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Gjergji Zaimi
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I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

 

For example outFrom here we can count the number of occurrences of each value. Let's start with $n!^2$ pairs$\det(\sigma_1+\sigma_2)$. The exponential generating function for odd cycles (or cyclic permutatons of odd size) on $\{1,2,\dots,n\}$ is $x+\frac{x^3}{3}+\cdots=\frac{1}{2}\left(\log(1+x)-\log(1-x)\right)$. This is because there are $(n-1)!$ odd cycles when $n$ is odd, and $0$ otherwise. By the exponential formula, the generating function of permutations fromthat consist of only odd cycles, together with a statistic $S_n$$t$ that keeps track of the number of cycles, is $$e^{\frac{t}{2}\left(\log(1+x)-\log(1-x)\right)}=\left(\frac{1+x}{1-x}\right)^{\frac{t}{2}}$$ By substituting $t=2s$ we haveget $\operatorname{per}(\sigma_1-\sigma_2)=2^k$$\left(\frac{1+x}{1-x}\right)^{s}$. The coefficient $a_{k,n}$ of the monomial $s^kx^n$ is given exactly by $n!f(n,k)$$\frac{1}{n!}$ times the number of permutations on $n$ letters that decompose into $k$ odd cycles and no even cycles, wheretimes a factor of $f(n,k)$$2^k$. Therefore the number of permutation pairs $(\sigma_1,\sigma_2)$ for which $\det(\sigma_1+\sigma_2)=-2^k$ is the same as the number of permutation pairs for which $\det(\sigma_1+\sigma_2)=2^k$ and is given by $\frac{(n!)^2a_{k,n}}{2}$. Here we used the fact that $(-1)^{E(\sigma)}$ is the sign of $\sigma$, and the number of permutations with sign $-1$ is the same as those with sign $+1$.


For $\operatorname{per}(\sigma_1+\sigma_2)$ we are looking at $2^{\text{number of cycles}}$ over all permutations. So we start with the generating function of cycles which is $x+\frac{x^2}{2}+\cdots=-\log(1-x)$. So the exponential generating function $$e^{t(-\log(1-x))}=\frac{1}{(1-x)^t}$$ has as coefficient of $x^nt^k$ in$t^kx^n$ the expansionnumber of permutations on $\frac{1}{(1-x^2)^t}$$n$ letters with precisely $k$ cycles, divided by $n!$. Substituting $t=2s$ we get $\frac{1}{(1-x)^{2s}}$, and we denote by $b_{k,n}$ the coefficient of $s^kx^n$. This coefficient is equal to $\frac{1}{n!}$ times the number of permutations on $n$ letters with precisely $k$ cycles, times $2^k$. Therefore the number of permutation pairs $(\sigma_1,\sigma_2)$ with $\operatorname{per}(\sigma_1+\sigma_2)=2^k$ is exactly $(n!)^2b_{k,n}$.


Finally for $\operatorname{per}(\sigma_1-\sigma_2)$ we want to look at permutations with only even cycles. The exponential generating function of even cycles is given by $\frac{x^2}{2}+\frac{x^4}{4}+\cdots=-\frac{1}{2}\log(1-x^2)$. Similarly to above the generating function $$e^{2s\left(-\frac{1}{2}\log(1-x^2)\right)}=\frac{1}{(1-x^2)^s}$$ has coefficients $c_{k,n}$ for monomials $s^kx^n$ which are equal to $\frac{1}{n!}$ times the number of permutations on $n$ letters which decompose into exactly $k$ even cycles, times $2^k$. So the number of permutation pairs $(\sigma_1,\sigma_2)$ with $\operatorname{per}(\sigma_1-\sigma_2)=2^k$ is exactly $(n!)^2c_{k,n}$.

I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

For example out of $n!^2$ pairs of permutations from $S_n$ we have $\operatorname{per}(\sigma_1-\sigma_2)=2^k$ exactly $n!f(n,k)$ times, where $f(n,k)$ is the coefficient of $x^nt^k$ in the expansion of $\frac{1}{(1-x^2)^t}$.

I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

 

