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{{Short description|Second-order
In the [[calculus of variations]] and [[classical mechanics]], the '''Euler–Lagrange equations'''<ref>{{cite book|first=Charles|last=Fox|title=An introduction to the calculus of variations|publisher=Courier Dover Publications|year=1987|isbn=978-0-486-65499-7}}</ref> are a system of second-order [[ordinary differential equation]]s whose solutions are [[stationary point]]s of the given [[action (physics)|action functional]]. The equations were discovered in the 1750s by Swiss mathematician [[Leonhard Euler]] and Italian mathematician [[Joseph-Louis Lagrange]].
Because a differentiable functional is stationary at its local [[maxima and minima|extrema]], the Euler–Lagrange equation is useful for solving [[optimization (mathematics)|optimization]] problems in which, given some functional, one seeks the function minimizing or maximizing it. This is analogous to [[Fermat's theorem (stationary points)|Fermat's theorem]] in [[calculus]], stating that at any point where a differentiable function attains a local extremum its [[derivative (mathematics)|derivative]] is zero.
In [[Lagrangian mechanics]], according to [[Hamilton's principle]] of stationary action, the evolution of a physical system is described by the solutions to the Euler equation for the [[action (physics)#Action (functional)|action]] of the system. In this context Euler equations are usually called '''Lagrange equations'''. In [[classical mechanics]],<ref name="Goldstein"> {{cite book|author1-link=Herbert Goldstein|author2-link=Charles P. Poole|first1=H.
==History==
[[File:Tautochrone curve.gif|thumb|The Euler–Lagrange equation was in connection with their studies of the [[tautochrone]] problem. ]]
The Euler–Lagrange equation was developed in the 1750s by Euler and Lagrange in connection with their studies of the Lagrange solved this problem in 1755 and sent the solution to Euler. Both further developed Lagrange's method and applied it to [[mechanics]], which led to the formulation of [[Lagrangian mechanics]]. Their correspondence ultimately led to the [[calculus of variations]], a term coined by Euler himself in 1766.<ref>[http://numericalmethods.eng.usf.edu/anecdotes/lagrange.pdf A short biography of Lagrange] {{webarchive|url=https://web.archive.org/web/20070714022022/http://numericalmethods.eng.usf.edu/anecdotes/lagrange.pdf |date=2007-07-14 }}</ref>
==Statement==
Let <math>(X,L)</math> be a
Let <math>{\cal P}(a,b,\boldsymbol x_a,\boldsymbol x_b)</math> be the set of smooth paths <math>\boldsymbol q: [a,b] \to X</math> for which <math>\boldsymbol q(a) = \boldsymbol x_a</math> and <math>\boldsymbol q(b) = \boldsymbol
The [[action (physics)|action functional]] <math>S : {\cal P}(a,b,\boldsymbol x_a,\boldsymbol x_b) \to \mathbb{R}</math> is defined via <math display="block"> S[\boldsymbol q] = \int_a^b L(t,\boldsymbol q(t),\dot{\boldsymbol q}(t))\, dt.</math>
A path <math>\boldsymbol q \in {\cal P}(a,b,\boldsymbol x_a,\boldsymbol x_b)</math> is a [[
{{Equation box 1
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Here, <math>\dot{\boldsymbol q}(t) </math> is the time derivative of <math>\boldsymbol q(t).</math> When we say stationary point, we mean a stationary point of <math>S</math> with respect to any small perturbation in <math>\boldsymbol q</math>. See proofs below for more rigorous detail.
{{math proof|title=Derivation of the one-dimensional Euler–Lagrange equation|proof=
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We wish to find a function <math>f</math> which satisfies the boundary conditions <math>f(a) = A</math>, <math>f(b) = B</math>, and which extremizes the functional
<math display="block"> J[f] = \int_a^b L(x,f(x),f'(x))\, \mathrm{d}x\ . </math>
We assume that <math>L</math> is twice continuously differentiable.<ref name='CourantP184'>{{harvnb|Courant|Hilbert|1953|p=184}}</ref> A weaker assumption can be used, but the proof becomes more difficult.{{Citation needed|date=September 2013}}
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If <math>f</math> extremizes the functional subject to the boundary conditions, then any slight perturbation of <math>f</math> that preserves the boundary values must either increase <math>J</math> (if <math>f</math> is a minimizer) or decrease <math>J</math> (if <math>f</math> is a maximizer).
