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I am trying to prove that $\frac{1}{n!\space2^n}\frac{d^n}{dx^n}\{(x^2-1)^n\}=P_n(x)$, where $P_n(x)$ is the Legendre Polynomial of order n.

I've been told that the proof uses complex analysis, of which I know nothing, isn't there a proof with elementary methods? (If there isn't, I'm still interested in the other one).

Alubeixu
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4 Answers4

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If $n$ is integer \begin{eqnarray*} \frac{d^n}{d x^n} (x^2-1)^n &=& \frac{d^n}{d x^n} \left [ \sum_{k=0}^n (-1)^k \frac{n!}{k!(n-k)!} x^{2n-2k} \right ] \\ &=& \sum_{k=0}^n (-1)^k \frac{n!}{k! (n-k)!} \frac{(2n-2k)!}{(n-2k)!} x^{n-2k}. \end{eqnarray*} The sum above does not go up to $k=n$, since after $k=[n/2]$, the derivatives are 0 then we write

\begin{eqnarray*} \frac{d^n}{d x^n} (x^2-1)^n &=& \sum_{k=0}^{[n/2]} (-1)^k \frac{n!}{k! (n-k)!} \frac{(2n-2k)!}{(n-2k)!} x^{n-2k}. \end{eqnarray*} It follows from the infinite series truncated to the Legendre polynmial that

\begin{eqnarray*} P_n(x) = \frac{1}{2^n n!} \frac{d^n}{dx^n} (x^2-1)^n. \end{eqnarray*}

The approach followed here is in reverse order. We started with Rodriguez's formula and showed that it corresponds to a Legendre polynomial. A more intuitive approach is to start at the polynomials

\begin{eqnarray*} y(x)= (1-x^2)^n. \end{eqnarray*} and take derivates, and verifty that the derivatives taken $n$ times will get you to the Legendre differential equation. That is, we have that

\begin{eqnarray*} y' = -2 n x (1-x^2)^{n-1} \end{eqnarray*} which we can write as

\begin{eqnarray} (1-x^2) y' + 2n x y = 0. \label{tole} \end{eqnarray} and starts looking a bit like a Legendre differential equation.

We want to differentiate this equation $k$ times and use the Leibniz rule. That is, if we call $u=1-x^2$,

\begin{eqnarray*} \frac{ d^k}{dx^k} [u y'] = \sum_{j=0}^{k} \binom{k}{j} u^{(j)} y^{(k-j+1)} \end{eqnarray*} Given that $u$ is a second order polynomial only three terms of this sum will survive. That is

\begin{eqnarray*} \frac{ d^k}{dx^k} [u y'] &=& u y^{(k+1)} + k u' y^{(k)} + k(k-1) u^{(2)} y^{(k-1)} \\ &=& (1-x^2)y^{(k+1)} - 2 k x y^{(k)} -2 \frac{k(k-1)}{2} y^{(k-1)} = 0 \end{eqnarray*} Likewise we use the Leibniz rule for the product $2nxy$ where only two terms will survive. That is

\begin{eqnarray*} \frac{ d^k}{dx^k} [2 n x y] &=& 2 n x y^{(k)} + 2 n k y^{(k-1)}, \end{eqnarray*} we combine the two results above to find

\begin{eqnarray*} (1-x^2)y^{(k+1)} - 2 k x y^{(k)} - k(k-1) y^{(k-1)} + 2 n x y^{(k)} + 2 n k y^{(k-1)} = 0 \end{eqnarray*} At this point we observe that if $k=n+1$, we find

\begin{eqnarray*} (1-x^2)y^{(n+2)} - 2(n+1) x y^{(n+1)} - n(n+1) y^{(n)} + 2 n x y^{(n+1)} + 2 n (n+1) y^{(n)} = 0 \end{eqnarray*} which simplifies to

\begin{eqnarray*} (1-x^2) y^{(n+2)} - 2 x y^{(n+1)} + n(n+1) y^{(n)}=0. \end{eqnarray*}

and this is the Legendre differential equation with $y^n=P_n$. We then showed that

\begin{eqnarray*} \frac{d^n}{dx^n}(1-x^2)^n \end{eqnarray*} satisfies the Lagrange differential equation. The factor $1/(2^n n!)$ is included to make $P(1)=1$.

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  1. Check that the left side indeed defines an $n$th order polynomial.

