Let
We see that
It is positive
and symmetric and plays the role of the Laplacian on
Positivity
follows by setting
The operator
Proposition
The Hermite polynomials are eigenvectors for the Ornstein-Uhlenbeck operator.
Moreover, for any multi-index
Proof.
Again consider
So,
Thus
system. Hence
We now turn to the Ornstein-Uhlenbeck semigroup, i.e., the semigroup generated
by
Let
In particular
It follows that
Any
It is not
essential here that we work in our Gaussian setting. Any
Integrating both
sides in
\left|\left|Tf\right|\right|^{2}\le\left|\left|\Phi\right|\right|_{L^{2}(\gamma\times\gamma)}^{2}\left|\left|f\right|\right|^{2}.
We now leave the
general situation. The operator T_{t}
T_{t}f(x)=\int_{\mathbb{R}^{d}}M_{t}^{\gamma}(x,y)f(y)d\gamma(y).
The explicit
expression for this kernel was found already in 1866 by Mehler. It is named the
Mehler kernel. Using the normalized Hermite polynomials h_{\alpha}
M_{t}^{\gamma}(x,y)=\sum_{\alpha\in\mathbb{N}^{d}}e^{-t|\alpha|}h_{\alpha}(x)h_{\alpha}(y).
It is easy to
check that this series converges in L^{2}(\gamma\times\gamma)
\sum_{|\alpha|<N}e^{-t|\alpha|}h_{\alpha}(x)h_{\alpha}(y).
For |\beta|<N
\int\sum_{|\alpha|<N}e^{t|\alpha|}h_{\alpha}(x)h_{\alpha}(y)H_{\beta}(y)d\gamma(y)=e^{-t|\beta|}<h_{\beta},H_{\beta}h_{\beta}(x)=e^{-t|\beta|}\left|\left|H_{\beta}\right|\right|h_{\beta}(x)=e^{-t|\beta|}H_{\beta}=T_{t}H_{\beta}.
Since the
truncated kernels converge in L^{2}(\gamma\times\gamma)
\begin{array}{rcl}H_{n}\left(y\right) & = & \left(-1\right)^{n}e^{\frac{y^{2}}{2}}\frac{d^{n}}{dy^{n}}e^{-\frac{y^{2}}{2}}=\left(-1\right)^{n}e^{\frac{y^{2}}{2}}\frac{d^{n}}{dy^{n}}\frac{1}{\sqrt{2\pi}}\int e^{iy\xi-\frac{^{\xi^{2}}}{2}}d\xi\\& = & \left(-1\right)^{n}e^{\frac{y^{2}}{2}}\frac{i^{n}}{\sqrt{2\pi}}\int\xi^{n}e^{iy\xi-\frac{\xi^{2}}{2}}d\xi.\end{array}
Assuming that the order of summation and integration can be switched. By using the generating function of Hermite polynomial, we get
\begin{array}{rcl}M_{t}^{\gamma} & = & \sum_{n=0}^{\infty}e^{-tn}h_{n}\left(x\right)h_{n}\left(y\right)\\& = & \sum_{n=0}^{\infty}e^{-tn}\frac{1}{n!}H_{n}\left(x\right)\left(-1\right)^{n}e^{\frac{y^{2}}{2}}\frac{i^{n}}{\sqrt{2\pi}}\int\xi^{n}e^{iy\xi-\frac{\xi^{2}}{2}}d\xi\\& = & \frac{1}{\sqrt{2\pi}}e^{\frac{y^{2}}{2}}int\sum_{n=0}^{\infty}\frac{1}{n!}\left(-i\xi e^{-t}\right)^{n}H_{n}\left(x\right)e^{iy\xi-\frac{\xi^{2}}{2}}d\xi\\& = & \frac{1}{\sqrt{2\pi}}e^{\frac{y^{2}}{2}}\int e^{i\xi\left(y-e^{t}x+\frac{\xi^{2}}{2}e^{-2t}\right)}d\xi\end{array}
Let \xi^{t}=\xi\sqrt{1-e^{-2t}} . Then, taking the inverse Fourier transform yields
M_{t}^{\gamma}\left(x,y\right)=\frac{e^{\frac{y^{2}}{2}}}{\sqrt{1-e^{-2t}}}e^{-\frac{\left(y-e^{-t}x\right)^{2}}{1-e^{-2t}}}.
This is a closed expression for the kernel, but it remains to verify the switch of order above. BY using dominated convergence theorem, it is ease to get the conclusion. Let d\ge1 . Then
M_{t}^{\gamma}\left(x,y\right)=\frac{e^{\frac{\left|y\right|^{2}}{2}}}{\sqrt{\left(1-e^{-2t}\right)^{d}}}e^{-\frac{\left|y-e^{-t}x\right|^{2}}{1-e^{-2t}}}.
Making the change of variable z=\frac{y-e^{-t}x}{\sqrt{1-e^{-2t}}} , we get
T_{t}f\left(x\right)=\int M_{t}^{\gamma}\left(x,y\right)f\left(y\right)d\gamma\left(y\right)=\int f\left(e^{-t}x+z\sqrt{1-e^{-2t}}\right)d\gamma\left(z\right).
This is sometimes called Mehler‘s formula.