Let <math>
<math display="block">
<math display="block"> \frac{\mathrm{d} J_\varepsilon}{\mathrm{d} \varepsilon} = \frac{\mathrm d}{\mathrm d\varepsilon}\int_a^b L_\varepsilon\, \mathrm{d}x = \int_a^b \frac{\mathrm{d} L_\varepsilon}{\mathrm{d}\varepsilon} \, \mathrm{d}x. </math>▼
▲<math display="block">
\\
&
The
When <math>\varepsilon = 0
<math display="block"> \left.\frac{\mathrm
▲When <math>\varepsilon = 0</math> we have <math>g_{\varepsilon} = f</math>, <math>L_{\varepsilon} = L(x,f(x),f'(x))</math> and <math>J_{\varepsilon}</math> has an [[extremum]] value, so that
The next step is to use [[integration by parts]] on the second term of the integrand, yielding
<math display="block"> \int_a^b \left[ \frac{\partial L}{\partial f}(x,f(x),f'(x)) - \frac{\mathrm{d}}{\mathrm{d}x} \frac{\partial L}{\partial f'}(x,f(x),f'(x)) \right] \eta(x)\,\mathrm{d}x + \left[ \eta(x) \frac{\partial L}{\partial f'}(x,f(x),f'(x)) \right]_a^b = 0 \ . </math>
Using the boundary conditions <math>\eta (a) = \eta (b) = 0</math>,
<math display="block"> \int_a^b \left[ \frac{\partial L}{\partial f}(x,f(x),f'(x)) - \frac{\mathrm{d}}{\mathrm{d}x} \frac{\partial L}{\partial f'}(x,f(x),f'(x)) \right] \eta(x)\,\mathrm{d}x = 0 \, . </math>
Applying the [[fundamental lemma of calculus of variations]] now yields the Euler–Lagrange equation
<math display="block"> \frac{\partial L}{\partial f}(x,f(x),f'(x)) - \frac{\mathrm{d}}{\mathrm{d}x} \frac{\partial L}{\partial f'}(x,f(x),f'(x)) = 0 \, . </math>
}}
{{math proof|title=
Given a functional
<math display="block">J = \int^b_a L(t, y(t), y'(t))\,\mathrm{d}t</math>
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<math display="block">\frac{\partial J(y_1,\ldots,y_n)}{\partial y_m} = 0.</math>
Note that change of <math> y_m </math> affects L not only at m but also at m-1 for the derivative of the 3rd argument.
Evaluating this partial derivative gives▼
<math display="block"> L(\text{3rd argument}) \left( \frac{y_{m+1} - (y_{m} + \Delta y_{m})}{\Delta t} \right) = L \left(\frac{y_{m+1} - y_{m}}{\Delta t}\right) - \frac{\partial L}{\partial y'} \frac{\Delta y_m}{\Delta t} , L \left( \frac{(y_{m} + \Delta y_{m}) - y_{m-1}}{\Delta t} \right) = L \left(\frac{y_{m} - y_{m-1}}{\Delta t}\right) + \frac{\partial L}{\partial y'} \frac{\Delta y_m}{\Delta t}</math>
<math display="block">\frac{\partial J}{\partial y_m} = L_y\left(t_m, y_m, \frac{y_{m + 1} - y_m}{\Delta t}\right)\Delta t + L_{y'}\left(t_{m - 1}, y_{m - 1}, \frac{y_m - y_{m - 1}}{\Delta t}\right) - L_{y'}\left(t_m, y_m, \frac{y_{m + 1} - y_m}{\Delta t}\right).</math>
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==Example==
A standard example{{Citation needed|reason=this example seems like a poor one as it is not even presented as a dynamical system|date=July 2023}} is finding the real-valued function ''y''(''x'') on the interval [''a'', ''b''], such that ''y''(''a'') = ''c'' and ''y''(''b'') = ''d'', for which the
:<math> \text{s} = \int_{a}^{b} \sqrt{\mathrm{d}x^2+\mathrm{d}y^2} = \int_{a}^{b} \sqrt{1+y'^2}\,\mathrm{d}x,</math>
the integrand function being
The partial derivatives of ''L'' are:
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\forall i:\frac{\mathrm{d}}{\mathrm{d}t}\frac{\partial L}{\partial X^i}\bigg|_{\dot{f}(t)}=\frac{\partial L}{\partial x^i}\bigg|_{\dot{f}(t)}.
</math>
Euler-Lagrange equations can also be written in a coordinate-free form as <ref>{{Cite web |last=José |last2=Saletan |year=1998 |title=Classical Dynamics: A contemporary approach |url=https://www.cambridge.org/in/academic/subjects/physics/general-and-classical-physics/classical-dynamics-contemporary-approach,%20https://www.cambridge.org/in/academic/subjects/physics/general-and-classical-physics |access-date=2023-09-12 |website=Cambridge University Press |language=en |isbn=9780521636360}}</ref>
:<math>
\mathcal{L}_\Delta \theta_L=dL
</math>
where <math>\theta_L</math> is the canonical momenta [[One-form (differential geometry)|1-form]] corresponding to the Lagrangian <math>L</math>. The vector field generating time translations is denoted by <math>\Delta</math> and the [[Lie derivative]] is denoted by <math>\mathcal{L}</math>. One can use local charts <math>(q^\alpha,\dot{q}^\alpha)</math> in which <math>\theta_L=\frac{\partial L}{\partial \dot{q}^\alpha}dq^\alpha</math> and <math>\Delta:=\frac{d}{dt}=\dot{q}^\alpha\frac{\partial}{\partial q^\alpha}+\ddot{q}^\alpha\frac{\partial}{\partial \dot{q}^\alpha}</math> and use coordinate expressions for the Lie derivative to see equivalence with coordinate expressions of the Euler Lagrange equation. The coordinate free form is particularly suitable for geometrical interpretation of the Euler Lagrange equations.
==See also==
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{{DEFAULTSORT:Euler-Lagrange Equation}}
[[Category:Eponymous equations of mathematics]]
[[Category:Eponymous equations of physics]]
[[Category:Ordinary differential equations]]
[[Category:Partial differential equations]]
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