MHB How Does the Order of Convergence Relate to Numerical Schemes for ODEs?

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The discussion explores the relationship between the order of convergence and numerical schemes for ordinary differential equations (ODEs), specifically focusing on explicit methods for approximating solutions. The analysis begins with the initial value problem (IVP) dy/dx = y, leading to approximations for e using various numerical methods, including Euler's method and higher-order Runge-Kutta methods. A hypothesis is proposed that an explicit numerical scheme yielding a specific limit will have an order of convergence corresponding to its power p. The thread also notes that implicit methods produce different convergence behaviors, with one example approaching e from above. The findings suggest that as the order p increases, the rate of convergence improves, ultimately leading to the Taylor series expansion for e.
MarkFL
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A while back, I dug out a topic I worked on many years ago after taking a course in ordinary differential equations and I was left with an unanswered question, which I thought I would post here. While my question arose from studying numeric methods for approximating the solutions to ODEs, I feel it is probably more of a question in numeric analysis.

I was analyzing the correlation between the approximation methods for definite integrals and for first order initial value problems via the anti-derivative form of the Fundamental Theorem of Calculus. In an attempt to determine the rate of convergence for the various methods, I have observed what I believe to be a pattern, but had difficulty in proving a hypothesis.

I began by using the IVP:

$\displaystyle \frac{dy}{dx}=y$ where $y(0)=1$

and used the explicit numerical schemes to approximate y(1) which led to approximations for $e$.

Analysis of Euler's method (Riemann sum of regular partitions) gave rise to

$\displaystyle e=\lim_{n\to\infty}\left(1+\frac{1}{n} \right)^n$

Use of a limit comparison test shows this scheme to be of order 1.

Analysis of the improved Euler's method (trapezoidal scheme) and the 2nd order Runge-Kutta method (mid-point scheme) which both use Euler's method as a predictor-corrector, show that both give rise to:

$\displaystyle e=\lim_{n\to\infty}\left(1+\frac{1}{n}+\frac{1}{2n^2} \right)^n$

Use of a limit comparison test shows this scheme to be of order 2.

Analysis of the 4th order Runge-Kutta method (Simpson's or prismoidal scheme) gave rise to:

$\displaystyle e=\lim_{n\to\infty}\left(1+\frac{1}{n}+\frac{1}{2n^2}+\frac{1}{6n^3}+\frac{1}{24n^4} \right)^n$

Use of a limit comparison test shows this scheme to be of order 4.

My hypothesis is that an explicit numerical scheme that yields

(1) $\displaystyle e=\lim_{n\to\infty}\left(\sum_{i=0}^{p}\left(\frac{1}{i!n^{i}} \right) \right)^n$

will be of order $p$.

Interestingly, two of the implicit methods yield the formula

$\displaystyle e=\lim_{n\to\infty}\left(\frac{2n+1}{2n-1} \right)^n$

but I did not explore its rate of convergence or what type of formula an implicit method of order $p$ will yield.

While it was a simple enough matter to show that (1) is valid and that as p increases the rate of convergence improves, demonstrating that this rate of convergence increases linearly as $p$ is another matter entirely. I applied L'Hôpital's rule and Maclaurin expansions for logarithmic functions, but to no avail. I also looked into the use of a Taylor formula of order $p$ because of its relationship to the limit comparison test and its use in the derivation of the Runge-Kutta methods and the Maclaurin power series.

If anyone could shed some light on this or post links to relevant material, I would greatly appreciate it! :cool:
 
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Just to verify, I created an Excel sheet with these sequences.
A log-log-plot of n versus the error in the approximation from e, shows the rate of convergence.
And indeed for each approximation sequence we get a line with a slope that corresponds to the order of convergence.
It turns out that a sequence with powers up to 6, has a 6th order of convergence.

The quotient form $(\dfrac {2n+1}{2n-1})^2$ turns out to have convergence order 2.
It is also the only one that approaches e from above instead of from below.
 
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I appreciate you taking the time to verify the rate of convergence up to $p=6$. (Yes)
 
Here's an observation.
Suppose we let p go to infinity, then we get for n=1:

$\qquad (\displaystyle\sum_{p=0}^\infty \dfrac{1}{p! n^p})^n = (1 + \frac 1 {2!} + \frac 1 {3!} + ...)^1 = e$

Hey! We know this sequence!
It is the Taylor expansion of $e^x$ for $x=1$.

And for higher values of n, we simply get $(e^{1/n})^n = e$.
So in the ultimate case we get a constant sequence of just e.
 
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We all know the definition of n-dimensional topological manifold uses open sets and homeomorphisms onto the image as open set in ##\mathbb R^n##. It should be possible to reformulate the definition of n-dimensional topological manifold using closed sets on the manifold's topology and on ##\mathbb R^n## ? I'm positive for this. Perhaps the definition of smooth manifold would be problematic, though.

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