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diff --git a/content/know/concept/beltrami-identity/index.pdc b/content/know/concept/beltrami-identity/index.pdc new file mode 100644 index 0000000..a466a63 --- /dev/null +++ b/content/know/concept/beltrami-identity/index.pdc @@ -0,0 +1,138 @@ +--- +title: "Beltrami identity" +firstLetter: "B" +publishDate: 2022-09-17 +categories: +- Physics +- Mathematics + +date: 2022-09-10T13:39:06+02:00 +draft: false +markup: pandoc +--- + +# Beltrami identity + +Consider a general functional $J[f]$ of the following form, +with $f(x)$ an unknown function: + +$$\begin{aligned} + J[f] = \int_{x_0}^{x_1} L(f, f', x) \dd{x} +\end{aligned}$$ + +Where $L$ is the Lagrangian. +To find the $f$ that maximizes or minimizes $J[f]$, +the [calculus of variations](/know/concept/calculus-of-variations/) +states that the Euler-Lagrange equation must be solved for $f$: + +$$\begin{aligned} + 0 = \pdv{L}{f} - \dv{x} \Big( \pdv{L}{f'} \Big) +\end{aligned}$$ + +We now want to know exactly how $L$ depends on the free variable $x$, +since it is a function of $x$, $f(x)$ and $f'(x)$. +Using the chain rule: + +$$\begin{aligned} + \dv{L}{x} + = \pdv{L}{f} \dv{f}{x} + \pdv{L}{f'} \dv{f'}{x} + \pdv{L}{x} +\end{aligned}$$ + +Substituting the Euler-Lagrange equation into the first term gives us: + +$$\begin{aligned} + \dv{L}{x} + &= f' \dv{x} \Big( \pdv{L}{f'} \Big) + \dv{f'}{x} \pdv{L}{f'} + \pdv{L}{x} + \\ + &= \dv{x} \bigg( f' \pdv{L}{f'} \bigg) + \pdv{L}{x} +\end{aligned}$$ + +Although we started from the "hard" derivative $\dv*{L}{x}$, +we arrive at an expression for the "soft" derivative $\pdv*{L}{x}$, +describing the *explicit* dependence of $L$ on $x$: + +$$\begin{aligned} + - \pdv{L}{x} + = \dv{x} \bigg( f' \pdv{L}{f'} - L \bigg) +\end{aligned}$$ + +What if $L$ does not explicitly depend on $x$, i.e. $\pdv*{L}{x} = 0$? +In that case, the equation can be integrated to give the **Beltrami identity**: + +$$\begin{aligned} + \boxed{ + f' \pdv{L}{f'} - L + = C + } +\end{aligned}$$ + +Where $C$ is a constant. +This says that the left-hand side is a conserved quantity in $x$, +which could be useful to know. +If we insert a concrete expression for $L$, +the Beltrami identity might be easier to solve for $f$ than the full Euler-Lagrange equation. +The assumption $\pdv*{L}{x} = 0$ is justified; +for example, if $x$ is time, it means that the potential is time-independent. + + +## Higher dimensions + +Above, a 1D problem was considered, i.e. $f$ depended only on a single variable $x$. +Consider now a 2D problem, such that $J[f]$ is given by: + +$$\begin{aligned} + J[f] = \iint_{(x_0, y_0)}^{(x_1, y_1)} L(f, f_x, f_y, x, y) \dd{x} \dd{y} +\end{aligned}$$ + +In which case the Euler-Lagrange equation takes the following form: + +$$\begin{aligned} + 0 = \pdv{L}{f} - \dv{x} \Big( \pdv{L}{f_x} \Big) - \dv{y} \Big( \pdv{L}{f_y} \Big) +\end{aligned}$$ + +Once again, we calculate the hard $x$-derivative of $L$ (the $y$-derivative is analogous): + +$$\begin{aligned} + \dv{L}{x} + &= \pdv{L}{f} \dv{f}{x} + \pdv{L}{f_x} \dv{f_x}{x} + \pdv{L}{f_y} \dv{f_y}{x} + \pdv{L}{x} + \\ + &= \dv{f}{x} \bigg( \dv{x} \Big( \pdv{L}{f_x} \Big) + \dv{y} \Big( \pdv{L}{f_y} \Big) \bigg) + + \pdv{L}{f_x} \dv{f_x}{x} + \pdv{L}{f_y} \dv{f_y}{x} + \pdv{L}{x} + \\ + &= \dv{x} \Big( f_x \pdv{L}{f_x} \Big) + \dv{y} \Big( f_x \pdv{L}{f_y} \Big) + \pdv{L}{x} +\end{aligned}$$ + +This time, we arrive at the following expression for the soft derivative $\pdv*{L}{x}$: + +$$\begin{aligned} + - \pdv{L}{x} + &= \dv{x} \Big( f_x \pdv{L}{f_x} - L \Big) + \dv{y} \Big( f_x \pdv{L}{f_y} \Big) +\end{aligned}$$ + +Due to the derivatives, this cannot be cleanly turned into an analogue of the 1D Beltrami identity, +and therefore we use that name only in the 1D case. + +However, if $\pdv*{L}{x} = 0$, this equation is still useful. +For an off-topic demonstration of this fact, +let us choose $x$ as the transverse coordinate, and integrate over it to get: + +$$\begin{aligned} + 0 + &= - \int_{x_0}^{x_1} \pdv{L}{x} \dd{x} + \\ + &= \int_{x_0}^{x_1} \dv{x} \Big( f_x \pdv{L}{f_x} - L \Big) + \dv{y} \Big( f_x \pdv{L}{f_y} \Big) \dd{x} + \\ + &= \Big[ f_x \pdv{L}{f_x} - L \Big]_{x_0}^{x_1} + \dv{y} \int_{x_0}^{x_1} \Big( f_x \pdv{L}{f_y} \Big) \dd{x} +\end{aligned}$$ + +If our boundary conditions cause the boundary term to vanish (as is often the case), +then the integral on the right is a conserved quantity with respect to $y$. +While not as elegant as the 1D Beltrami identity, +the above 2D counterpart still fulfills the same role. + + + +## References +1. O. Bang, + *Nonlinear mathematical physics: lecture notes*, 2020, + unpublished. |