b=(b_1, \dots, b_n)$$
$$A=[a_{ij}], i,j = 1, \dots, n$$

We set the question if there are characteristic directions at the path of which the PDE system $(1)$ is reduced to an ODE system.

So we take linear combinations of the above equations.

We use the vector $\gamma=(\gamma_1, \dots, \gamma_n) \ \ \ \ \ \ \ \ \ \ (2)$.

We take $\gamma^T(u_t+Au_x)=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (3)$.

We want to conclude to a form of total derivative of the linear combination of $u$.

That means:(we consider that $u_j=u_j(x(t),t)$)

$$\frac{d}{dt}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)=\frac{\partial}{\partial{t}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)+\frac{dx}{dt} \frac{\partial}{\partial{x}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)$$

and we define $\frac{dx}{dt}=\lambda$

The relation above means:
$$m^T(\frac{\partial{u}}{\partial{t}}+\lambda\frac{\partial{u}}{\partial{x}})=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (4)$$

From the relation $(3)$ and $(4)$, we see that $\gamma=m=(\gamma_1, \dots, \gamma_n)$ and that $\gamma^TA=\lambda \gamma^T$

$\lambda:$ eigenvalue of the matrix $A$

$\gamma^T:$ left eigenvector of $A$

We define the characteristic directions:

$\frac{dx}{dt}=\lambda$, so $\gamma^T(\frac{\partial{u}}{\partial{t}}+\frac{dx}{dt}
\frac{\partial{u}}{\partial{x}})=\gamma^Tb$

$\gamma^T \frac{du}{dt}=\gamma^Tb$

(To can reduce the system to a PDE system, the $\frac{dx}{dt}=\lambda$ must exist. To be able to apply this method, the matrix $A$ should have $n$ real values.)

We conclude that to reduce the PDE system to an ODE system, the matrix $A$ should have $n$ discrete real eigenvalues.

In this case we say that the system is hyperbolic.
Could you explain me what we have done here? I got stuck right now... (Wondering)
 
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mathmari said:
Hey! :o

I have the following in my notes:

$$u_t+A(x,t,u)u_x=b(x,t,u) \ \ \ \ \ \ \ \ \ \ (1)$$
$$u=(u_1, \dots, u_n), b=(b_1, \dots, b_n)$$
$$A=[a_{ij}], i,j = 1, \dots, n$$

We set the question if there are characteristic directions at the path of which the PDE system $(1)$ is reduced to an ODE system.

So we take linear combinations of the above equations.

We use the vector $\gamma=(\gamma_1, \dots, \gamma_n) \ \ \ \ \ \ \ \ \ \ (2)$.

We take $\gamma^T(u_t+Au_x)=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (3)$.

We want to conclude to a form of total derivative of the linear combination of $u$.

That means:(we consider that $u_j=u_j(x(t),t)$)

$$\frac{d}{dt}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)=\frac{\partial}{\partial{t}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)+\frac{dx}{dt} \frac{\partial}{\partial{x}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)$$

and we define $\frac{dx}{dt}=\lambda$

The relation above means:
$$m^T(\frac{\partial{u}}{\partial{t}}+\lambda\frac{\partial{u}}{\partial{x}})=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (4)$$

From the relation $(3)$ and $(4)$, we see that $\gamma=m=(\gamma_1, \dots, \gamma_n)$ and that $\gamma^TA=\lambda \gamma^T$

$\lambda:$ eigenvalue of the matrix $A$

$\gamma^T:$ left eigenvector of $A$

We define the characteristic directions:

$\frac{dx}{dt}=\lambda$, so $\gamma^T(\frac{\partial{u}}{\partial{t}}+\frac{dx}{dt}
\frac{\partial{u}}{\partial{x}})=\gamma^Tb$

$\gamma^T \frac{du}{dt}=\gamma^Tb$

(To can reduce the system to a PDE system, the $\frac{dx}{dt}=\lambda$ must exist. To be able to apply this method, the matrix $A$ should have $n$ real values.)

We conclude that to reduce the PDE system to an ODE system, the matrix $A$ should have $n$ discrete real eigenvalues.

In this case we say that the system is hyperbolic.
Could you explain me what we have done here? I got stuck right now... (Wondering)

What are characteristic directions at the path of which the PDE system $(1)$ is reduced to an ODE system? (Wondering)
 
Hey! (Blush)

mathmari said:
We set the question if there are characteristic directions at the path of which the PDE system $(1)$ is reduced to an ODE system.

So we take linear combinations of the above equations.

We use the vector $\gamma=(\gamma_1, \dots, \gamma_n) \ \ \ \ \ \ \ \ \ \ (2)$.

We take $\gamma^T(u_t+Au_x)=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (3)$.

We want to conclude to a form of total derivative of the linear combination of $u$.

