# Mittag-Leffler family for an integro-differential equation

In a few months ago I post a note about a family of an integro-partial differential equations (2), there the main objective was to expose, without details, a first work to treat questions such as existence and symmetries of solutions in certain critical space, namely, homogeneous Morrey Spaces. On that work the Mittag-Leffler family below was central on the estimates,

$\displaystyle \widehat{u}(t,\xi)=\mathbb{E}_{\alpha}(-t^{\alpha}\vert\xi\vert^2)\widehat{\varphi}(\xi) \ \ \ \ \ (1)$

which is an integral form of the integro-partial differential equation

$\displaystyle u_t(t,x)=\int_{0}^{t}r_{\alpha-1}(t-s) \Delta_{x}u(s,x)ds,\; u(0,x)=\varphi(x) \ \ \ \ \ (2)$

where ${1\leq\alpha<2}$, ${\Delta_{x}=\Sigma_{j=1}^{n}(\partial/\partial x_j)^2}$, ${u(t,x)=(u_{1}(t,x),\cdots,u_{n}(t,x))}$ for ${t\in [0,\infty)}$ and ${x\in\mathbb{R}^{n}}$ and ${r_{\alpha}(s)=s^{\alpha-1}/\Gamma(\alpha)}$, here ${\Gamma(\alpha)}$ stands for Gamma function. In this post we will prove (1). Before, we need some properties of the Laplace transform. Given a “well” real-valued function ${u_j(\cdot,x)}$ on ${[0,\infty]}$, we define the Laplace transform as

$\displaystyle \mathcal{L}(u_j(\cdot,x))(s)=\int_0^{\infty}e^{-st}u_j(t,x)dt. \ \ \ \ \ (3)$

Given ${\lambda\in (0,\infty)}$, let  ${\partial_tu, u,v:[0,\lambda]\times\mathbb{R}^{n}\rightarrow\mathbb{R}^n}$ be certain  ${\mathbb{R}^n}$-valued functions for each ${t\in(0,\lambda)}$ fixed, then

$\displaystyle \mathcal{L}(\partial_tu)(s)=-u(0,x)+s\mathcal{L}(u)(s) \ \ \ \ \ (4)$

and

$\displaystyle \mathcal{L}(u\ast^{t}v)(s)=\mathcal{L}(u)(s)\mathcal{L}(v)(s) \ \ \ \ \ (5)$

where ${\ast^{t}}$ stands for convolution operator on variable ${t}$, that is, ${u\ast^{t}v(t)=\int_0^t u(t-s,x)v(s,x)ds}$. Hence, applying the Laplace transform in (2), we obtain

$\displaystyle s\mathcal{L}(u)(s)-\varphi(x)=\mathcal{L}(r_{\alpha-1})(s)\mathcal{L}(\Delta_{x} u)(s). \ \ \ \ \ (6)$

In view of

$\displaystyle \begin{array}{rcl} \mathcal{L}(t^{d})(s)=\int_0^{\infty}e^{-ts}t^{d}dt=\frac{\Gamma(d+1)}{s^{d+1}}, \;\; (d>0) \end{array}$

and

$\displaystyle \begin{array}{rcl} \mathcal{L}(\frac{\partial^2}{\partial x_i^2}u)(s)=\frac{\partial^2}{\partial x_i^2}\mathcal{L}(u)(s) \end{array}$

we have that the equation (6) can be written as

$\displaystyle s\mathcal{L}(u)(s)-\varphi(x)=s^{1-\alpha}\Delta_{x}\mathcal{L}(u)(s). \ \ \ \ \ (7)$

For ${j=1,\cdots n}$, let ${u_j\in \mathcal{S}(\mathbb{R}^{n})}$ (Schwartz space) and let ${\widehat{u_j}}$ be the Fourier transform of ${u_j}$ given by

$\displaystyle \widehat{u_j}(t,\xi)=\int_{\mathbb{R}^{n}}e^{-ix\cdot \xi}u_j(t,x)dx. \ \ \ \ \ (8)$

