Motion on a sphere with speed proportional to has travel-time line element proportional to . With , this becomes the flat cylinder metric . Shortest lifted paths are straight lines. Nonvertical lines give ; vertical lines are meridians of constant . The poles lie at infinite travel-time distance.
An isoperimetric constraint fixes the value of an integral while optimizing another integral over functions. A constant Lagrange multiplier incorporates the constraint into the variational integrand, and the resulting Euler-Lagrange equation must be supplemented by the appropriate natural boundary conditions for a free endpoint. The name includes integral constraints more general than prescribed geometric length.
When a variational integrand has no explicit dependence on the independent variable, every extremal satisfies
A catenary is a curve of the form . It is the equilibrium shape of a uniform flexible chain in a uniform gravitational field.
When the values of are free at both fixed endpoint locations, integration by parts leaves the boundary term . Since the endpoint variations are arbitrary, stationarity requires
A pointwise constraint on the initial derivative need not be closed in the norm controlling the value and first-derivative square integrals. For example, minimize with , and . The attained minimum is , uniquely achieved by , with natural condition . Adding excludes this minimizer but leaves the same infimum. Multiplying by and rescaling to restore the integral gives smooth admissible approximations converging in energy. The formal quadratic from the interior Euler-Lagrange equation and two initial conditions alone is therefore not a true minimizer.
Forwith free terminal values, the Euler-Lagrange equations and natural conditions give a nonzero stationary family exactly when . It is
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The Euler–Lagrange equation is a fundamental equation in the calculus of variations, which is a field of mathematics that deals with optimizing functionals. A functional is typically an integral that depends on a function and its derivatives. In particular, the Euler–Lagrange equation is used to find the function (or functions) that will minimize (or maximize) a certain integral, usually representing some physical quantity, such as action in physics.
Let's start with the one dimensional case. Let the and a Functional defined by a function of three variables :
Then, the Euler-Lagrange equation gives the maxima and minima of the that type of functional. Note that this type of functional is just one very specific type of functional amongst all possible functionals that one might come up with. However, it turns out to be enough to do most of physics, so we are happy with with it.
Given , the Euler-Lagrange equations are a system of ordinary differential equations constructed from that such that the solutions to that system are the maxima/minima.
By and we simply mean "the partial derivative of with respect to its second and third arguments". The notation is a bit confusing at first, but that's all it means.
Therefore, that expression ends up being at most a second order ordinary differential equation where is the unknown, since:
Now let's think about the multi-dimensional case. Instead of having , we now have . Think about the Lagrangian mechanics motivation of a double pendulum where for a given time we have two angles.
Let's do the 2-dimensional case then. In that case, is going to be a function of 5 variables rather than 3 as in the one dimensional case, and the functional looks like:
This time, the Euler-Lagrange equations are going to be a system of two ordinary differential equations on two unknown functions and of order up to 2 in both variables:At this point, notation is getting a bit clunky, so people will often condense the vectoror just omit the arguments of entirely:
Calculus of Variations ft. Flammable Maths by vcubingx (2020)
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