# Famous Theorems of Mathematics/π is transcendental/Symmetric polynomials

## Definition 1

A permutation is a bijective function from a set to itself.

Let ${\displaystyle X={\bigl \{}X_{1},\ldots ,X_{n}{\bigr \}}}$ be a finite set. The function ${\displaystyle \sigma :X\to X}$ is called a permutation if and only if it is one-to-one and onto.

Meaning, for all ${\displaystyle 1\leq i\leq n}$ there exists a unique ${\displaystyle 1\leq j\leq n}$ such that ${\displaystyle \sigma (X_{i})=X_{\sigma (i)}=X_{j}}$.

The set of all permutations of the elements of ${\displaystyle X}$ is denoted by ${\displaystyle S_{X}}$.

### Example

For ${\displaystyle X={\bigl \{}1,2,3{\bigr \}}}$ there are ${\displaystyle 3!=6}$ different permutations:

{\displaystyle {\begin{aligned}&\sigma _{1}={\begin{bmatrix}1&2&3\\1&2&3\end{bmatrix}},\quad \sigma _{2}={\begin{bmatrix}1&2&3\\1&3&2\end{bmatrix}}\\[5pt]&\sigma _{3}={\begin{bmatrix}1&2&3\\2&1&3\end{bmatrix}},\quad \sigma _{4}={\begin{bmatrix}1&2&3\\2&3&1\end{bmatrix}}\\[5pt]&\sigma _{5}={\begin{bmatrix}1&2&3\\3&1&2\end{bmatrix}},\quad \sigma _{6}={\begin{bmatrix}1&2&3\\3&2&1\end{bmatrix}}\end{aligned}}}

In general, if ${\displaystyle |X|=n}$ then ${\displaystyle |S_{X}|=n!=1\cdot 2\cdots n}$.

## Definition 2

Let ${\displaystyle F({\vec {X}}{}^{n})}$ be a polynomial. Let us define:

${\displaystyle \sigma (F):=F(X_{\sigma (1)},\ldots ,X_{\sigma (n)})}$

### Properties

Let ${\displaystyle F({\vec {X}}{}^{n}),G({\vec {X}}{}^{n})}$ be polynomials. Then we have:

• ${\displaystyle \sigma (cF)=c\,\sigma (F)}$ such that ${\displaystyle c\in \mathbb {R} }$.
• ${\displaystyle \sigma (F\pm G)=\sigma (F)\pm \sigma (G)}$
• ${\displaystyle \sigma (F\cdot G)=\sigma (F)\cdot \sigma (G)}$
• ${\displaystyle (\sigma _{1}\circ \sigma _{2})(F)=\sigma _{1}(\sigma _{2}(F))}$