If ${u_j\in C^{\infty}(\mathbb{R}^{n})}$ with compact support, easily seems that

$\displaystyle \widehat{\frac{\partial^{2} u_j}{\partial x_i^{2}}}(t,\xi)=-\xi_j^{2}\,\widehat{u_j}(t,\xi)\Rightarrow \widehat{\Delta_{x} u}(t,\xi)=-\vert \xi\vert^2\,\widehat{u}(t,\xi). \ \ \ \ \ (9)$

As ${\widehat{\mathcal{L}(u)(s)}(\xi)=\mathcal{L}(\widehat{u}(\cdot,\xi))(s)}$ it follows from (7) and (9) that

$\displaystyle s\mathcal{L}(\widehat{u}(\cdot,\xi))(s)=\widehat{\varphi}(\xi)-s^{1-\alpha}\vert \xi\vert^2 \mathcal{L}(\widehat{u}(\cdot,\xi))(s)\nonumber \ \ \ \ \ (10)$

which yields

$\displaystyle \mathcal{L}(\widehat{u}(\cdot,\xi))(s)=\frac{\widehat{\varphi}(\xi)}{s+s^{1-\alpha}\vert\xi\vert^2}=\frac{s^{\alpha-1}}{s^{\alpha}+\vert\xi\vert^2} \widehat{\varphi}(\xi). \ \ \ \ \ (11)$

This motivates to define Mittag-Leffler function as a complex integral on certain curve. Indeed, firstly notice that the complex valued function ${f(z)=\frac{e^zz^{\alpha-1}}{z^{\alpha}+\vert\xi\vert^2}}$ has singularities in

$\displaystyle a_{\alpha}(\xi)=|\xi|^{\frac{2}{\alpha}}e^{\frac{i\pi}{\alpha}} ,\;\;\;b_{\alpha}(\xi)=|\xi|^{\frac{2}{\alpha}}e^{-\frac{i\pi}{\alpha}},\text{ for }\xi\in\mathbb{R}^{n}. \ \ \ \ \ (12)$

Let ${\gamma}$ be the standard Hankel’s curve in ${\mathbb{C}}$, positive oriented, such that ${a_{\alpha}(\xi)\in Int(\gamma)}$ and ${b_{\alpha}(\xi)\in Int(\gamma)}$, that is, let ${\gamma=r_1+r_2+C_r}$ be a parametrized curve given by ${r_1(t)=te^{i\theta}}$, ${r_2(t)=te^{-i\theta}}$ for ${t\in (r,\infty)}$ and ${C_r(t)=r e^{it}}$ for ${t\in (-\theta,\theta)}$. As we want to chose ${\gamma}$ such that ${a_{\alpha}(\xi)\in Int(\gamma)}$ and ${b_{\alpha}(\xi)\in Int(\gamma)}$, we shall suppose that ${r^{\alpha}>\vert \xi\vert^2>\epsilon^{\alpha}>0}$ and one defines Mittag-Leffler function as

$\displaystyle \begin{array}{rcl} \mathbb{E}_{\alpha,\beta}(-\vert\xi\vert^2)=\frac{1}{2\pi i}\int_{\gamma}\frac{e^zz^{\alpha-\beta}}{z^{\alpha}+\vert\xi\vert^2}dz,\; (\alpha>0,\beta>0). \end{array}$

Using residue theorem, a characterization very important of this definition was obtained in [Fujita] (see also [Hirata-Miao][Fujita2]).