From here we can count the number of occurrences of each value. Let's start with $\det(\sigma_1+\sigma_2)$. The exponential generating function for odd cycles (or cyclic permutatons of odd size) on $\{1,2,\dots,n\}$ is $x+\frac{x^3}{3}+\cdots=\frac{1}{2}\left(\log(1+x)-\log(1-x)\right)$. This is because there are $(n-1)!$ odd cycles when $n$ is odd, and $0$ otherwise. By the exponential formula, the generating function of permutations that consist of only odd cycles, together with a statistic $t$ that keeps track of the number of cycles, is $$e^{\frac{t}{2}\left(\log(1+x)-\log(1-x)\right)}=\left(\frac{1+x}{1-x}\right)^{\frac{t}{2}}$$ By substituting $t=2s$ we get $\left(\frac{1+x}{1-x}\right)^{s}$. The coefficient $a_{k,n}$ of the monomial $s^kx^n$ is given exactly by $\frac{1}{n!}$ times the number of permutations on $n$ letters that decompose into $k$ odd cycles and no even cycles, times a factor of $2^k$. Therefore the number of permutation pairs $(\sigma_1,\sigma_2)$ for which $\det(\sigma_1+\sigma_2)=-2^k$ is the same as the number of permutation pairs for which $\det(\sigma_1+\sigma_2)=2^k$ and is given by $\frac{(n!)^2a_{k,n}}{2}$. Here we used the fact that $(-1)^{E(\sigma)}$ is the sign of $\sigma$, and the number of permutations with sign $-1$ is the same as those with sign $+1$.


For $\operatorname{per}(\sigma_1+\sigma_2)$ we are looking at $2^{\text{number of cycles}}$ over all permutations. So we start with the generating function of cycles which is $x+\frac{x^2}{2}+\cdots=-\log(1-x)$. So the exponential generating function $$e^{t(-\log(1-x))}=\frac{1}{(1-x)^t}$$ has as coefficient of $t^kx^n$ the number of permutations on $n$ letters with precisely $k$ cycles, divided by $n!$. Substituting $t=2s$ we get $\frac{1}{(1-x)^{2s}}$, and we denote by $b_{k,n}$ the coefficient of $s^kx^n$. This coefficient is equal to $\frac{1}{n!}$ times the number of permutations on $n$ letters with precisely $k$ cycles, times $2^k$. Therefore the number of permutation pairs $(\sigma_1,\sigma_2)$ with $\operatorname{per}(\sigma_1+\sigma_2)=2^k$ is exactly $(n!)^2b_{k,n}$.


Finally for $\operatorname{per}(\sigma_1-\sigma_2)$ we want to look at permutations with only even cycles. The exponential generating function of even cycles is given by $\frac{x^2}{2}+\frac{x^4}{4}+\cdots=-\frac{1}{2}\log(1-x^2)$. Similarly to above the generating function $$e^{2s\left(-\frac{1}{2}\log(1-x^2)\right)}=\frac{1}{(1-x^2)^s}$$ has coefficients $c_{k,n}$ for monomials $s^kx^n$ which are equal to $\frac{1}{n!}$ times the number of permutations on $n$ letters which decompose into exactly $k$ even cycles, times $2^k$. So the number of permutation pairs $(\sigma_1,\sigma_2)$ with $\operatorname{per}(\sigma_1-\sigma_2)=2^k$ is exactly $(n!)^2c_{k,n}$.

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Gjergji Zaimi
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I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

For example out of $n!^2$ pairs of permutations from $S_n$ we have $\operatorname{per}(\sigma_1-\sigma_2)=2^k$ exactly $n!f(n,k)$ times, where $f(n,k)$ is the coefficient of $x^nt^k$ in the expansion of $\frac{1}{(1-x^2)^t}$.

I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.

For example out of $n!^2$ pairs of permutations from $S_n$ we have $\operatorname{per}(\sigma_1-\sigma_2)=2^k$ exactly $n!f(n,k)$ times, where $f(n,k)$ is the coefficient of $x^nt^k$ in the expansion of $\frac{1}{(1-x^2)^t}$.

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Gjergji Zaimi
  • 85.6k
  • 4
  • 236
  • 402

I will abuse notation by identifying a permutation and the matrix it represents. We can denote by $E(\sigma), O(\sigma)$ the number of even and odd cycles that $\sigma$ decomposes into. Given two permutations $\sigma_1,\sigma_2$ we can compute the following: $$\det(\sigma_1+\sigma_2)=\left\{ \begin{array}{ll} (-1)^{E(\sigma_1)}2^{O(\sigma_1\sigma_2^{-1})} & \mbox{if } E(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ $$\operatorname{per}(\sigma_1+\sigma_2)=2^{E(\sigma_1\sigma_2^{-1})+O(\sigma_1\sigma_2^{-1})}$$ $$\operatorname{per}(\sigma_1-\sigma_2)=\left\{ \begin{array}{ll} 2^{E(\sigma_1\sigma_2^{-1})} & \mbox{if } O(\sigma_1\sigma_2^{-1})=0 \\ 0 & \mbox{otherwise } \end{array} \right. $$ and trivially $\det(\sigma_1-\sigma_2)=0$ since the vector of all 1's is always in the kernel of $\sigma_1-\sigma_2$. These calculations follow from noticing that the matrices decompose as direct sums of smaller matrices corresponding to each cycle of $\sigma_1\sigma_2^{-1}$. Distributions of cycle statistics like these are easy to obtain with the exponential formula.