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--- basic_tools:variational_calculus [2018/03/14 16:14]
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+++ basic_tools:variational_calculus [2018/05/05 15:41]
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 ====== Variational Calculus ======
-<tabbox Why is it interesting?>
-Variational calculus is the alternative to the usual calculus methods when we want to find functions that minimize something. As an analogy, usually when we search for the extrema of a function, we differentiate the function, set the derivative of the function to zero and find the point that yields the extrema. Similar results can be computed by using variational calculus.In variational calculus we find extrema of functionals which are functions of functions with respect some function (instead of variable). This is extremely important for the [[frameworks:lagrangian_formalism|Lagrangian formalism]].
+Variational calculus is the alternative to the usual calculus methods when we want to find functions that minimize something. As an analogy, usually when we search for the extrema of a function, we differentiate the function, set the derivative of the function to zero and find the point that yields the extrema. Similar results can be computed by using variational calculus.In variational calculus we find extrema of functionals which are functions of functions with respect some function (instead of variable). This is extremely important for the [[formalisms:lagrangian_formalism|Lagrangian formalism]].
-In the same way that the to find the extrema of a function one needs to solve a system of algebraic equation, the result of a [[basic_tools:variational_calculus:functional_derivative|variational derivative]]
-is a system of differential equations, these being ordinary or partial differential equations, depending on the function space being search.
-<tabbox A note on notation>
-<blockquote>
+=== What we know from Calculus ===
-The best tool of a physicist is notation abuse.
-<cite>Angry Mathematician</cite>
-</blockquote>
-One has to be careful. When talking about variational calculus in this section, we need to be in the same page on some things. This is the most important thing to do when starting studying different topics.
+On [[basic_tools:calculus|calculus]], when we want to find the extremum of a function, we use the derivative:
-Symbols that appear in this section, by (quasi-)order of apparence
+We differentiate the function $f(x)$, then demand that the resulting derivative vanishes:
+$$\frac{d f(x)}{dx} \stackrel{!}{=} 0 ,
-$$\Omega, q, \mathcal Q, (\cdot), [\cdot], L, q(x), q'(x), T^{(n)} \Gamma,
 $$
+if we solve for $x$, we find an critical point, for this function $f$
-We should learn the meaning of these symbols to keep going.
-There is the main problem, the multiplicity of use of $q$. This can mean:
+=== Concept of Variational Calculus ===
-* For 1-D dynamics or particle systems it is can be the path $q:\mathbb R\to \mathcal Q$, a point or coordinates of that point of $\mathcal Q$. THey can be vectors or scalars, time dependent or not...
+Instead of a function $f$ that takes numbers to numbers, the object of interest is a [[basic_tools:variational_calculus:functional|functional]], a function of functions of sorts. To find the stationary functions of the functionals, we need to change a bit the differentiation process, and we use the //[[basic_tools:variational_calculus:functional_derivatives|functional derivative]]// or variational derivative, and we equate the result to zero.
-* For n-D (or field mechanics), q will be usually substitute by a greek leter, and they are not paths, but surfaces or volumes, functions of more than one variable.
+In the same way that the to find the extrema of a function one needs to solve a system of algebraic equation, the result of a variational derivative is a system of differential equations, these being ordinary or partial differential equations, depending on the function space being search.
-For this reason we will focus on 1-D variational problems for now, but with minimal change on notation we can have the same results for multiple dimensional systems.
+This is the recipe of the [[basic_tools:variational_calculus:the_variational_problem|variational problem]]
+=== References ===
+  * //Calculus of Variations//, Gelfand and Fomin
+  * Calculus of Variations by MacCluer.
-<tabbox Layman>
-<blockquote>Another way of saying a thing is least is to say that if you move the path a little bit at first it
+<tabbox Quotes>
-does not make any difference. Suppose you were walking around on hills – but smooth hills, since
-the mathematical things involved correspond to smooth things – and you come to a place where you
-are lowest, then I say that if you take a small step forward you will not change your height. When
-you are at the lowest or at the highest point, a step does not make any difference in the altitude in
-first approximation, whereas if you are on a slope you can walk down the slope with a step and then
-if you take the step in the opposite direction you walk up. That is the key to the reason why, when
-you are at the lowest place, taking a step does not make much difference, because if it did make any
-difference then if you took a step in the opposite direction you would go down. Since this is the
-lowest point and you cannot go down, your first approximation is that the step does not make any
-difference. We therefore know that if we move a path a little bit it does not make any difference to the
-action on a first approximation.<cite>"The Character of Physical Law" by R. Feynman</cite></blockquote>
-<tabbox Student>
-Variational calculus is a powerful mathematical tool to find the extremums (maxima, minima and saddle points) of functions and even functionals ( we can call them functions of functions).