Proposition 1 If ${1<\alpha<2}$ and ${\beta=1}$, we have

$\displaystyle \begin{array}{rcl} L^{1}(\mathbb{R}^{n})\ni\mathbb{E}_{\alpha}(-|\xi|^{2})=\frac{1}{\alpha}(\exp(a_{\alpha}(\xi))+\exp(b_{\alpha}(\xi)))+l_{\alpha}(\xi) \end{array}$

where

$\displaystyle l_{\alpha}(\xi)= \begin{cases} \frac{\sin(\alpha\pi)}{\pi}\int_{0}^{\infty}\frac{|\xi|^{2}s^{\alpha-1}e^{-s} }{s^{2\alpha}+2|\xi|^{2}s^{\alpha}\cos(\alpha\pi)+|\xi|^{4}}ds & \text{ if }\xi\neq0\\ 1-\frac{2}{\alpha}, & \text{ if }\xi=0. \end{cases} \ \ \ \ \ (13)$

Some corollaries can be obtained by Lemma above. Indeed, taking ${t=\vert\xi\vert^{\frac{2}{\alpha}}s^{\frac{1}{\alpha}}}$ one has

$\displaystyle \begin{array}{rcl} \vert \mathbb{E}_{\alpha}(-|\xi|^{2})\vert&\leq& \frac{2}{\alpha}+\vert l_{\alpha}(\xi)\vert\\ &\leq&\frac{2}{\alpha}+\frac{\sin(\alpha\pi)}{\pi}\int_{0}^{\infty}\frac{e^{-\vert\xi\vert^{\frac{2}{\alpha}}s^{\frac{1}{\alpha}}}}{s^{2}+2s\cos(\alpha\pi)+1}ds\\ &\leq&\frac{2}{\alpha}+\frac{\sin(\alpha\pi)}{\pi}\int_{0}^{\infty}\frac{1}{s^{2}+2s\cos(\alpha\pi)+1}ds\\ &=&\frac{2}{\alpha} +(1-\frac{2}{\alpha})=1, \end{array}$

more general (see de Almeida, Ferrreira, L.F.C).

Proposition 2 Let ${1\leq\alpha<2}$ and ${0\leq\delta<2.}$ There is ${C>0}$ such that

$\displaystyle \left\vert \frac{\partial^{k}}{\partial\xi^{k}}\left[ \left\vert \xi\right\vert ^{\delta}\mathbb{E}_{\alpha}(-|\xi|^{2})\right] \right\vert \leq C\left\vert \xi\right\vert ^{-\left\vert k\right\vert },\text{ } \ \ \ \ \ (14)$

for all ${k\in(\mathbb{N}\cup\{0\})^{n}}$ with ${\left\vert k\right\vert \leq\lbrack n/2]+1}$ and for all ${\xi\neq0.}$

Using an exercise,

$\displaystyle \int_{0}^{\infty}e^{-t}\mathbb{E}_{\alpha}(at^{\alpha})dt=\frac{1}{1-a},\;\; (r^{\alpha}>\vert a\vert>0)\text{ and } (1< \alpha< 2),\nonumber \ \ \ \ \ (15)$

we have

$\displaystyle \mathcal{L}(\mathbb{E}_{\alpha}(-t^{\alpha}\vert\xi\vert^2))(s)=\frac{s^{\alpha-1}}{s^{\alpha}+\vert\xi\vert^2}. \ \ \ \ \ (16)$

Taking in (11) the inverse Laplace transform and using (16), we obtain ${\widehat{u}(t,\xi)=\mathbb{E}_{\alpha}(-t^{\alpha}\vert\xi\vert^2)\widehat{\varphi}(\xi).}$

## Mikhlin-Hormander

### Featured

1. Mikhlin-Hormander type symbols

Let ${X,Y}$ be vector-spaces of measurable functions from ${\mathbb{R}^{n}}$ to itself and let ${T}$ be a bounded linear operator from ${X}$ to ${Y}$. Recall that ${T}$ is called translation invariant if ${T(\tau_{y}f)=\tau_{y}(T(f))}$ for all ${y\in\mathbb{R}^{n}}$ and ${f\in X}$. Let ${X=L^p}$ and ${Y=L^q}$ with ${1\leq q\leq p<\infty}$, we found that each such operator ${T}$ is determined by a certain tempered distribution ${K}$ such that ${Tf=K\ast f}$ for every ${f\in\mathcal{S}}$ (Schwartz space). So taking Fourier transform ${\mathcal{F}}$ into ${Tf}$ we have ${\mathcal{F}(Tf)=\mathcal{F}(K)\mathcal{F}(f)}$. This motivate us to define a Fourier multiplier as a map ${T_{\sigma}:\mathcal{S}(\mathbb{R}^n)\rightarrow\mathcal{S}'(\mathbb{R}^n)}$ given by

