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-rw-r--r--figures/invariant_perturbed_ol.pdfbin10048 -> 21026 bytes
-rwxr-xr-xmain.tex140
2 files changed, 86 insertions, 54 deletions
diff --git a/figures/invariant_perturbed_ol.pdf b/figures/invariant_perturbed_ol.pdf
index 0d01681..1e40bd1 100644
--- a/figures/invariant_perturbed_ol.pdf
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diff --git a/main.tex b/main.tex
index c6117c6..7596b40 100755
--- a/main.tex
+++ b/main.tex
@@ -220,6 +220,92 @@
\end{frame}
\begin{frame}
+ {Nonequilibrium overdamped Langevin dynamics}
+ In general, can we prove existence of and convergence to an invariant measure for
+ \[
+ \d q_t = - \grad V(q_t) \, \d t + \alert{\eta F} + \sqrt{2} \, \d W_t \, ?
+ \]
+
+ \begin{itemize}
+ \item
+ If the state space is compact (e.g. $\torus^d$),
+ then we can apply Doeblin's theorem.
+
+ \item
+ If not, we can apply its generization, Harris' theorem.
+ \end{itemize}
+
+ \medskip
+ Fix $t > 0$ and denote by $p\colon \mathcal E \times \mathcal B(\mathcal E)$ the Markov transition kernel
+ \[
+ p(x, A) := \proba \left[ q_t \in A \, \middle| \, q_0 = x \right].
+ \]
+ For an observable $\phi \colon \mathcal E \to \real$ and a probability measure $\mu$,
+ we let
+ \[
+ (\mathcal P \phi)(x) := \int_{\mathcal E} \phi(y) \, p(x, \d y),
+ \qquad
+ (\mathcal P^{\dagger} \mu)(A) := \int_{A} p(x, A) \, \mu(\d x).
+ \]
+ Note that $\mathcal P$ and $\mathcal P^{\dagger}$ are formally $L^2$ adjoints:
+ \[
+ \int_{\mathcal E} (\mathcal P \phi) \, \d \mu = \int_{\mathcal E} \phi \, \d (\mathcal P^\dagger \mu).
+ \]
+\end{frame}
+
+\begin{frame}
+ {Existence of an invariant measure (1/2)}
+ Remember that the set of probability measures with TV distance $d(\placeholder, \placeholder)$ is complete.
+ \begin{theorem}
+ [Doeblin's theorem]
+ If there exists $\alpha \in (0, 1)$ and a probability measure $\eta$ such that
+ \[
+ \mathcal P^{\dagger} \mu \geq \alpha \eta,
+ \]
+ then there exists $\mu_{\infty}$ such that $\mathcal P^{\dagger} \mu_{\infty} = \mu_{\infty}$.
+ Furthermore $d(\mathcal P^{\dagger^n} \mu, \mu_{\infty}) \leq \alpha^n d(\mu, \mu_{\infty})$.
+ \end{theorem}
+
+ \emph{Sketch of proof.} Define the Markov transition kernel
+ \[
+ \widetilde {p}(x, \placeholder) := \frac{1}{1-\alpha} p(x, \placeholder) - \frac{\alpha}{1 - \alpha} \eta(\placeholder),
+ \]
+ Let $\mathcal F$ denote the set of measurable functions $\phi \colon \mathcal E \to [-1, 1]$.
+ We have
+ \begin{align*}
+ d(\mathcal P^\dagger \mu, \mathcal P^\dagger \nu)
+ &= \sup_{\phi \in \mathcal F} \int_{\mathcal E} \phi(q) (\mathcal P^{\dagger} \mu - \mathcal P^{\dagger} \nu) (\d q)
+ = \sup_{\phi \in \mathcal F} \int_{\mathcal E} \mathcal P \phi(q) \bigl(\mu - \nu\bigr) (\d q) \\
+ &= (1 - \alpha) \sup_{\phi \in \mathcal F} \int_{\mathcal E} \widetilde {\mathcal P} \phi(q) (\mu - \nu) (\d q)
+ \leq (1 - \alpha) \, d(\mu, \nu).
+ \end{align*}
+ Conclude using Banach's fixed point theorem.
