% vim: tw=50 % 10/11/2022 10AM \begin{proof} Let $x, y \in I$. Need to show $\hat{P}^n(y, x) > 0$ for some $n$. $P$ is irreducible, so there exists $n$ and $x_0 = x, \dots, x_n = y$ such that \[ P(x_0, x_1) \cdots P(x_{n - 1}, x_n) > 0 \] \begin{align*} \hat{P}(x_n, x_{n - 1}) \cdots \hat{P}(x_1, x_0) &= \hat{P}(x_n, x_{n - 1}) \cdots P(x_0, x_1) \frac{\pi(x_0)}{\pi(x_1)} \\ &= \cdots \\ &= P(x_0, x_1) P(x_1, x_2) \cdots P(x_{n - 1}, x_n) \frac{\pi(x_0)}{\pi(x_n)} > 0 \end{align*} \end{proof} \begin{flashcard} \begin{definition*} A chain with matrix $P$ and invariant distribution $\pi$ is called \emph{(time) reversible} if \[ \cloze{\hat{P} = P} \] \end{definition*} \end{flashcard} \noindent That is, for all $x, y$, \[ \hat{P}(x, y) = P(x, y) \iff \frac{\pi(y) P(y, x)}{\pi(x)} = P(x, y) \] $X$ is reversible if for all $x, y$, \begin{flashcard}[detailed-balance-equation] \prompt{Detailed balance equation?} \[ \boxed{\cloze{\pi(x) P(x, y)} = \cloze{\pi(y)P(y, x)}} \] \end{flashcard} Detailed balance equation. \myskip Equivalently, $X$ is reversible if $\forall N \in \NN$, when $X_0 \sim \pi$, then \[ (X_0, \dots, X_N) \sim (X_n, \dots, X_0) \] $\PP(X_0 = x, X_1 = y) = \pi(x)P(x, y)$. \begin{example*} \begin{center} \includegraphics[width=0.6\linewidth] {images/dea6710060e111ed.png} \end{center} \[ P(i, (i + 1) \bmod n) = \frac{2}{3} \quad P(i, (i - 1) \bmod n) = \frac{1}{3} \] for all $i \in \ZZ_n$. Is $P$ time reversible? Take $\pi_i = \frac{1}{n}$ for all $i$, then $P$ is not reversible, because the Detailed Balance equation are not satisfied, for example \[ \pi(i)P(i, i + 1) = \frac{1}{n} \frac{2}{3} \] but \[ \pi(i + 1)P(i + 1, i) = \frac{1}{n} \frac{1}{3} \] \end{example*} \begin{example*} \begin{center} \includegraphics[width=0.6\linewidth] {images/48ff984c60e211ed.png} \end{center} Is this time reversible? $\lambda^i = 2^i$ invariant measure. $\pi(i) \propto 2^i$, $X_0 \sim \pi$. Check $\pi$ satisfies Detailed Balance equation. \end{example*} \begin{lemma*} Let $\mu$ be a distribution satisfying \[ \mu(x) P(x, y) = \mu(y) P(y, x) \quad \forall x, y \] Then $\mu$ is an invariant distribution. \end{lemma*} \begin{proof} \[ \mu(y) = \sum_x \mu(x) P(x, y) = \sum_x \mu(y) P(y, x) = (\mu P)(y) \] So $\mu = \mu P$. \end{proof} \myskip When looking for an invariant distribution, first we should look for a solution to the Detailed Balance equation. If a distribution that solves Detailed Balance equation exists, then it is an invariant distribution. If no solution to Detailed Balance equation exists, then if there exists an invariant distribution, it means the chain is not reversible. \begin{example*} Simple random walk on a graph. $G = (V, E)$, $E$ is edge set, $V$ is vertex set. $G$ is finite and connected. \[ P(x, y) = \begin{cases} \frac{1}{d(x)} & (x, y) \in E \\ 0 & \text{otherwise} \end{cases} \] $d(x)$ is the degree