Implicit Euler scheme and stability

In summary, we can find the fixed points of the implicit Euler scheme and investigate their stability by setting the scheme equal to the differential equation y'=y(1-y) and solving for the fixed points. The stability of these fixed points can change depending on the value of h, the step size used in the scheme. We must also consider constraints on the acceptable values of h, such as ensuring that g'(y) > 0 at every fixed point to avoid oscillatory solutions.
  • #1
wel
Gold Member
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Find the fixed points of the implicit Euler scheme
\begin{equation} y_{n+1}-y_{n}= hf(t_{n+1},y_{n+1})
\end{equation}
when applied to the differential equation [itex]y'=y(1-y)[/itex] and investigate their stability?

=>
implicit Euler scheme
\begin{equation} y_{n+1}-y_{n}= hf(t_{n+1},y_{n+1})
\end{equation}

$y'=y(1-y)$
\begin{equation} y_{n+1}=y_{n}+hy_{n+1}(1-y_{n+1})
\end{equation}
\begin{equation} y_{n+1}=y_{n}+hy_{n+1}-hy^2_{n+1}
\end{equation}

For fixed points
[itex]y_{n+1}=y_{n}[/itex]
\begin{equation} y_{n}=y_{n}+hy_{n}-hy^2_{n}
\end{equation}
[itex]y_{n}=0[/itex] or [itex]1[/itex]

I got problem with stability but this is what I have done

[itex]y_{n}= \alpha +\epsilon^n[/itex], [itex]y_{n+1}= \alpha +\epsilon^{n+1}[/itex],
\begin{equation} \alpha +\epsilon^{n+1}= \alpha +\epsilon^n + h (\alpha +\epsilon^{n+1})(1-\alpha -\epsilon^{n+1}) \end{equation}
\begin{equation} \epsilon^{n+1}= \epsilon^n + h (\alpha +\epsilon^{n+1})(1-\alpha -\epsilon^{n+1}) \end{equation}
When $y_{n}=0=\alpha$
\begin{equation} \epsilon^{n+1}= \epsilon^n + h \epsilon^{n+1}(1-\epsilon^{n+1}) \end{equation}

I don't what to say or do after that to determine the stability.

When [itex]y_{n}=1=\alpha[/itex]
\begin{equation} \epsilon^{n+1}= \epsilon^n - h \epsilon^{n+1}(1+\epsilon^{n+1}) \end{equation}

same again what can say about with my answer to investigate the stability.
 
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  • #2
wel said:
Find the fixed points of the implicit Euler scheme
\begin{equation} y_{n+1}-y_{n}= hf(t_{n+1},y_{n+1})
\end{equation}
when applied to the differential equation [itex]y'=y(1-y)[/itex] and investigate their stability?

=>
implicit Euler scheme
\begin{equation} y_{n+1}-y_{n}= hf(t_{n+1},y_{n+1})
\end{equation}

$y'=y(1-y)$
\begin{equation} y_{n+1}=y_{n}+hy_{n+1}(1-y_{n+1})
\end{equation}
\begin{equation} y_{n+1}=y_{n}+hy_{n+1}-hy^2_{n+1}
\end{equation}

For fixed points
[itex]y_{n+1}=y_{n}[/itex]
\begin{equation} y_{n}=y_{n}+hy_{n}-hy^2_{n}
\end{equation}
[itex]y_{n}=0[/itex] or [itex]1[/itex]

I got problem with stability but this is what I have done

[itex]y_{n}= \alpha +\epsilon^n[/itex], [itex]y_{n+1}= \alpha +\epsilon^{n+1}[/itex],

I think you mean [itex]y_n = \alpha + \epsilon_n[/itex], etc.

\begin{equation} \alpha +\epsilon^{n+1}= \alpha +\epsilon^n + h (\alpha +\epsilon^{n+1})(1-\alpha -\epsilon^{n+1}) \end{equation}
\begin{equation} \epsilon^{n+1}= \epsilon^n + h (\alpha +\epsilon^{n+1})(1-\alpha -\epsilon^{n+1}) \end{equation}
When $y_{n}=0=\alpha$
\begin{equation} \epsilon^{n+1}= \epsilon^n + h \epsilon^{n+1}(1-\epsilon^{n+1}) \end{equation}

I don't what to say or do after that to determine the stability.

