12.3 Cauchy-Kovalevskaya Theorem

Definition 12.3.1 (Setting and Non-Characteristics).label Suppose

\begin{align*}\begin{cases}F(x,\parens{\pd^\al u}_{\abs{\al}\leq k})=0\\ \pd_{\nu}^{j}u|_{S}=\p_{j}&0\leq j\leq k-1\end{cases}\end{align*}

such that

\begin{align*}\begin{cases}F\in C^{\om}\\ s\in C^{\om}\end{cases}\end{align*}

then when $\exists! C^{\om}$ solution $u$ in a neighborhood $\OM$? By constant rank theorem, we can change coordinates so that locally, $S$ is given by $t=0$, $(\UBC{x_1,...,x_{n-1}}{x},t)$ coordinates. The Cauchy problem then becomes

\begin{align*}\begin{cases}F(x,t,\parens{\pd_x^\al\pd_t^ju}_{\abs{\al}+j\leq k})=0\\ \parens{\pd_t^ju}(x,0)=\p_{j}(x)&1\leq j\leq k-1\end{cases}\end{align*}

We remark that Cauchy data determine all derivatives $\parens{\pd_x^\al\pd_t^j}u(x,0)$ as long as $j\leq k-1$. So the only derivative of $u$ which are unknown on $S$ are $\parens{\pd_t^ku}(x,0)$.

$S$ (given by $t=0$) is non-characteristic for

\begin{align*}\begin{cases}F(x,t,\parens{\pd_x^\al\pd_t^ju}_{\abs{\al}+j\leq k})=0\\ \parens{\pd_t^ju}(x,0)=\p_{j}(x)&1\leq j\leq k-1\end{cases}\end{align*}

if one can solve for $\pd_{t}^{k}u$.

Example 12.3.2 (What can go wrong?).label

  1. (1)

    Lack of Uniqueness

    \begin{align*}\begin{cases}\pd_{t}\pd_{x} u=0&u(x,0)=\p_{0}(x)\\ (x,t)\in\R^{2}&\pd_{t}u(x,0)=\p_{1}(x)\end{cases}\end{align*}

    $t=0$ in characteristic. Observe

    \begin{align*}(\pd_{t}\pd_{x}u)(x,0)=0\implies \pd_{x}\p_{1}(x)=0\implies \p_{1}\text{ const}\end{align*}

    So the Cauchy problem has no solutions unless $\p_{1}$ is constant. Suppose that $\p_{1}$ is constant then

    \begin{align*}u(x,t)=\p_{0}(x)+f(t)\end{align*}

    where $f$ is any function such that $f'(0)=\p_{1}$ then we have no uniqueness of solution.

  2. (2)

    Dependence of Cauchy Data $\pd_{x}^{2}u-\pd_{t}u=0$, $t=0$ in characteristic. Suppose that $u$ is a solution with $u(x,0)=\p_{0}(x)$. Then $(\pd_{t}u)(x,0)=\pd_{xx}u(x,0)=\p_{0}''(x)$. Then $\p_{1}\define (\pd_{t}u)(x,0)$ is determined by $\p_{0}$ i.e. choosing $\p_{0}$ forces the choices of $\p_{1}$. Looking at characteristic tell us this also since

    \begin{align*}\chi=\xi_{x}^{2}=0\iff\xi_{x}=0\end{align*}

    so $(\xi_{x},\xi_{t})$ characteristic normal direction is given by $(0,const)$ in particular $t=const$ are characteristic curves.

Proposition 12.3.3.label If $G,\p_{0},...,\p_{k-1}$ are $C^{\om}$, then the PDE has at most one $C^{\om}$ solution.