#### Proof

• By definition, the permutation is applied on the variable indexes only.
• First, let ${\displaystyle F,G}$ be monomials of the form
{\displaystyle {\begin{aligned}F&=a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}\\[5pt]G&=b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}\\[5pt]\sigma (F\pm G)&=\sigma {\bigl (}a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}\!\pm b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}{\bigl )}\\[5pt]&=a\,X_{\sigma (1)}^{a_{1}}\!\cdots X_{\sigma (n)}^{a_{n}}\!\pm b\,X_{\sigma (1)}^{b_{1}}\!\cdots X_{\sigma (n)}^{b_{n}}\\[5pt]&=\sigma {\bigl (}a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}{\bigl )}\pm \sigma {\bigl (}b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}{\bigl )}\\[5pt]&=\sigma (F)\pm \sigma (G)\end{aligned}}}
We can generalize by induction for ${\displaystyle F=\sum _{i_{1}\,=\,1}^{k_{1}}F_{i_{1}},\,G=\sum _{i_{2}\,=\,1}^{k_{2}}G_{i_{2}}}$, such that ${\displaystyle F_{i_{1}},G_{i_{2}}}$ are monomials.
• Same as before, let ${\displaystyle F,G}$ be monomials of the form
{\displaystyle {\begin{aligned}F&=a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}\\[5pt]G&=b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}\\[5pt]\sigma (F\cdot G)&=\sigma {\bigl (}a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}\!\cdot b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}{\bigl )}\\[5pt]&=ab\,\sigma {\bigl (}X_{1}^{a_{1}+b_{1}}\!\cdots X_{n}^{a_{n}+b_{n}}{\bigl )}\\[5pt]&=ab\,X_{\sigma (1)}^{a_{1}+b_{1}}\!\cdots X_{\sigma (n)}^{a_{n}+b_{n}}\\[5pt]&={\bigl (}a\,X_{\sigma (1)}^{a_{1}}\!\cdots X_{\sigma (n)}^{a_{n}}{\bigr )}\cdot {\bigl (}b\,X_{\sigma (1)}^{b_{1}}\!\cdots X_{\sigma (n)}^{b_{n}}{\bigr )}\\[5pt]&=\sigma {\bigl (}a\,X_{1}^{a_{1}}\!\cdots X_{n}^{a_{n}}{\bigl )}\cdot \sigma {\bigl (}b\,X_{1}^{b_{1}}\!\cdots X_{n}^{b_{n}}{\bigl )}\\[5pt]&=\sigma (F)\cdot \sigma (G)\end{aligned}}}
Again, We can generalize by induction for ${\displaystyle F=\sum _{i_{1}\,=\,1}^{k_{1}}F_{i_{1}},\,G=\sum _{i_{2}\,=\,1}^{k_{2}}G_{i_{2}}}$, such that ${\displaystyle F_{i_{1}},G_{i_{2}}}$ are monomials:
{\displaystyle {\begin{aligned}\sigma (F\cdot G)&=\sigma {\bigg (}\sum _{i_{1}\,=\,1}^{k_{1}}F_{i_{1}}\cdot \sum _{i_{2}\,=\,1}^{k_{2}}G_{i_{2}}{\bigg )}\\[5pt]&=\sigma {\bigg (}\sum _{i_{1}\,=\,1}^{k_{1}}\sum _{i_{2}\,=\,1}^{k_{2}}F_{i_{1}}G_{i_{2}}{\bigg )}\\[5pt]&=\sum _{i_{1}\,=\,1}^{k_{1}}\sum _{i_{2}\,=\,1}^{k_{2}}\sigma (F_{i_{1}}\!\cdot G_{i_{2}})\\[5pt]&=\sum _{i_{1}\,=\,1}^{k_{1}}\sum _{i_{2}\,=\,1}^{k_{2}}\sigma (F_{i_{1}})\cdot \sigma (G_{i_{2}})\\[5pt]&=\sum _{i_{1}\,=\,1}^{k_{1}}\sigma (F_{i_{1}})\cdot \sum _{i_{2}\,=\,1}^{k_{2}}\sigma (G_{i_{2}})\\&=\sigma {\bigg (}\sum _{i_{1}\,=\,1}^{k_{1}}F_{i_{1}}{\bigg )}\cdot \sigma {\bigg (}\sum _{i_{2}\,=\,1}^{k_{2}}G_{i_{2}}{\bigg )}\\[5pt]&=\sigma (F)\cdot \sigma (G)\end{aligned}}}
• By definition we get:
{\displaystyle {\begin{aligned}(\sigma _{1}\circ \sigma _{2})(F)&=F{\bigl (}X_{(\sigma _{1}\,\circ \,\sigma _{2})(1)},\ldots ,X_{(\sigma _{1}\,\circ \,\sigma _{2})(n)}{\bigr )}\\[5pt]&=F{\bigl (}X_{\sigma _{1}(\sigma _{2}(1))},\ldots ,X_{\sigma _{1}(\sigma _{2}(n))}{\bigr )}\\[5pt]&=\sigma _{1}{\bigl (}F(X_{\sigma _{2}(1)},\ldots ,X_{\sigma _{2}(n)}){\bigr )}\\[5pt]&=\sigma _{1}(\sigma _{2}(F))\end{aligned}}}

## Definition 3

Let ${\displaystyle P({\vec {X}}{}^{n})}$ be a polynomial. Then it is called symmetric if

${\displaystyle \sigma (P)=P}$

for all permutations ${\displaystyle \sigma :\{1,\ldots ,n\}\to \{1,\ldots ,n\}}$.