  2. Check that $\displaystyle \int_{-1}^{1}P_n(x)P_m(x)dx$ vanishes for $m\neq n$ (integration by parts).

  3. Check the normalization condition $P_n(1)=1$ (Leibniz rule).


Added: As you almost correctly write in the comment below, the result of integration by parts (assuming that $m<n$ and transferring the derivatives from $P_n$ to $P_m$) can be written as $$\int_{-1}^1P_m(x)P_n(x)dx=\sum_{k=1}^{n}c_{mnk}\left[\frac{d^{m+k-1} (x^2-1)^m}{dx^{m+k-1}}\frac{d^{n-k}(x^2-1)^n}{dx^{n-k}}\right]_{-1}^{1},$$ where $c_{mnk}$ is some irrelevant constant. Consider the second factor in the square brackets. There you have a polynomial having $n$th order zeros at $x=\pm 1$ which we differentiate $n-k$ times. The result will therefore have $k$th order zeros at these points, which implies vanishing of the integral.

  • Wow, I hadn't even thought of this, thanks! However, is that enough? Aren't there other polynomials that satisfy condition number 2? And shouldn't I also check that $\int_{-1}^1 P_n(x)P_n(x)dx=\frac{2}{2n+1}$? I will start trying this right now! – Alubeixu Jun 18 '14 at 20:32
  • @Alubeixu it's enough, there are no other polynomials satisfying 2 (since the weight is positive). As for the 3rd question, this property is a consequence but not a part of the standard definition (weight + value at 1 fixing the normalization). A hint for the point 2: e.g if $m<n$, then use integration by parts to transfer the derivatives in $P_n$ to $P_m$. – Start wearing purple Jun 18 '14 at 20:38
  • I'm sorry, could you do point 2 explicitly? I'm stuck at $\int_{-1}^1 \frac{d^n}{dx^n}(x^2-1)^n\frac{d^m}{dx^m}(x^2-1)^mdx=\sum_{i=o}^n(\frac{d^{n+i}}{dx^{n+i}}(x^2-1)^n\frac{d^{m-1-i}}{dx^{m-1-i}}(x^2-1)^m(-1)^{i} \space \Big]_{-1}^1$ – Alubeixu Jun 19 '14 at 11:03
  • @Alubeixu I've added some explanations. – Start wearing purple Jun 19 '14 at 17:34
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(The general formula of Legendre Polynomials is given by following equation: $$ P_k(x)=\sum_{m=0}^{\frac{k}{2}|\frac{k-1}{2}}{\frac{(-1)^m(2k-2m)!}{2^km!(k-m)!}}\frac{1}{(k-2m)!} x^{k-2m} $$

The Rodrigues' formula is:

$$ \frac{1}{2^kk!}\frac{d^k}{dx^k}[(x^2-1)^k] $$

The Binomial theorem is as follow: $$(x+y)^k=\sum_{i=0}^{k}\frac{k!}{i!(k-i)!}x^{k-i}y^{i}$$

Then $$(x^2-1)^k=\sum_{i=0}^{k}\frac{k!}{i!(n-i)!}{(x^{2})}^{k-i}(-1)^{i}$$

$$\frac{1}{2^kk!}\frac{d^k}{dx^k}[(x^2-1)^k]=\frac{1}{2^kk!}\frac{d^k}{dx^k}\big[\sum_{i=0}^{k}\frac{k!}{i!(n-i)!}{(x^{2})}^{k-i}(-1)^{i}\big]$$

So $$ =\frac{1}{2^kk!}\sum_{i=0}^{k}\frac{k!}{i!(n-i)!}\frac{d^k}{dx^k}(x)^{2k-2i}(-1)^{i} .....(1)$$

$$\frac{d^k}{dx^k}(x)^{2k-2i}=\frac{(2k-2i)!}{k-2i}x^{k-2i}......(2)$$

By compensate (2) into (1), we get:

$$ P_k(x)=\sum_{m=0}^{\frac{k}{2}|\frac{k-i}{2}}{\frac{(-1)^i(2k-2i)!}{2^ki!(k-i)!}}\frac{1}{(k-2i)!} x^{k-2i} $$

Change dummy variable (i) to (m), we get the same general formula of Legendre Polynomials :

$$ P_k(x)=\sum_{m=0}^{\frac{k}{2}|\frac{k-1}{2}}{\frac{(-1)^m(2k-2m)!}{2^km!(k-m)!}}\frac{1}{(k-2m)!} x^{k-2m} $$