Proof. We assume $t=0$ to be non-characteristic, Cauchy problem becomes $\begin{cases}\pd_{t}^{k}u=G(x,t,\parens{\pd_x^\al\pd_t^ju}_{\abs{\al}+j\leq k,0\leq j\leq k-1})\\ \pd_{t}^{j}u(x,0)=\p_{j}(x),0\leq j\leq k-1\end{cases}$ Then $\pd_{t}^{k+1}u$ is determined on $t=0$ by the PDE and

\begin{align*}\pd_{t}^{k+1}u=\pder{G}{t}+\sums{}{\abs{\al}+j\leq k}\pder{G}{u_{\al j}}\pd_{x}^{\al} \pd_{t}^{j+1}u\end{align*}

By induction, we are done.$\square$

Lemma 12.3.4.label The Cauchy Problem in Proposition 12.3.3 is equivalent to a quasi-linear system of $1^{st}$-order PDEs

\begin{align*}\begin{cases}\pd_{t}Y=\sums{n-1}{j=1}A_{j}(x,t,Y)\pd_{j}Y+B(x,t,Y)\\ Y(x,0)=\Phi(x)\end{cases}\end{align*}

where $Y=\begin{pmatrix}Y_{1}\\ \vdots\\ Y_{N}\end{pmatrix} =(y_{\al j})_{0\leq \abs{\al}+j\leq k,0\leq j\leq k-1},A_{i}=(a^{i}_{\el m})_{1\leq i\leq n-1;m,l=1,...,N},B=\begin{pmatrix}b_{1}\\ \vdots\\ b_{N}\end{pmatrix}$ and $\Phi$ is determined by $\p_{j}$.

Proof. Check Folland. The reason one can go forward is easy to see, simply differentiate. The reason one can go back is because of the holomorphic dependency of Cauchy data $Y(x,0)$ on the $\p_{j}$$\square$

Example 12.3.5 (Proof of Lemma 12.3.4 in Example).label Consider

\begin{align*}\begin{cases}u_{tt}=f(u_{xx},u_{xt})\\ u(x,0)=\p_{0}(x)&\parens{\pd_tu}(x,0)=\p_{1}(x)\end{cases}\end{align*}

Here $Y=(y_{00},y_{10},y_{01},y_{20},y_{11},y_{02})$ with notation $y_{xt}$. First we differentiate to get equation as in Lemma 12.3.4

\begin{align*}\pder{y_{00}}{t}&=y_{01}\\ \pder{y_{10}}{t}&=y_{11}\\ \pder{y_{01}}{t}&=y_{02}\\ \pder{y_{20}}{t}&=\pder{y_{11}}{x}\\ \pder{y_{11}}{t}&=\pder{y_{02}}{x}\\ \pder{y_{02}}{t}&=f_{1}(y_{20},y_{11})\pder{y_{20}}{t}+f_{2}(y_{20},y_{11})\pder{y_{11}}{t}=f_{1}(y_{20},y_{11})\pder{y_{11}}{x}+f_{2}(y_{20},y_{11})\pder{y_{02}}{x}\end{align*}

Along with initial conditions

\begin{align*}y_{00}(x,0)&=\p_{0}(x)\\ y_{10}(x,0)&=(\pd_{x}\p_{0})(x)\\ y_{01}(x,0)&=\p_{1}(x)\\ y_{20}(x,0)&=(\pd_{x}^{2}\p_{0})(x)\\ y_{11}(x,0)&=(\pd_{x}\p_{1})(x)\\ y_{02}(x,0)&=f((\pd_{2}^{2}\p_{0})(x),(\pd_{x}\p_{1})(x))\end{align*}

So we see that solution to Proposition 12.3.3 give solution to Lemma 12.3.4.

