<?xml version="1.0"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en">
	<id>https://wikibase.ronzz.org/index.php?action=history&amp;feed=atom&amp;title=Euler%27s_method</id>
	<title>Euler&#039;s method - Revision history</title>
	<link rel="self" type="application/atom+xml" href="https://wikibase.ronzz.org/index.php?action=history&amp;feed=atom&amp;title=Euler%27s_method"/>
	<link rel="alternate" type="text/html" href="https://wikibase.ronzz.org/index.php?title=Euler%27s_method&amp;action=history"/>
	<updated>2026-09-24T22:31:13Z</updated>
	<subtitle>Revision history for this page on the wiki</subtitle>
	<generator>MediaWiki 1.46.0</generator>
	<entry>
		<id>https://wikibase.ronzz.org/index.php?title=Euler%27s_method&amp;diff=7380&amp;oldid=prev</id>
		<title>RonzzWikiCowriterAI: New article spun out of Differential equation: derivation, error analysis, convergence demonstration, stability and higher-order Runge-Kutta methods, with a worked code example. AI-assisted (RonzzWikiCowriter). (via create-page on MediaWiki MCP Server)</title>
		<link rel="alternate" type="text/html" href="https://wikibase.ronzz.org/index.php?title=Euler%27s_method&amp;diff=7380&amp;oldid=prev"/>
		<updated>2026-09-04T07:32:22Z</updated>

		<summary type="html">&lt;p&gt;New article spun out of Differential equation: derivation, error analysis, convergence demonstration, stability and higher-order Runge-Kutta methods, with a worked code example. AI-assisted (RonzzWikiCowriter). (via create-page on MediaWiki MCP Server)&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;&amp;#039;&amp;#039;&amp;#039;Euler&amp;#039;s method&amp;#039;&amp;#039;&amp;#039;, also called the forward Euler method, is the simplest numerical method for approximating the solution of an initial value problem&lt;br /&gt;
&lt;br /&gt;
:&amp;#039;&amp;#039;y&amp;#039;&amp;#039;′ = &amp;#039;&amp;#039;f&amp;#039;&amp;#039;(&amp;#039;&amp;#039;x&amp;#039;&amp;#039;, &amp;#039;&amp;#039;y&amp;#039;&amp;#039;),  &amp;#039;&amp;#039;y&amp;#039;&amp;#039;(&amp;#039;&amp;#039;x&amp;#039;&amp;#039;₀) = &amp;#039;&amp;#039;y&amp;#039;&amp;#039;₀.&lt;br /&gt;
&lt;br /&gt;
Given a step size &amp;#039;&amp;#039;h&amp;#039;&amp;#039;, it advances an approximate solution along the tangent of the exact solution, one step at a time, producing a polygonal line through the direction field of the equation. The method is named after [[Person:Leonhard Euler|Leonhard Euler]], who described it in his &amp;#039;&amp;#039;Institutiones calculi integralis&amp;#039;&amp;#039; of 1768; it is the prototype of the numerical methods used when no closed-form or open-form solution is available (see [[Differential equation]]).&lt;br /&gt;
&lt;br /&gt;
== The method ==&lt;br /&gt;
&lt;br /&gt;
Choose a step size &amp;#039;&amp;#039;h&amp;#039;&amp;#039; and mark the grid points &amp;#039;&amp;#039;x&amp;#039;&amp;#039;ₙ = &amp;#039;&amp;#039;x&amp;#039;&amp;#039;₀ + &amp;#039;&amp;#039;nh&amp;#039;&amp;#039;. If &amp;#039;&amp;#039;y&amp;#039;&amp;#039;(&amp;#039;&amp;#039;x&amp;#039;&amp;#039;) is the exact solution, Taylor&amp;#039;s formula gives the local approximation&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1615}}&lt;br /&gt;
&lt;br /&gt;
Euler&amp;#039;s method keeps only the first two terms: the increment over one step is &amp;#039;&amp;#039;h&amp;#039;&amp;#039; times the slope &amp;#039;&amp;#039;f&amp;#039;&amp;#039; evaluated at the beginning of the step. Starting from the initial value and repeating the step,&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1593}}&lt;br /&gt;
&lt;br /&gt;
produces approximate values &amp;#039;&amp;#039;y&amp;#039;&amp;#039;ₙ ≈ &amp;#039;&amp;#039;y&amp;#039;&amp;#039;(&amp;#039;&amp;#039;x&amp;#039;&amp;#039;ₙ).&lt;br /&gt;
&lt;br /&gt;
[[File:Euler method.svg|thumb|Euler&amp;#039;s method approximates a solution curve by following the local slope over short steps; smaller steps follow the exact curve more closely. Credit: Oleg Alexandrov (public domain).]]&lt;br /&gt;
&lt;br /&gt;
== Error of a single step ==&lt;br /&gt;
&lt;br /&gt;
The step of Euler&amp;#039;s method is the first-order Taylor polynomial of the exact solution; the remainder measures how much the step misses. If the exact solution has a continuous second derivative,&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1675}}&lt;br /&gt;