### Examples

• A symmetric polynomial:
{\displaystyle {\begin{aligned}P({\color {red}x_{1}},{\color {Green}x_{2}},{\color {blue}x_{3}})&={\color {red}x_{1}^{2}}{\color {Green}x_{2}^{2}}{\color {blue}x_{3}^{2}}+{\color {red}3x_{1}}+{\color {Green}3x_{2}}+{\color {blue}3x_{3}}\\[5pt]&={\color {red}x_{1}^{2}}{\color {blue}x_{3}^{2}}{\color {Green}x_{2}^{2}}+{\color {red}3x_{1}}+{\color {blue}3x_{3}}+{\color {Green}3x_{2}}\\[5pt]&={\color {Green}x_{2}^{2}}{\color {red}x_{1}^{2}}{\color {blue}x_{3}^{2}}+{\color {Green}3x_{2}}+{\color {red}3x_{1}}+{\color {blue}3x_{3}}\\[5pt]&={\color {Green}x_{2}^{2}}{\color {blue}x_{3}^{2}}{\color {red}x_{1}^{2}}+{\color {Green}3x_{2}}+{\color {blue}3x_{3}}+{\color {red}3x_{1}}\\[5pt]&={\color {blue}x_{3}^{2}}{\color {red}x_{1}^{2}}{\color {Green}x_{2}^{2}}+{\color {blue}3x_{3}}+{\color {red}3x_{1}}+{\color {Green}3x_{2}}\\[5pt]&={\color {blue}x_{3}^{2}}{\color {Green}x_{2}^{2}}{\color {red}x_{1}^{2}}+{\color {blue}3x_{3}}+{\color {Green}3x_{2}}+{\color {red}3x_{1}}\end{aligned}}}
• A non-symmetric polynomial:
{\displaystyle {\begin{aligned}P({\color {red}x_{1}},{\color {Green}x_{2}},{\color {blue}x_{3}})&={\color {red}x_{1}}+{\color {Green}x_{2}}-{\color {blue}x_{3}}\\[5pt]&\neq {\color {red}x_{1}}+{\color {blue}x_{3}}-{\color {Green}x_{2}}\\[5pt]&\neq {\color {Green}x_{2}}+{\color {red}x_{1}}-{\color {blue}x_{3}}\\[5pt]&\neq {\color {Green}x_{2}}+{\color {blue}x_{3}}-{\color {red}x_{1}}\\[5pt]&\neq {\color {blue}x_{3}}+{\color {red}x_{1}}-{\color {Green}x_{2}}\\[5pt]&\neq {\color {blue}x_{3}}+{\color {Green}x_{2}}-{\color {red}x_{1}}\end{aligned}}}

### Properties

• The sum and product of symmetric polynomials is a symmetric polynomial.
• Let ${\displaystyle F}$ be a polynomial in variables ${\displaystyle Y_{1},\ldots ,Y_{m}}$, and let ${\displaystyle G_{1},\ldots ,G_{m}}$ be symmetric polynomials in variables ${\displaystyle X_{1},\ldots ,X_{n}}$.
Then ${\displaystyle F({\vec {G}}{}^{m}({\vec {X}}{}^{n}))}$ is also symmetric in variables ${\displaystyle X_{1},\ldots ,X_{n}}$.

#### Proof

• This follows from the properties in definition 2 and the symmetric polynomial definition above.
• By definition we get:
{\displaystyle {\begin{aligned}\sigma {\bigl (}F({\vec {G}}{}^{m}({\vec {X}}{}^{n})){\bigr )}&=\sigma {\bigl (}F(G_{1}({\vec {X}}{}^{n}),\ldots ,G_{m}({\vec {X}}{}^{n})){\bigr )}\\[5pt]&=F{\bigl (}\sigma (G_{1}({\vec {X}}{}^{n})),\ldots ,\sigma (G_{m}({\vec {X}}{}^{n})){\bigr )}\\[5pt]&=F{\bigl (}G_{1}({\vec {X}}{}^{n}),\ldots ,G_{m}({\vec {X}}{}^{n}){\bigr )}\\[5pt]&=F({\vec {G}}{}^{m}({\vec {X}}{}^{n}))\end{aligned}}}

 Symmetric polynomials