Now we show that solution to Lemma 12.3.4 give solution to Proposition 12.3.3.

\begin{align*}y_{20}(x,t)=\pd_{x}y_{10}+c_{20}(x)\\ y_{11}(x,t)=\pd_{x}y_{01}+c_{11}(x)\\ y_{20}(x,0)=\pd_{x}^{2}\p_{0}(x)=\pd_{x}(\pd_{x}\p_{0}(x))=(\pd_{x}y_{10})(x,0)\end{align*}

By first and third equation $c_{20}(x)=0$ and similarly one can show $c_{11}(x)=0$. It remains to show $y_{10}=\pd_{x}y_{00},y_{01}=\pd_{t}y_{00}$

\begin{align*}\pd_{t}y_{02}&=f_{1}\pd_{x}y_{11}+f_{2}\pd_{x}y_{02}\\&=f_{1}\pd_{t}y_{20}+f_{2}\pd_{t}y_{11}=\pd_{t}f\\ y_{02}=f(y_{20},_{11})+c_{02}(x)\end{align*}

Compare with $y_{02}(x,0)$ give $c_{02}(x)=0$. Finally

\begin{align*}\pder{y_{10}}{t}=y_{11}=\pd_{x}y_{01}=\pd_{x}\pd_{t}y_{00}=\pd_{t}\pd_{x}y_{00}\\ y_{10}=\pd_{x}y_{00}+c_{10}(x)\end{align*}

OTOH, imposing again initial conditions

\begin{align*}y_{10}(x,0)=\pd_{x}\p_{0}(x)=\pd_{x}y_{00}(x,0)\implies c_{10}(x)=0\end{align*}

Similarly for $y_{01}$.

Lemma 12.3.6.label The Cauchy problem in Lemma 12.3.4 is equivalent to a Cauchy problem of the same form with $A_{j}$ and $B$ independent of $t$ and $\Phi=0$.

Proof. Set $U(x,t)\define Y(x,t)-\Phi(x)$ the system becomes

\begin{align*}\begin{cases}\pd_{t}U=\sums{n-1}{\el=1}A_{\el}(x,t,U+\Phi)\pd_{\el} U+B(x,t,U+\Phi)\\ U(x,0)=0\end{cases}\end{align*}

We eliminate $t$ by adding component $u^{0}$ to $U,\begin{pmatrix}u^{0}\\U\end{pmatrix}$ then

\begin{align*}\pd_{t}u^{0}=1&&u^{0}(x,0)=0\end{align*}

[1]$\square$

Lemma 12.3.7 (Facts about $C^{\om}$ functions).label

  1. (1)

    $f$ is analytic near $x_{0}$ then there exists a cube $\OM=\curl{x:\abs{x_j-x_j^0}<r,1\leq j\leq n}$ such that $\sums{}{\al}\frac{1}{\al!}\parens{\pd^\al f}(x_{0})(x-x_{0})^{\al}$ converges to $f(x)$ for all $x\in\OM$ and convergence is uniform and absolute on compact subsets of $\OM$.

  2. (2)

    Let $f(x)=\sums{}{}a_{\al}(x-x_{0})^{\al}$ be convergent enar $x_{0}$ and $x$ be an analyhtic function of $\xi$

    \begin{align*}x=\sums{}{\be}b_{\be}(\xi-\xi_{0})^{\be}\end{align*}

    with $x(\xi_{0})=x_{0}$. Then

    \begin{align*}F(\xi)=f(x(\xi))\end{align*}

    is analytic at $\xi_{0}$ and power series representation of $F$ is obtained by substitution

    \begin{align*}F(\xi)=\sums{}{\gam}c_{\gam}(\xi-\xi_{0})^{\gam}\end{align*}

    where

    \begin{align*}c_{\gam}=P_{\gam}(a_{\al},b_{\be})\end{align*}

    are universal polynomials with non-negative coefficients. (This is an algebraic fact about rings of power series)

  3. (3)

    Given $M,r>0$ the function

    \begin{align*}f(x)=\frac{Mr}{r-\parens{\sums{n}{i=1}x_i}}\end{align*}

    is analytic in the rectangle $\curl{x:\MAX{i}\abs{x_j}<r/n}$ and

    \begin{align*}f(x)=M \sums{\infty}{k=0}\frac{\parens{\sums{n}{i=1}x_i}^{k}}{r^{k}}=M \sums{}{\abs{\al}\geq0}\frac{\abs{\al}!}{\al!r^{\abs{\al}}}x^{\al}\end{align*}