of $x$. Then since $G$ is connected, $P$ is irreducible. To find $\pi$, let's look at Detailed Balance equation \[ (x, y) \in E \quad \pi(x) \ub{P(x, y)}_{\frac{1}{d(x)}} = \pi(y) \ub{P(y, x)}_{\frac{1}{d(y)}} \] so $\pi$ must satisfy \[ \pi(x) \frac{1}{d(x)} = \pi(y) \frac{1}{d(y)} \quad \forall (x, y) \in E \] Taking $\nu(x) = d(x)$, then $\nu$ is an invariant measure. So \[ \pi(x) = \frac{d(x)}{\sum_{y \in V} d(y)} = \frac{d(x)}{2|E|} \] So simple random walk on $G$ is \emph{reversible}. \end{example*} \subsubsection*{Convergence to equilibrium} \begin{theorem*} $I$ \emph{finite}, $i \in I$ such that $\forall j$ \[ p_{ij}(n) \to \pi(j) \] as $n \to \infty$. Then $\pi$ is invariant. \end{theorem*} \noindent $P$ has invariant distribution $\pi$. Question: Under what conditions do we have convergence to $\pi$? \begin{example*} \begin{center} \includegraphics[width=0.6\linewidth] {images/eba5c42a60e411ed.png} \end{center} $p + q = 1$, $p = \frac{2}{3}$, $q = \frac{1}{3}$ $P^n(0, 0)$. If $n$ is odd, then \[ P^n(0, 0) = 0 \] \end{example*} \begin{flashcard} \begin{definition*} $P$ transition matrix, $i \in I$. The period of $i$ is defined \[ d_i = \cloze{\gcd \{n \ge 1 : P^n(i, i) > 0\}} \] $i$ is called \emph{aperiodic} if \cloze{$d_i = 1$.} \end{definition*} \end{flashcard} \begin{flashcard}[period-1-markov-chain-condition] \begin{lemma*} Let $P$ be a transition matrix and $i \in I$. Then $d_i = 1$ if and only if \cloze{\[ P^n(i, i) > 0 \] for all $n$ sufficiently large.} \end{lemma*} \end{flashcard} \begin{proof} \begin{enumerate} \item[$\Leftarrow$] Obvious. \item[$\Rightarrow$] If $d_i = 1$ then want to show $P^n(i, i) > 0$ for all $n$ large enough. \[ D(i) = \{n \ge 1 : P^n(i, i) > 0\} \] Observation: if $n, m \in D(i)$ then $n + m \in D(i)$. So suffices to prove that $D(i)$ contains 2 consecutive integers. Say it contains $m, m + 1$. Then by the observation it will also contain $am + b(m + 1)$ for all $a, b \in \NN$. One can check that \[ D(i) \supset \{n : n \ge m^2\} \] Suppose $\min\{x - y : x > y, x, y \in D(i)\} = r \ge 2$. Let $n, m \in D(i)$ such that $n = m + r$. Then there exists $k = lr + s$ with $0 < s < r$, $l \in \NN$ such that $k \in D(i)$. If there does not exist such $k$, then all elements of $D(i)$ would be multiples of $r$, and hence gcd $D(i)$ would be $r$, contradiction. \\ Let $a = (l + 1)n$ and $b = (l + 1)m + k$. By observation, $a, b \in D(i)$. \[ a - b = r - s < r \] so $r = 1$, so $D(i)$ contains 2 consecutive integers. \end{enumerate} \end{proof} \begin{lemma*} If $P$ is irreducible and $i \in I$ is aperiodic, then all states are aperiodic. \end{lemma*} \begin{proof} Let $j \in I$. There exists $r, s \ge 0$ such that \[ P^r(i, j) > 0 \text{ and } P^s(j, i) > 0 \] (by irreducibility) \[ P^{n + r + s}(j, j) \ge P^s(j, i) P^n(i, i) P^r(i, j) > 0 \] for all $n$ sufficiently large. \end{proof}