Advanced numerical solution of differential equation

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SUMMARY

The explicit Runge-Kutta scheme applied to the differential equation \(y' = y(1-y)\) exhibits two spurious fixed points when the step size \(h > 2\). The true fixed points are \(y = 0\) and \(y = 1\). The iteration \(y_{n+1} = y_n + \frac{h}{2} [f(t,y_{n} + f(t+h, y_{n}+hf(t,y_{n}))]\) leads to an eighth-order polynomial, indicating the presence of additional real roots. Stability analysis reveals that a fixed point \(y\) is stable if \(|g'(y)| < 1\), unstable if \(|g'(y)| > 1\), and indeterminate if \(|g'(y)| = 1.

PREREQUISITES
  • Understanding of explicit Runge-Kutta methods
  • Familiarity with differential equations, specifically \(y' = y(1-y)\)
  • Knowledge of polynomial roots and stability analysis
  • Experience with computer algebra systems (CAS) for polynomial solving
NEXT STEPS
  • Investigate the properties of the explicit Runge-Kutta method for different step sizes
  • Learn about stability criteria for fixed points in iterative methods
  • Explore the use of computer algebra systems (CAS) for solving higher-order polynomials
  • Study the implications of spurious fixed points in numerical methods
USEFUL FOR

Mathematicians, numerical analysts, and students studying numerical methods for differential equations, particularly those interested in stability analysis and fixed point theory.

rickyflair
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Show that the explicit Runge-Kutta scheme
\begin{equation} \frac {y_{n+1} -y_{n}}{h}= \frac{1}{2} [f(t,y_{n} + f(t+h, y_{n}+hk_{1})]
\end{equation}
where $k_{1} = f(t,y_{n})$

applied to the equation $y'= y(1-y)$ has two spurious fixed points if $h>2$.

Briefy describe how you would investigate their stability.

=> my attempt so far
from $y'= y(1-y)$

$y'= 0$

$y=0$ or
$y=1$ which are the true fixed points.
after that i rearranged the runge kutta scheme
\begin{equation} \frac {y_{n+1} -y_{n}}{h}= \frac{1}{2} [f(t,y_{n} + f(t+h, y_{n}+hk_{1})]
\end{equation}
\begin{equation} y_{n+1} = y_{n} + \frac{h}{2} [f(t,y_{n} + f(t+h, y_{n}+hf(t,y_{n})]
\end{equation}
i try to put the fixed points into above scheme and try to get two two Spurious fixed point for $y_{n}$ but i got struck. for the stability to describe i need to get two Spurious fixed point first. but in general please help to describe stability too because this part i really get confuse. Anyone please help me, it will be really helpful for my other problems too if i got this answer correctly.
 
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rickyflair said:
Show that the explicit Runge-Kutta scheme
\begin{equation} \frac {y_{n+1} -y_{n}}{h}= \frac{1}{2} [f(t,y_{n} + f(t+h, y_{n}+hk_{1})]
\end{equation}
where $k_{1} = f(t,y_{n})$

applied to the equation $y'= y(1-y)$ has two spurious fixed points if $h>2$.

Briefy describe how you would investigate their stability.

=> my attempt so far
from $y'= y(1-y)$

$y'= 0$

$y=0$ or
$y=1$ which are the true fixed points.
after that i rearranged the runge kutta scheme
\begin{equation} \frac {y_{n+1} -y_{n}}{h}= \frac{1}{2} [f(t,y_{n} + f(t+h, y_{n}+hk_{1})]
\end{equation}
\begin{equation} y_{n+1} = y_{n} + \frac{h}{2} [f(t,y_{n} + f(t+h, y_{n}+hf(t,y_{n})]
\end{equation}
i try to put the fixed points into above scheme and try to get two two Spurious fixed point for $y_{n}$ but i got struck. for the stability to describe i need to get two Spurious fixed point first. but in general please help to describe stability too because this part i really get confuse. Anyone please help me, it will be really helpful for my other problems too if i got this answer correctly.

Your f(t,y) doesn't actually depend on t, so you may as well drop it and write f(y) = y(1 - y).

A fixed point of the iteration will satisfy y_{n+1} = y_n = y, which gives you
<br /> 0 = f(y + f(y + hf(y))).<br /> Now for y = 0 and y = 1 you have f(y) = 0, so they satisfy the above and are fixed points of the iteration. But f(y + f(y + hf(y))) is here an eighth-order polynomial in y, so it might have other real roots aside from y = 0 and y = 1. But determining that really requires the aid of a CAS.

For stability: a fixed point y of y_{n+1} = g(y_n) is stable if |g&#039;(y)| &lt; 1, unstable if |g&#039;(y)| &gt; 1 and indeterminate at linear order if |g&#039;(y)| = 1.
 
Thank you sir. that was really helpful.
 

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