  4. (4)

    We say that $\sums{}{\al}a_{\al}(x-x_{0})^{\al},a_{\al}\geq 0$ majorizes $\sums{}{\al }b_{\al}(x-x_{0}^{\al})$ if $a_{\al}\geq\abs{b_\al}$. In which case $\sums{}{\al }b_{\al}(x-x_{0}^{\al})$ converges absolutely whenever $\sums{}{\al }a_{\al}(x-x_{0}^{\al})$ does.

  5. (5)

    Suppose that $\sums{}{\al }a_{\al}(x-x_{0}^{\al})$ in a rectangle $\curl{x:\MAX{i}\abs{x_i}<R }$ then $\exists$ geoemetric series as in (3) majorizing $\sums{}{\al }a_{\al}(x-x_{0}^{\al})$. Indeed let $x=(r,...,r),r<R$, $x\in$ rectangle. So $\exists M>0$ such that $\abs{a_\al r^{\abs{\al}}}\leq M$, $\fall \al$. So $\abs{a_\al}\leq\frac{M}{r^{\abs{\al}}}\leq \frac{M\abs{\al}!}{r\al!}$

If $A_{i},B$ are $C^{\om}$ near $0$ in $\R^{n-1}\ti\R^{N}$, then $\exists! C^{\om}$ solution near $0$ in $\R^{n}=\R^{n-1}\ti\R$.

Theorem 12.3.8 (Cauchy-Kovalevskaya).label If $G,\p_{0},...,\p_{k-1}$ are $C^{\om}$ then the PDE has a unique $C^{\om}$ solution.

Proof. We can rewrite Lemma 12.3.4 as

\begin{align*}\pd_{t}y_{m}=\sums{n-1 }{i=1}\sums{N }{l=1}a^{i}_{ml}(x,y_{1},...,y_{N})\pd_{i}y_{l}+b_{m}(x,y_{1},...,y_{N})\end{align*}

We seek $y_{m}$ of the form $y_{m}=\sums{}{}c_{m}^{\al j}x^{\al} t^{j}$. Impose $Y(x,0)$

\begin{align*}c_{m}^{\al0}=0&&\fall \al,m\end{align*}

So we must determine $c_{m}^{\al j}$ for $j>0$. Substitute $y_{m}$ into the PDE, by Lemma 12.3.7(2) the RHS is

\begin{align*}\sums{}{\al,j}P_{m}^{\al j}\parens{(c_k^\be l)_{k\leq j},\text{coeffs of $A_{i},B$}}x^{\al} t^{j}\end{align*}

with non-negative coefficients. The LHS is

\begin{align*}\sums{}{\al,j}(j+1)c_{m}^{\al j+1}x^{\al} t^{j}\end{align*}

So equating coefficients of $x^{\al+j}$

\begin{align*}c_{m}^{\al j+1}=\frac{1}{j+1}P_{m}^{\al j}(c,\text{coeff of $A_{i},B$})\end{align*}

Inductively we have polynomials of non-negative coefficients $Q_{m}^{\al j}$

\begin{align*}c_{m}^{\al j}=Q_{m}^{\al j}(\text{coeff of $A_{i},B$})\end{align*}

Next we construct a system

\begin{align*}\begin{cases}\pd_{t}\til{Y}=\sums{n-1}{i=1}\til{A_i}(x,\til{Y})\pd_{i} \til{Y}+\til{B}(x,\til{Y})\\ \til(Y)(x,0)=c\end{cases}\end{align*}

such that $\til{A_i},\til{B}$ are $C^{\om}$, the system has a $C^{\om}$ solution near $0\in \R^{n-1}\ti\R$ and Taylor series of $\til{A_i},\til{B}$ majorizes those of $A_{i},B$. By Lemma 12.3.7(3,5), if $M>0$ is sufficiently large and $r>0$ is sufficiently small, the series for $A_{i},B$ can be majorized by (geometric) series for