+<blockquote>
+Another way of saying a thing is least is to say that if you move the path a little bit at first it does not make any difference. Suppose you were walking around on hills – but smooth hills, since the mathematical things involved correspond to smooth things – and you come to a place where you are lowest, then I say that if you take a small step forward you will not change your height. When you are at the lowest or at the highest point, a step does not make any difference in the altitude in first approximation, whereas if you are on a slope you can walk down the slope with a step and then if you take the step in the opposite direction you walk up. That is the key to the reason why, when you are at the lowest place, taking a step does not make much difference, because if it did make any difference then if you took a step in the opposite direction you would go down. Since this is the lowest point and you cannot go down, your first approximation is that the step does not make any difference. We therefore know that if we move a path a little bit it does not make any difference to the action on a first approximation.
-**What we know from Calculus**
+<cite>"The Character of Physical Law" by R. Feynman</cite>
+</blockquote>
-On calculus, when we want to find the extremum of a function, we use the derivative:
-We differentiate the function $f(x)$, then demand that the resulting derivative vanishes:
-$$\frac{d f(x)}{dx} \stackrel{!}{=} 0 .$$
-While this mathematical tool is great for functions it does not help us if we want to calculate the extrema of different objects, like functionals. A **functional** is a function of a function. This means, a functional $S[f(x)]$ has as an argument a **function** $f(x)$ and spits out a number for each function that we put into it. This is to be contrasted with what a function is: A function $f(x)$ eats a //number// $x$ and spits our a number.
-(Functionals are especially important for the Lagrangian framework.)
-We will see in a moment that the variational calculus enables us to calculate the extrema of functions **and** functionals.
-To "invent" this new theory that is capable of finding the minima of functionals, we need to take a step back and think about what characterizes a mathematical minimum.
-The answer of variational calculus is that a minimum is characterised by the neighbourhood of the minimum. For example, let's find the minimum $x_{\mathrm{min }}$ of an ordinary function $f(x)=3x^2+x$. We start by looking at one specific $x=a$ and take a close look at its neighborhood. Mathematically this means $a+ \epsilon$, where $\epsilon$ denotes an infinitesimal (positive or negative) variation. We put this variation of $a$ into our function $f(x)$:
-$$f(a+\epsilon)=3(a+\epsilon)^2+(a+\epsilon)=3(a^2+2a \epsilon + \epsilon^2)+a+\epsilon. $$
-**If $a$ is a minimum, first-order variations in $\epsilon$ must vanish**, because otherwise we can choose $\epsilon$ to be negative $\epsilon<0$ and then $f(a+\epsilon)$ is smaller than  $f(a)$. Therefore, we collect all terms linear in $\epsilon$ and demand this to be zero
-$$3\cdot 2a \epsilon+ \epsilon \stackrel{!}{=}0 \rightarrow 6a+1 \stackrel{!}{=} 0.$$
-So we find the minimum
-$x_{\mathrm{min }}= a=\frac{-1}{6},$$
-which is of course exactly the same result we get if we take the derivative $f(x)=3x^2+x \rightarrow f'(x)= 6x+1$ and demand this to be zero. In terms of ordinary functions, this is just another way of doing the same thing, but variational calculus is, in addition, able to find the extrema of functionals.
-__** References**__
- * //Calculus of Variations//, Gelfand and Fomin
-<tabbox Researcher>
-<note tip>
-The motto in this section is: //the higher the level of abstraction, the better//.
-</note>
---> Common Question 1#
-<--
---> Common Question 2#
-<--
-<tabbox Examples>
---> Example1#
-<--
---> Example2:#
-<--
-<tabbox History>
 </tabbox>

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