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2.7: Calculus of Variations with Many Variables

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We’ve found the equations defining the curve y(x) along which the integral

J[y]=x2x1f(y,y)dx

has a stationary value, and we’ve seen how it works in some two-dimensional curve examples.

But most dynamical systems are parameterized by more than one variable, so we need to know how to go from a curve in (x,y) to one in a space (x,y1,y2,yn), and we need to minimize (say)

J[y1,y2,yn]=x2x1f(y1,y2,yn,y1,y2,yn)dx

In fact, the generalization is straightforward: the path deviation simply becomes a vector,

δy(x)=(δy1(x),δy2(x),,δyn(x))

Then under any infinitesimal variation δy(x) (writing also y=(y1,yn))

δJ[y]=x2x1ni=1[f(y,y)yiδyi(x)+f(y,y)yiδyi(x)]dx=0

Just as before, we take the variation zero at the endpoints, and integrate by parts to get now n separate equations for the stationary path:

f(y,y)yiddx(f(y,y)yi)=0,i=1,,n


This page titled 2.7: Calculus of Variations with Many Variables is shared under a not declared license and was authored, remixed, and/or curated by Michael Fowler.

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