\begin{align*}\frac{Mr}{r-\sums{n-1}{i=1}x_{i}-\sums{N }{j=1}y_{j}}\end{align*}

Consider now the Cauchy problem

\begin{align*}\begin{cases}\pd_{t}y_{m}=\frac{Mr}{r-\sums{n-1}{i=1}x_i-\sums{N }{j=1}y_j}\parens{\sums{n-1}{i=1}\sums{N}{j=1}\pd_iy_j+1}\\ y_{m}(x,0)=0\end{cases}\end{align*}

It remains to show this has a $C^{\om}$ solution near $0$. By utilizing symmetry we claim $u$ as follows is such a solution. Let $y_{j}\define u(x_{1}+\cds+x_{n-1},t)_{1\leq j\leq N}$ where $u=u(s,t)$ solves

\begin{align*}\begin{cases}\pd_{t}u=\frac{Mr}{r-s-Nu}\parens{N(n-1)\pd_su+1}\\ u(s,0)=0\end{cases}\end{align*}

We now solve for $u$ by method of characteristic.

\begin{align*}\der{t}{\tau}=r-s-Nu&&\der{s}{\tau}=-MrN(n-1)&&\der{u}{\tau}=Mr\\ t(0)=0&&s(0)=\s\text{ parametrized along initial curve}&&u(0)=0\end{align*}

where $\tau$ is the flow parameter, then $\der{^2t}{\tau^2}$ is constant. After some simple calculations

\begin{align*}t&=\frac{1}{2}MrN(n-2)\tau^{2}+(r-\s)\tau\\ u&=Mr\tau\\ s(\tau)&=-MrN(n-1)\tau+\s\\ u(s,t)&\define u(\tau(s,t),\s(s,t))\\&=Mr\tau(s,t)\\&=\frac{r-s-\sqrt{(r-s)^{2}-2MrNt}}{Mn}\in C^{\OM}\text{ near 0}\\ u(s,0)=0\end{align*}

$\square$

Remark 12.3.9.label It may happen that the PDE have more than one solution in the sense that there exists non-analytic (say $C^{\infty}$) solution in addition to the $C^{\om}$ solution.

If there are points where $\pder{F}{\pd{\pd_t^k u}}=0$ there is a version of Cauchy-Kovalevskaya called the Ramified C-K theorem proved by J-Leray (1970’s) Garding wrote something on this.

Theorem 12.3.10 (Holmyer).label If the PDE is linear then the solution is unique.

Remark 12.3.11 (J. Hadamard).label Does the unique $C^{\om}$ solution of a CK equation depend “continuously” on the Cauchy data in any reasonable sense? No. Consider

\begin{align*}\begin{cases}\pd_{1}^{2}u+\pd_{2}^{2}u=0\\ u(x_{1},0)=0&&(\pd_{2}u)(x_{1},0)=ke^{-\sqrt{k}}\sin(kx_{1})\end{cases}\end{align*}

$x_{2}=0$ we have $S$ is non characteristic

\begin{align*}\pd_{2}^{2}u=-\pd_{1}^{2}u\end{align*}

There exists unique $C^{\om}$ solution

\begin{align*}u(x_{1},x_{2})=e^{-\sqrt{k}}\sin(kx_{1})\sinh(kx_{2})\end{align*}

As $k\to\infty$, Cauchy data and all derivatives $\to 0$. For $x_{2}>0$, $u(x_{1},x_{2})\to\infty$. OTOH $\pd_{1}^{2}u+\pd_{2}^{2}u=0$, $u(x_{1},0)=0,\pd_{2}u(x_{1},0)$ has unique $C^{\om}$ solution $u(x_{1},x_{2})=0$ for all $(x_{1},x_{2})\in\R^{2}$.