Can it be that it should be: "linear combination of the total derivative of $u$ with respect to $t$"?
That means:(we consider that $u_j=u_j(x(t),t)$)

$$\frac{d}{dt}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)=\frac{\partial}{\partial{t}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)+\frac{dx}{dt} \frac{\partial}{\partial{x}}(\gamma_1u_1+\gamma_2u_2 +\dots+\gamma_n u_n)$$

and we define $\frac{dx}{dt}=\lambda$

The relation above means:
$$m^T(\frac{\partial{u}}{\partial{t}}+\lambda\frac{\partial{u}}{\partial{x}})=\gamma^Tb \ \ \ \ \ \ \ \ \ \ (4)$$

It seems the assumption is made that (3) can be written as an ODE that is a linear combination of $\frac{du_j}{dt}$. (Wondering)

That would imply there is some vector $m$ such that:
$$m^T \frac{du}{dt} = g(t)$$
where $g(t) = \gamma^T b(t)$.
From the relation $(3)$ and $(4)$, we see that $\gamma=m=(\gamma_1, \dots, \gamma_n)$ and that $\gamma^TA=\lambda \gamma^T$

$\lambda:$ eigenvalue of the matrix $A$

$\gamma^T:$ left eigenvector of $A$

I think I'm seeing another assumption here.
That from $\gamma^T x_t(t) u_x(t) = \gamma^T A(t) u_x(t)$ we can assume that $\gamma^T x_t(t) = \gamma^T A(t)$. (Wondering)

If that holds true, we get that the scalar $x_t(t)$ is an eigenvalue of $A(t)$.
We define the characteristic directions:

$\frac{dx}{dt}=\lambda$, so $\gamma^T(\frac{\partial{u}}{\partial{t}}+\frac{dx}{dt}
\frac{\partial{u}}{\partial{x}})=\gamma^Tb$

$\gamma^T \frac{du}{dt}=\gamma^Tb$

(To can reduce the system to a PDE system, the $\frac{dx}{dt}=\lambda$ must exist. To be able to apply this method, the matrix $A$ should have $n$ real values.)

We conclude that to reduce the PDE system to an ODE system, the matrix $A$ should have $n$ discrete real eigenvalues.

In this case we say that the system is hyperbolic.

If the assumptions hold and $A(t)$ is diagonalizable, we should be able to apply a change of variables and reduce the system to something like:
$$\delta^T(v_t + D(t) v_x) = \delta^T c(t)$$
where $\delta$ is some constant vector just like $\gamma$.

Perhaps this is considered a hyperbolic form? (Wondering)
mathmari said:
What are characteristic directions at the path of which the PDE system $(1)$ is reduced to an ODE system? (Wondering)

I have just found Method_of_characteristics on wiki that seems to describe this method.
 
I like Serena said:
Can it be that it should be: "linear combination of the total derivative of $u$ with respect to $t$"?

In my notes, it is as I wrote it:
"We want to conclude to a form of total derivative of the linear combination of $u$."

Does it mean that we are looking for the derivative of $(\gamma_1 u_1 +\gamma_2 u_2+ \dots +\gamma_n u_n)$ ??
What does the part "a form of total derivative" mean?? (Wondering)
I like Serena said:
It seems the assumption is made that (3) can be written as an ODE that is a linear combination of $\frac{du_j}{dt}$. (Wondering)

That would imply there is some vector $m$ such that:
$$m^T \frac{du}{dt} = g(t)$$
where $g(t) = \gamma^T b(t)$.

I haven't understood this part... (Doh) (Worried)
I like Serena said:
I think I'm seeing another assumption here.
That from $\gamma^T x_t(t) u_x(t) = \gamma^T A(t) u_x(t)$ we can assume that $\gamma^T x_t(t) = \gamma^T A(t)$. (Wondering)

If that holds true, we get that the scalar $x_t(t)$ is an eigenvalue of $A(t)$.

$(3): \gamma^T(u_t+Au_x)= \gamma^Tb$
$(4): m^T(u_t+\lambda u_x)=\gamma^Tb$

$\Rightarrow \gamma^T(u_t+Au_x)=m^T(u_t+\lambda u_x) \Rightarrow \gamma^T u_t+\gamma^T A u_x=m^T u_t+m^T \lambda u_x \Rightarrow \gamma^T=m^T \text{ AND } \gamma^T A= m^T \lambda \overset{\gamma^T=m^T}{\Rightarrow} \gamma^T A=\lambda \gamma^T$$\gamma^T=m^T \Rightarrow \gamma=m$

Is this correct?? (Thinking)

Does it stand that $m^T \lambda=\lambda m^T$ because $\lambda$ is a number?? (Wondering)

Also how do we conlcude that
$\lambda:$ eigenvalue of the matrix $A$
and
$\gamma^T:$ left eigenvector of $A$
??

Do we suppose that these two hold??
I like Serena said:
If the assumptions hold and $A(t)$ is diagonalizable, we should be able to apply a change of variables and reduce the system to something like:
$$\delta^T(v_t + D(t) v_x) = \delta^T c(t)$$
where $\delta$ is some constant vector just like $\gamma$.

Perhaps this is considered a hyperbolic form? (Wondering)

So that the eigenvalues exist means that the matrix has $n$ real values?? (Wondering)
And is that equivalent to that the matrix $A$ is diagonalizable??
Why?? (Sweating)

And also, why do we consider this a hyperbolic form??
 