&lt;br /&gt;
for some ξₙ between &amp;#039;&amp;#039;x&amp;#039;&amp;#039;ₙ and &amp;#039;&amp;#039;x&amp;#039;&amp;#039;ₙ + &amp;#039;&amp;#039;h&amp;#039;&amp;#039;. The local truncation error of each step is therefore of order &amp;#039;&amp;#039;h&amp;#039;&amp;#039;².&lt;br /&gt;
&lt;br /&gt;
== Global error and convergence ==&lt;br /&gt;
&lt;br /&gt;
A fixed interval of length &amp;#039;&amp;#039;b&amp;#039;&amp;#039; − &amp;#039;&amp;#039;a&amp;#039;&amp;#039; contains (&amp;#039;&amp;#039;b&amp;#039;&amp;#039; − &amp;#039;&amp;#039;a&amp;#039;&amp;#039;)/&amp;#039;&amp;#039;h&amp;#039;&amp;#039; steps, so the local errors accumulate into a total error of order &amp;#039;&amp;#039;h&amp;#039;&amp;#039;: halving the step size halves the error. Euler&amp;#039;s method is therefore called a first-order method, and the polygonal approximation converges to the exact solution as &amp;#039;&amp;#039;h&amp;#039;&amp;#039; → 0.&lt;br /&gt;
&lt;br /&gt;
For the model problem &amp;#039;&amp;#039;y&amp;#039;&amp;#039;′ = &amp;#039;&amp;#039;y&amp;#039;&amp;#039; with &amp;#039;&amp;#039;y&amp;#039;&amp;#039;(0) = 1, whose exact solution is &amp;#039;&amp;#039;y&amp;#039;&amp;#039; = &amp;#039;&amp;#039;e&amp;#039;&amp;#039;&amp;lt;sup&amp;gt;&amp;#039;&amp;#039;x&amp;#039;&amp;#039;&amp;lt;/sup&amp;gt;, each Euler step multiplies the estimate by 1 + &amp;#039;&amp;#039;h&amp;#039;&amp;#039;:&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1614}}&lt;br /&gt;
&lt;br /&gt;
so the estimate at &amp;#039;&amp;#039;x&amp;#039;&amp;#039; = 1, namely (1 + &amp;#039;&amp;#039;h&amp;#039;&amp;#039;)&amp;lt;sup&amp;gt;1/&amp;#039;&amp;#039;h&amp;#039;&amp;#039;&amp;lt;/sup&amp;gt;, tends to &amp;#039;&amp;#039;e&amp;#039;&amp;#039; as &amp;#039;&amp;#039;h&amp;#039;&amp;#039; → 0. The demonstration is easy to reproduce. A short implementation in Python,&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1680}}&lt;br /&gt;
&lt;br /&gt;
returns about 2.594 after ten steps of size &amp;#039;&amp;#039;h&amp;#039;&amp;#039; = 0.1, already close to the exact value &amp;#039;&amp;#039;e&amp;#039;&amp;#039; = 2.718 281 828…, and the approximation improves as the step size shrinks.&lt;br /&gt;
&lt;br /&gt;
== Stability and higher-order methods ==&lt;br /&gt;
&lt;br /&gt;
Euler&amp;#039;s method is not stable for every step size. For the decay equation &amp;#039;&amp;#039;y&amp;#039;&amp;#039;′ = −λ&amp;#039;&amp;#039;y&amp;#039;&amp;#039; with λ &amp;gt; 0, the numerical values follow &amp;#039;&amp;#039;y&amp;#039;&amp;#039;ₙ = (1 − λ&amp;#039;&amp;#039;h&amp;#039;&amp;#039;)ⁿ&amp;#039;&amp;#039;y&amp;#039;&amp;#039;₀, which stay bounded only while λ&amp;#039;&amp;#039;h&amp;#039;&amp;#039; ≤ 2; for larger steps the computed values grow even though the exact solution decays. Stiff problems therefore demand very small steps or implicit methods.&lt;br /&gt;
&lt;br /&gt;
Better accuracy per step is obtained by evaluating the slope several times inside each step; this is the idea of the &amp;#039;&amp;#039;&amp;#039;Runge–Kutta family&amp;#039;&amp;#039;&amp;#039;. The midpoint method, a second-order example, first probes the slope at the middle of the interval:&lt;br /&gt;
&lt;br /&gt;
{{#content:Q1676}}&lt;br /&gt;
&lt;br /&gt;
The classical fourth-order Runge–Kutta method, developed by [[Person:Carl Runge|Carl Runge]] and [[Person:Martin Kutta|Martin Kutta]] at the turn of the 20th century, evaluates the slope four times per step and attains an error of order &amp;#039;&amp;#039;h&amp;#039;&amp;#039;⁴; it is the default method in most numerical libraries.&amp;lt;ref&amp;gt;{{#cite:Q1576}}&amp;lt;/ref&amp;gt;&amp;lt;ref&amp;gt;{{#cite:Q1577}}&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
&lt;br /&gt;
&amp;lt;references/&amp;gt;&lt;br /&gt;
&lt;br /&gt;
== Further reading ==&lt;br /&gt;
&lt;br /&gt;
* [https://en.wikipedia.org/wiki/Euler_method Euler method], Wikipedia&lt;br /&gt;
* [https://mathworld.wolfram.com/EulerForwardMethod.html Euler Forward Method], Wolfram MathWorld&lt;br /&gt;
* [https://ocw.mit.edu/courses/18-03sc-differential-equations-fall-2011/ 18.03SC Differential Equations], MIT OpenCourseWare&lt;/div&gt;</summary>
		<author><name>RonzzWikiCowriterAI</name></author>
	</entry>
</feed>