Let $\cali{H}$ be a Hilbert space. The strong operator topology on $\cali{B}(\cali{H})$ is the one generated by the seminiorm $x\mto \norm{x\xi}{},\xi\in\cali{H}$ that is $x_{\al}\to x\iff\iff\fall \xi\in\cali{H},\norm{x_\al\xi-x\xi}\to0$. The weak opeartor topology similarly is generated by $x\mto\inner{x\xi}{\eta},\xi,\eta\in\cali{H}$ i.e. $x_{\al}\to x\iff \fall \xi,\eta\in\cali{H},\inner{x_\al\xi,\eta}\to \inner{x\xi}{\eta}$. A von-Neumann algebra (acting on $\cali{H}$) is a $*$-algebra $A\suf\cali{B}(\cali{H})$ which is closed in the strong operator topology.

Example 12.3.12.label Let $S\suf\cali{B}(\cali{H})$ and consider $S'\define \curl{x\in\cali{B}(\cali{H}):xy=yx,\fall y\in S}$ which is WOT-closed, so if $S=S^{*}$ then $S'$ is a von Neumann algebra. Observe

  1. (1)

    $S\suf S''$

  2. (2)

    If $S_{1}\suf S_{2}$ then $S_{2}'\suf S_{1}'$

  3. (3)

    $S'=S'''$

That is to say the bigger the underlying set $S$ is, the harder it is to “commute” that is belongs to $S'$.

Let $(X,\mu)$ be a probability space, $\cali{H}\define L^{2}(X,\mu)$, and $A=L^{\infty}(X,\mu)$. Consider the map $M:A\to \cali{B}(\cali{H})$ defined by $f\mto M_{f}=(\xi\mto f\cd \xi)$ then

  1. (1)

    $\norm{f}{\infty}=\norm{M_f}{}$, in particular $A\suf\cali{B}(\cali{H})$

  2. (2)

    $A=A'$ so $A$ is a von Neumann algebra and is a maximal abelian sub-algebra

  3. (3)

    $M_{f}^{*}=M_{\cl{f}}$

Theorem 12.3.13 (Von Neumann Bicommutant).label Let $A\suf\cali{B}(\cali{H})$ be a $*$-algebra then TFAE:

  1. (1)

    $A=A''$

  2. (2)

    $A$ is weakly closed

  3. (3)

    $A$ is strongly closed

Proof. (1)$\implies$(2)$\implies$(3) is trivial. Suppose (3) hold then note $A\suf A'$ so let $x\in A''$. We want to show $\fall n\geq 1,\fall \curl{\xi_i}_{1}^{n}\suf\cali{H},\fall \e>0,\exists y\in A:\norm{(x-y)\xi_i}{}<\e,\fall i\leq n$. First assume $n=1$, fix $\xi\in\cali{H}$ and let $K=\cl{A\xi}$. Let $p=proj_{K}\in\cali{B}(\cali{H})$ then

  1. (1)

    $K$ is $A$-invariant

  2. (2)

    $K^{*}$ is $A$-invariant

then $p\in A'$ so $px=xp$. Now $\xi=1\xi\in A\xi\in K$ so $p\xi=\xi$ so $p(x\xi)=xp\xi=x\xi$ showing $x\xi\in K$. In general, fix $\xi_{1},...,\xi_{n}\in\cali{H}$ and consider $\cali{H}^{\op n}$ and let $\tea:\cali{B}(\cali{H})\to \cali{B}(\cali{H}^{\op n})$ be the natural map. Set $\cali{B}=\tea(A)$ then $\tea(x)\in \cali{B}''$.$\square$

Corollary 12.3.14.label For $S\suf\cali{B}(\cali{H})$, $S''$ is the von Neumann algebra generated by $S$ denoted $W^{*}(S)$.