+\end{frame}
+
+\begin{frame}
+ {Existence of an invariant measure (2/2)}
+ \begin{itemize}
+ \item
+ Suppose that $\phi$ is uniformly bounded. Then
+ \begin{align*}
+ \left\lvert \mathcal P^n \phi(x) - \overline \phi \right\rvert
+ &= \int_{\mathcal E} \mathcal P^n (\phi - \overline \phi) \, \d(\delta_x - \mu_{\infty})
+ = \int_{\mathcal E} (\phi - \overline \phi) \, (\mathcal P^{\dagger n} \delta_x - \mathcal P^{\dagger n} \mu_{\infty}) (\d q) \\
+ &\leq \norm{\phi - \overline \phi}_{L^{\infty}} (1-\alpha)^n d(\delta_x, \mu_{\infty})
+ \leq 2 \norm{\phi - \overline \phi}_{L^{\infty}} (1 - \alpha)^n.
+ \end{align*}
+
+
+ \item
+ In molecular dynamics, this theorem can be employed for showing existence of and convergence to the invariant measure,
+ provided that the \blue{state space is compact}.
+
+ \item
+ For \alert{noncompact state spaces}, an extension called \emph{Harris' theorem}
+ \end{itemize}
+\end{frame}
+
+\begin{frame}
{Existence of an invariant measure for noneq.\ dynamics}
Consider the paradigmatic dynamics
\begin{align*}
@@ -263,60 +349,6 @@
Then apply the main theorem from~\footfullcite{MR2857021}.
\end{frame}
-\begin{frame}
- {Existence of an invariant measure (1/2)}
- For a Markov transition kernel~$\mathcal P\colon \mathcal E \times \mathcal B(\mathcal E) \to [0, 1]$, let
- \[
- (\mathcal P \phi)(x) := \int_{\mathcal E} \phi(y) \, \mathcal P(x, \d y),
- \qquad
- (\mathcal P^{\dagger} \mu)(A) := \int_{A} \mathcal P(x, A) \, \mu(\d x).
- \]
- \begin{theorem}
- [Doeblin's theorem]
- If there exists $\alpha \in (0, 1)$ and a probability measure $\eta$ such that
- \[
- \mathcal P^{\dagger} \mu \geq \alpha \eta,
- \]
- then there exists $\mu_{\infty}$ such that $\mathcal P^{\dagger} \mu_{\infty} = \mu_{\infty}$.
- Furthermore $d(\mathcal P^{\dagger^n} \mu, \mu_{\infty}) \leq \alpha^n d(\mu, \mu_{\infty})$.
- \end{theorem}
-
- \emph{Sketch of proof.}
- Use Banach's fixed point theorem. Define the Markov transition
- \[
- \widetilde {\mathcal P}(x, \placeholder) := \frac{1}{1-\alpha} \mathcal P(x, \placeholder) - \frac{\alpha}{1 - \alpha} \eta(\placeholder).
- \]
- Let $V$ denote the set of measurable functions $\phi \colon \mathcal E \to [-1, 1]$.
- We have
- \begin{align*}
- d(\mathcal P^\dagger \mu, \mathcal P^\dagger \nu)
- &= \sup_{\phi \in V} \int_{\mathcal E} \phi(q) (\mathcal P^{\dagger} \mu - \mathcal P^{\dagger} \nu) (\d q)
- = \sup_{\phi \in V} \int_{\mathcal E} \mathcal P \phi(q) \bigl(\mu - \nu\bigr) (\d q) \\
- &= (1 - \alpha) \sup_{\phi \in V} \int_{\mathcal E} \widetilde {\mathcal P} \phi(q) (\mu - \nu) (\d q)
- \leq (1 - \alpha) \, d(\mu, \nu).
- \end{align*}
-\end{frame}
-
-\begin{frame}
- {Existence of an invariant measure (2/2)}
- \begin{itemize}
- \item
- Suppose that $\phi$ is uniformly bounded and let $\overline \phi = \int_{\mathcal E} \phi \, \d \mu_{\infty}$. Then
- \[
- \Bigl\lVert \mathcal P \left(\phi - \overline \phi\right) \Bigr\rVert_{L^\infty}
- = (1 - \alpha) \Bigl\lVert \widetilde {\mathcal P} (\phi - \overline \phi) \Bigr\rVert_{L^{\infty}}
- \leq (1 - \alpha) \Bigl\lVert \phi - \overline \phi \Bigr\rVert_{L^{\infty}},
- \]
-
-
- \item
- In molecular dynamics, this theorem can be employed for showing existence of and convergence to the invariant measure,
- provided that the \blue{state space is compact}.
-
- \item
- For \alert{noncompact state spaces}, an extension called \emph{Harris' theorem}
- \end{itemize}
-\end{frame}
\begin{frame}
{Linear response of nonequilibrium dynamics (1)}