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    Welcome to math.se! I have to ask you: what does notation $\frac{k}{2}\Big| \frac{k-1}{2}$ mean? – Nik Bren Aug 08 '18 at 13:57
  • Imagine you are looking for $$P_5(x)$$ (odd polynomial) then the the sum start from m=0 to 2: $$\sum_{m=0}^\frac{k-i}{2}$$, while $$\frac{k}{2}$$ isvalid for even polynomial such as $$P_4$$. – Mohamed Abugammar Aug 09 '18 at 14:46
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I still think the other answers are a little too complicated. Our goal is to find an $n+1$-degree polynomial $P_{n+1}(x)$ on the interval $[a,b]$ that is orthogonal to any $n$-degree polynomial $Q_{\leq n}(x)$ on the interval $[a,b]$, i.e. $$\int_a^b P_{n+1}(x) Q_{\leq n}(x) dx = 0.$$ The LHS is an integral of a product, so hopefully one's first instinct would be to try integration by parts. Allow me to use the notation of the tabular method: https://kevinboone.me/parts.html (though I can't typeset the arrows here, even if it's possible with more technology) . We have 2 options: we can put $P_{n+1}$ in the derivative column, or the integral column. Let us look at putting it in the derivative column first: $$\begin{array}{r|c|c} \text{row }\# & \frac{d}{dx} & \int \\ \hline 0 & \color{blue}{P_{n+1}(x)} & Q_{\leq n}(x) \\ 1 & P_{n+1}'(x) & \color{blue}{\int Q_{\leq n}}\\ \vdots &\vdots & \vdots \\ n+1 & \color{red}{\text{constant}} & \ldots \\ n+2 & 0 & \color{red}{\ldots} \end{array}$$ The left column ("row $0$") starts with degree $n+1$, decreasing in degree by 1 each time, until on row $n+1$ it becomes constant (degree $0$). The last term in the integration by parts is then some [constant] times some high degree antiderivative of $Q_{\leq n}(x)$, which we have no control over in making $0$ upon evaluation $(\bullet)|^{x=b}_{x=a}$.

Let us try the other option, putting $P_{n+1}$ in the integral column: $$\begin{array}{r|c|c} \text{row }\# & \frac{d}{dx} & \int \\ \hline 0 & \color{blue}{Q_{\leq n}(x)} & P_{n+1}(x) \\ 1& Q_{\leq n}'(x) & \color{blue}{\int P_{n+1} }\\ \vdots & \vdots & \vdots \\ n& \color{red}{\text{constant}} & \ldots \\ n+1& 0 & \color{red}{(\int)^{n+1} P_{n+1}} \end{array}$$

In the scenario where $Q_{\leq n}$ has degree $n$ (on row $0$ of the table), then on row $n$, it will be degree $0$, namely a constant; on the right/integral column, on row $n+1$ we will have the $(n+1)$th antiderivative of $P_{n+1}(x)$. So, the result of this integral by parts table is (at most) $n$ terms: $$\int_a^b P_{n+1}(x) Q_{\leq n}(x) dx = \textstyle \Big[Q_{\leq n}(x) \cdot \int P_{n+1}(x)\Big]\bigg|_{x=a}^{x=b} - \ldots + (-1)^n \Big[\text{const} \cdot (\int)^{n+1} P_{n+1}(x)\Big]\bigg|_{x=a}^{x=b}$$ (The notation is a bit fiddly, but I hope you can see that the ideas are actually quite simple. If I was writing on a whiteboard in front of you, I could just draw slope-$(-1)$ ovals in the table representing each term, without having to use all this notation, but oh well.)

Again, recall that we have control over what $P_{n+1}$ is, and we have just found that all it needs to be is a degree $n+1$ polynomial s.t. its $1$st, $2$nd, ..., $(n+1)$th antiderivative all vanish at both $x=a$ and $x=b$.

This is still a little hard to think about, but it becomes much easier, if I tell you to think about the problem backward: start with a polynomial $A(x)$ of degree $2(n+1)$ (supposed/destined to be the $(n+1)$th antiderivative of $P_{n+1}$), so that its $0$th, $1$st, ..., $n$th derivatives vanish at $x=a$ and $x=b$ (and then taking $P_{n+1}(x):= (\frac d{dx})^{n+1} A(x)$, we're done!)

And indeed, hopefully one is familiar (from working with Taylor series, or orders of zeroes and poles in complex analysis) that the derivative of a function vanishing to order $M$ at a point $x=x_0$ vanishes to order $M-1$ at $x=x_0$. So, taking $A(x)=(x-a)^{n+1} (x-b)^{n+1}$ (indeed of degree $2(n+1)$), the $0$th, $1$st, ..., $n$th derivatives vanish at $x=a$ and $x=b$, as desired (and indeed the $(n+1)$th derivative is a polynomial of degree $n+1$, as desired!)

D.R.
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