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There is the following example in my notes:

$$\left.\begin{matrix}
\frac{\partial{u_1}}{\partial{t}}+a \frac{\partial{u_2}}{\partial{x}}=0\\
\frac{\partial{u_2}}{\partial{t}}+b \frac{\partial{u_1}}{\partial{x}}=0
\end{matrix}\right\}$$

$a,b>0$
$\displaystyle{u=u(u_1, u_2)}$

$$A=\begin{bmatrix}
0 & a\\
b & 0
\end{bmatrix}$$

$\displaystyle{u_t+Au_x=0}$

To check if it is hypebolic, we have to find the eigenvalues.
$\displaystyle{det(A-\lambda I)=\lambda^2-ab=0 \Rightarrow \lambda= \pm \sqrt{ab}}$

$\gamma=(\gamma_1, \gamma_2)$

$\displaystyle{\gamma_1(\frac{\partial{u_1}}{\partial{t}}+a \frac{\partial{u_2}}{\partial{x}})+\gamma_2(\frac{\partial{u_2}}{\partial{t}}+b \frac{\partial{u_1}}{\partial{x}})=0}$

$\Rightarrow \displaystyle{\gamma_1(\frac{\partial{u_1}}{\partial{t}}+\frac{b \gamma_2}{\gamma_1} \frac{\partial{u_1}}{\partial{x}})+\gamma_2(\frac{\partial{u_2}}{\partial{t}}+\frac{a \gamma_1}{\gamma_2} \frac{\partial{u_2}}{\partial{x}})=0}$

Since it should be in the form: $\gamma^T(u_t+\lambda u_x)=\gamma^T b$, it should be: $\displaystyle{\frac{b \gamma_2}{\gamma_1}=\frac{a \gamma_1}{\gamma_2}}$

We set $\displaystyle{\gamma_1=1}$, so $\displaystyle{\gamma_2^2=\frac{a}{b} \Rightarrow \gamma_2= \pm \sqrt{\frac{a}{b}}}$

We take $\gamma_2=\sqrt{\frac{a}{b}}$:

At the case $\lambda=\sqrt{ab}$:

$\displaystyle{(\frac{\partial{u_1}}{\partial{t}}+\sqrt{ab} \frac{\partial{u_1}}{\partial{x}})+\sqrt{\frac{a}{b}}(\frac{\partial{u_2}}{\partial{t}}+\sqrt{ab} \frac{\partial{u_2}}{\partial{x}})=0}$

$\displaystyle{\frac{\partial}{\partial{t}}(u_1+\sqrt{\frac{a}{b}}u_2)+\sqrt{ab} \frac{\partial}{\partial{x}}(u_1+\sqrt{\frac{a}{b}}u_2)=0}$

We set $\displaystyle{v_+=u_1+\sqrt{\frac{a}{b}}u_2}$. So we have: $\displaystyle{\frac{\partial{v_+}}{\partial{t}}+\sqrt{ab} \frac{\partial{v_+}}{\partial{x}}=0}$

The characteristic system is:
$$\frac{dt}{1}=\frac{dx}{\sqrt{ab}}=\frac{dv_+}{0}$$

$\displaystyle{v=\text{ constant }, v=u_1+\sqrt{\frac{a}{b}}u_2}$, when $\displaystyle{\frac{dx}{dt}=\sqrt{ab}}$

$\displaystyle{x=\sqrt{ab}t+c \Rightarrow c=x- \sqrt{ab}t}$

$\displaystyle{v}$ is constant when $\displaystyle{x-\sqrt{ab}t}$ is constant.

That means that $$u_1+\sqrt{\frac{a}{b}}u_2=\frac{f(x-\sqrt{ab}t)}{2}$$At the case $\lambda=-\sqrt{ab}$:

We conclude that $\displaystyle{v_-=u_1-\sqrt{\frac{a}{b}}u_2= \text{ constant }}$ when $\displaystyle{x+\sqrt{ab}t}$ is constant.

$$u_1-\sqrt{\frac{a}{b}}u_2=\frac{g(x+\sqrt{ab}t)}{2}$$So $$u_1=f(x-\sqrt{ab}t)+g(x+\sqrt{ab}t)$$
$$u_2=\sqrt{\frac{b}{a}}[f(x-\sqrt{ab}t)-g(x+\sqrt{ab}t)]$$

Instead of $\gamma_2=\sqrt{\frac{a}{b}}$, we could also use $\gamma_2=-\sqrt{\frac{a}{b}}$ and we would get the same results, right?? (Wondering)
 
I like Serena said:
It seems the assumption is made that (3) can be written as an ODE that is a linear combination of $\frac{du_j}{dt}$. (Wondering)

That would imply there is some vector $m$ such that:
$$m^T \frac{du}{dt} = g(t)$$
where $g(t) = \gamma^T b(t)$.

I still don't understand what $m$ is... (Doh)(Worried)(Wondering)
 
mathmari said:
I still don't understand what $m$ is... (Doh)(Worried)(Wondering)

As far as I can tell $m$ is some vector of constants.
It would identify a linear combination.
That's all I've got. (Blush)
 

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