If [tex]
y_{n+1} = g(y_n)
[/tex] and [itex]y^{*} = g(y^{*})[/itex] is a fixed point, then one can set [itex]y_n = y^{*} + \epsilon_n[/itex] and expand [itex]g[/itex] in a taylor series to obtain [tex]
\epsilon_{n+1} = g'(y^{*})\epsilon_n + O(\epsilon_n^2).
[/tex]
Thus if [itex]g'(y^{*}) \neq 0[/itex] then for [itex]|\epsilon_0| \ll 1[/itex] one has initially
[tex]
\epsilon_n = (g'(y^{*}))^n \epsilon_0
[/tex] and the fixed point will then be stable if [itex]0 < |g'(y^{*})| < 1[/itex] and unstable if [itex]|g'(y^{*})| > 1[/itex]. If [itex]|g'(y^{*})| = 0[/itex] or [itex]|g'(y^{*})| = 1[/itex] then further investigation is necessary.

Here you have [tex]
y_{n+1} - y_n = hy_{n+1}(1 - y_{n+1})
[/tex] so that [tex]
g(y_n) - y_n = hg(y_n)(1 - g(y_n))
[/tex] and it may be easier to differentiate implicitly with respect to [itex]y_n[/itex] than to solve for [itex]g(y_n)[/itex] and then differentiate.
 
  • #3
so from there
\begin{equation}
g(y_{n})-y_{n}=hg(y_{n})(1-g(y_{n}))
\end{equation}
\begin{equation}
g(y*+\epsilon_{n})-y*+\epsilon_{n}=hg(y*+\epsilon_{n})(1-g(y*+\epsilon_{n})
\end{equation}
i guess do the taylor expaninsion but you get nothing to determine the stability
 
  • #4
wel said:
so from there
\begin{equation}
g(y_{n})-y_{n}=hg(y_{n})(1-g(y_{n}))
\end{equation}
\begin{equation}
g(y*+\epsilon_{n})-y*+\epsilon_{n}=hg(y*+\epsilon_{n})(1-g(y*+\epsilon_{n})
\end{equation}
i guess do the taylor expaninsion but you get nothing to determine the stability

You certainly don't want to do that. Instead differentiate
[tex]
g(y) - y = hg(y)(1 - g(y))
[/tex] implicitly with respect to [itex]y[/itex] as I suggested. This gives you [itex]g'(y)[/itex] as a function of [itex]h[/itex] and [itex]g(y)[/itex] and you can then set [itex]y = g(y) = 0[/itex] or [itex]y = g(y) = 1[/itex] as appropriate.
 
  • #5
pasmith said:
You certainly don't want to do that. Instead differentiate
[tex]
g(y) - y = hg(y)(1 - g(y))
[/tex] implicitly with respect to [itex]y[/itex] as I suggested. This gives you [itex]g'(y)[/itex] as a function of [itex]h[/itex] and [itex]g(y)[/itex] and you can then set [itex]y = g(y) = 0[/itex] or [itex]y = g(y) = 1[/itex] as appropriate.

So whay saying is that to differentiate this
[tex]
g(y) - y = hg(y)(1 - g(y))
[/tex]
[tex]
g'(y) =1-h(1 - g(y)-g(y))
[/tex]
[tex]
g'(y) =1-h(1-2g(y))
[/tex]
so
[tex]
y =g(y)=0
[/tex]
[tex]
g'(y) =1-h
[/tex]

[tex]
y =g(y)=1
[/tex]
[tex]
g'(y) =1+h
[/tex]
So what can i say with these results or did made any mistakes sir?
 