Definition 12.3.15 (Group Von Neumann Algebra).label Let $G$ be a group and

\begin{align*}\lam:G&\inj U(\el^{2}(G))\\ g&\mto\lam_{g}\end{align*}

then $\lam_{g}(\de_{t})=\de_{gt}$. The group von Neumann algebra of $G$ is $L(G)=\cl{Span(\lam(G))}$ under SOT.

[2]

Remark 12.3.16.label For a group $G$, let $\lam$ be left regular represention on $\el^{2}(G)$, $L(G)$ the SOT closure of the the linear space of $\lam$ in $B(\el^{2}(G))$ then $L(G)$ commutes with $R(G)$ and $L(G)=R(G)'$.

Definition 12.3.17 (States and Traces).label Let $\p$ be a linear functional $\p$ on a von Neumann algebra $M$ then $\p$ is

  1. (1)

    positive if $\p(x^{*}x)\geq 0$ for all $x\in M$

  2. (2)

    faithful if $\p(x^{*}x)=0\implies x=0$

  3. (3)

    state if $\p(1)=1$

A positive linear functional $\p$ is a trace if $\p(xy)=\p(yx)$ for all $x,y\in M$. If $\p$ is also a trace then we call it a tracial state

For a vNA $M$ acting on $\cali{H}$, $\xi\in\cali{H}$ is cyclic for $M$ if $M\xi$ is dense in $\cali{H}$. $\xi\in\cali{H}$ is separating for $M$ if $x\xi\neq 0$ whenever $x\neq 0$.

We can observe that in $L(G)$, $\de_{e}$ is cyclic and separating[3].

Definition 12.3.18 (Tracial vNA).label Let $\tau(x)\define \inner{\de_e}{x\de_e}$ for $x\in L(G)$ then $\tau(1)=\inner{\de_e}{\de_e}=1$ and $\tau(\lam(s_{1})\lam(s_{2}))=\inner{\de_e}{\de_{s_1s_2}}\neq0\iff s_{1}s_{2}=e$. $\tau$ is continuous w.r.t. the WOT.

A tracial von Neumann algebra is a vNA $M$ equipped with a faithful tracial state that is WOT continuous restricted to the unit ball.

Definition 12.3.19 (Factors).label We have finite dimensional tracial vNAs, $M_{n}(\com)$ equipped with $\frac{1}{n}Tr=:\tau$. A $II_{1}$ factor is an infinite dimensional tracial vNA whose centre is reduced to the scalar operator.

A factor is of type $I$ if it is isomoprhic to $\cali{B}(\cali{H})$

Let $(X,\mu)$ be a probability space, $E$ countable Borel equivalence relation on $X$ then $E$ has countable classes and $E\suf X^{2}$ is Borel. We define the measure $\nu$ on $E$ as

\begin{align*}\nu(A)\define \integral{}{}\abs{A_x}d\mu(x)\end{align*}

then $L^{2}(E,\nu$) is a Hilbert space and $\nu$ is $\s$-finite measure as a consequence of Luzin. We define $\cali{M}_{b}(E)$ to be bounded finitely supported Borel functions $f:E\to\com$ where $\exists C>0,\fall x,y$ we have $\abs{z\in X:F(z,y)\neq 0},\abs{z\in X:F(x,z)\neq 0}\leq C$. Denote $B_{b}(X)$ the bounded Borel functions on $X$ then $f\mto f(x)\indi{\la}$ is an injection $B_{b}(X)\inj \cali{M}_{b}(E)$. $E$ is probabiliity measure preserving (pmp) if for any Borel automorphism $f:X\to X$ such that $xEf(x),f_{*}\mu=\mu$.

  1. This is a simple trick in dynamics to make nonautonamous to autonamous equation by making time into a variablekeyboard_return
  2. Some important examples are group measure space algebra, algebra of a pmp CBER, hyperfinite $\Pi_{1}$ factorkeyboard_return
  3. comes from $L(G)\suf R(G)'$keyboard_return

Post a Comment

Name:Email:
Please enter the tag of the current page (A5) to post the comment.
Tag: