Solving Unstable ODE: Theory, Stability & Continuity

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In summary, it is important to confirm the accuracy of your numerical solution by comparing it with an analytic solution for simple cases.
  • #1
muzialis
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Hello there,

I am solving numerically the ODE

$$ \dot{y} = min \, (y, A) + B\, sin(t)$$ , A,B being constant.

I obtain a very "wiggled" solution which is very fine to me actually, as it echoes the problem I am studying.
However, as the numerical solution scheme is quite "rudimentary" I am wondering if I am getting an accurate answer.

In this respect I am wondering if somebody could point me towards a suitable theory for ODE to study their well-posedness, continuity with respect to inital data, stability.
I am no expert, but I understand the problems one would encounter if trying to solve the heat equation with negative conductvity!

The ODE, in the regime $$ y(t) < A$$ is of they type $$ \dot{y} = y + f(t)$$ which is prone to diverging exponentially.
I am trying to understand if the solution I find is meanigful or just "computer noise".

Thanks
 
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  • #2
muzialis said:
Hello there,

I am solving numerically the ODE

$$ \dot{y} = min \, (y, A) + B\, sin(t)$$ , A,B being constant.

I obtain a very "wiggled" solution which is very fine to me actually, as it echoes the problem I am studying.
However, as the numerical solution scheme is quite "rudimentary" I am wondering if I am getting an accurate answer.

In this respect I am wondering if somebody could point me towards a suitable theory for ODE to study their well-posedness, continuity with respect to inital data, stability.
I am no expert, but I understand the problems one would encounter if trying to solve the heat equation with negative conductvity!

The ODE, in the regime $$ y(t) < A$$ is of they type $$ \dot{y} = y + f(t)$$ which is prone to diverging exponentially.
I am trying to understand if the solution I find is meanigful or just "computer noise".

Thanks

The ODE looks simple enough that you could solve it analytically for an example case or two. For example, suppose ##y(0) = y_0 < A##. Then initially your ODE is just ##\dot{y} = y(t) + B\sin(t)##, as you said, which has solution ##y(t) = (y_0+B/2)e^t - (B/2)(\sin t + \cos t)## (double-check that). This solution is valid until it grows to ##y(t_1) = A##. At this point it must satisfy the ODE ##\dot{y} = A + B\sin t##, which has solution ##y(t) = y(t_1) + A(t-t_1) - B(\cos t - \cos t_1)##. You can find ##t_1## by setting ##y(t_1) = A## in your first solution for ##t<t_1##, and ##y(t_1)## is just A. (You will probably have to solve numerically for ##t_1##). If your parameter values are such that y(t) dips below A again, you would need to find the time ##t_2## at which that happens and solve the ODE with ##\mbox{min}(y,A) = y## again, and so on.

In this way you can construct a piece-wise analytic solution for some simple parameter choices which you can test against your numerical solution.
 

1. What is an unstable ODE?

An unstable ODE (ordinary differential equation) is an equation that does not have a unique solution and can exhibit chaotic behavior. This means that small changes in the initial conditions can result in significantly different solutions, making it difficult to accurately predict the behavior of the system over time.

2. What is the theory behind solving unstable ODEs?

The theory behind solving unstable ODEs involves understanding the concept of stability. In order for an ODE to be stable, it must have a unique solution for a given set of initial conditions. To solve an unstable ODE, one must use numerical methods such as Euler's method or Runge-Kutta methods, which approximate the solution by taking small steps and using iterative calculations.

3. How do you determine the stability of an ODE?

The stability of an ODE can be determined by analyzing the eigenvalues of the system's Jacobian matrix. If all eigenvalues have negative real parts, the system is stable, but if any eigenvalue has a positive real part, the system is unstable. Additionally, the location of the eigenvalues in the complex plane can also indicate the type of stability (e.g. stable, unstable, or marginally stable).

4. What is the importance of continuity in solving unstable ODEs?

Continuity is crucial in solving unstable ODEs because it ensures that the solution is well-defined and does not exhibit any sudden jumps or discontinuities. Without continuity, the solution may not accurately represent the behavior of the system and can lead to incorrect predictions. Therefore, it is important to consider continuity when using numerical methods to solve unstable ODEs.

5. Can unstable ODEs be solved analytically?

In general, unstable ODEs cannot be solved analytically due to their chaotic behavior and the lack of a unique solution. However, in some special cases, such as linear or separable ODEs, an analytical solution may exist. But for most unstable ODEs, numerical methods must be used to approximate the solution.

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