Last edited:
  • #6
wel said:
So whay saying is that to differentiate this
[tex]
g(y) - y = hg(y)(1 - g(y))
[/tex]
[tex]
g'(y) =1-h(1 - g(y)-g(y))
[/tex]

You should have [tex]
g'(y) - 1 = hg'(y) - h(2g(y)g'(y))
[/tex] so that [tex]
g'(y) = \frac{1}{1 - h + 2hg(y)}.
[/tex]
Stability of the fixed points can therefore change depending on the value of [itex]h > 0[/itex]. You will want to bear in mind the following:
  • We want the fixed points of the iteration to share the same stability as the corresponding fixed points of the original ODE. This may impose constraints on the acceptable values of [itex]h[/itex], which is not a parameter occurring in the original ODE.
  • The ODE whose solution you are approximating is [tex]\dot y = y(1- y),[/tex] which is first-order, one-dimensional and autonomous, so its solutions are constant or strictly monotonic. But the solution of [tex]
    \epsilon_{n+1} = A\epsilon_n
    [/tex] is oscillatory if [itex]A < 0[/itex]: [itex]\epsilon_{n} = (-1)^n|A|^n \epsilon_0[/itex]. Thus we require [itex]g'(y) > 0[/itex] at every fixed point. This again may impose constraints on the acceptable values of [itex]h[/itex].
 
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  • #7
wel said:
I don't what to say or do after that to determine the stability.
Break the problem down into parts.

When you are using implicit Euler you have to solve for ## y_{k+1} ## given a previous value ## y_k ##. Your goal is to solve ## y_{k+1} -y_k = hy_{k+1}(1-y_{k+1}) ##. Apparently you are asked to use a fixed point iteration scheme to do this part of the job. Let ## y_{k+1,0} \equiv y_k ##. Now iteratively solve for ## y_{k+1,n+1} = y_k + hy_{k+1,n}(1-y_{k+1,n}) ##.

Question #1: Does the sequence ## \{y_{k+1,0}, y_{k+1,1}, y_{k+1,2}, \cdots \} ## converge to some value ##y_{k+1} ##? If it doesn't, it's obviously not stable.

Question #2: If it does converge, does the sequence ## \{ y_k,y_{k+1},y_{k+2},\cdots \} ## converge toward the fixed point? If it doesn't it's also not stable (but not so obviously).
 
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Related to Implicit Euler scheme and stability

1. What is the Implicit Euler scheme?

The Implicit Euler scheme is a numerical method used for approximating the solution to a differential equation. It is an implicit method, meaning that the new value of the solution depends on its own value from the previous time step.

2. How does the Implicit Euler scheme work?

The Implicit Euler scheme uses the slope of the differential equation at the current time step to estimate the value of the solution at the next time step. This is done by solving an algebraic equation, rather than using the explicit formula used in the Forward Euler method.

3. What is stability in the context of the Implicit Euler scheme?

Stability refers to the behavior of the numerical solution as the step size (or time increment) used in the Implicit Euler scheme is changed. A stable scheme will produce a solution that does not grow uncontrollably as the step size is decreased, while an unstable scheme will produce a solution that becomes increasingly inaccurate.

4. How is stability determined for the Implicit Euler scheme?

Stability can be determined by analyzing the stability region of the numerical method. The stability region is a region in the complex plane where the numerical method will produce a stable solution. The size and shape of this region depend on the specific characteristics of the differential equation being solved.

5. What are the advantages and disadvantages of using the Implicit Euler scheme?

One advantage of the Implicit Euler scheme is that it is unconditionally stable, meaning that it can handle larger step sizes and more difficult differential equations without becoming unstable. However, it can be computationally more expensive than other numerical methods and may require more iterations to reach a desired level of accuracy.

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