$\displaystyle \begin{array}{rcl} \widehat{T_{\sigma}f}(\xi)=\sigma(\xi) \widehat{f}(\xi), \end{array}$

where ${\sigma}$ is a tempered distribution ${\mathcal{S}'(\mathbb{R}^n)}$ and ${\,\widehat{}\,}$ denotes the Fourier transform ${\mathcal{F}}$. We refer to ${\sigma}$ as symbol of ${T_{\sigma}}$, sometimes one writes ${T_{\sigma}}$ as ${\sigma(D)}$ to relate it with more general operators ${\sigma(D,X)}$ so-called pseudo-differential operators. No standard example of such symbols is, for ${\delta>0}$,

$\displaystyle \sigma_{\delta}(\xi)=(1-\vert\xi\vert^2)^{\delta}\text{ if }\vert \xi\vert\leq 1\text{ and }\;\sigma_{\delta}(\xi) =0 \text{ otherwise}. \ \ \ \ \ (1)$

In the limit case, ${\delta=0}$, the above symbol can be written as ${\mathcal{X}_{\mathbb{D}}}$, where ${\mathcal{X}_{\mathbb{D}}}$ denotes the characteristic function of unit disk ${\mathbb{D}}$. It’s well-known that the condition ${n\geq2}$ and ${2n/(n+1) is necessary for ${T_{\sigma_{0}}}$ be a Fourier multiplier on ${L^p(\mathbb{R}^{n})}$ (see e.g., [1]). However, Fefferman (see [2],[3]) gave an intricate proof which show us that this condition is not sufficient, that is, he showed that the operator ${T_{\sigma_{0}}}$ does not extend to a bounded operator on ${L^p(\mathbb{R}^{n})}$ for any ${p\neq 2}$ and ${n\geq2}$. This result give us a negative answer to the famous disk conjecture which states that ${T_{\sigma_0}}$ is bounded on ${L^p(\mathbb{R}^{2})}$ for ${4/3\leq p\leq 4}$. In this post we will work with symbols more regular than (1) such as Minklin symbols ${\Sigma_{1}^{0}(\mathbb{R}^{n})=\{\sigma\in C^{k}(\mathbb{R}^n\backslash\{0\}); \vert D^{\gamma}\sigma(x)\vert \leq C \vert x\vert ^{-\vert\gamma\vert}, \vert\gamma\vert\leq k\}}$.

In a few months ago, based on Littlewood-Paley theorem, we gave a proof that the operator ${T_{\sigma}}$ is a Fourier multiplier from ${L^{p}(\mathbb{R}^{n})}$ to itself (see Theorem 7) provided that ${1 and ${\sigma}$ satisfies

$\displaystyle \sup_{j\in\mathbb{Z}}\Vert \widehat{\psi}_{j}\sigma\Vert_{L^2_{s}(\mathbb{R}^{n})}\leq L \ \ \ \ \ (2)$

for ${s>n/2}$ and ${n\geq1}$. In this post will be showed that if ${\sigma\in \Sigma_{1}^0}$, then its satisfies the inequality (2). Hence, by Theorem 7 one has the following classical Mikhlin-Hormander theorem.

Theorem 1 (Mikhlin-Hormander theorem) Let ${k>n/2}$ and ${\sigma\in C^{k}(\mathbb{R}^{n})}$ away from the origin. If for ${\vert\gamma\vert\leq k}$ we have

$\displaystyle \sup_{r>0}r^{\vert \gamma\vert}\left(\frac{1}{r^n}\int_{\frac{r}{2}<\vert\xi\vert<2r}\vert (D^{\gamma}_{\xi}\sigma)(\xi)\vert^{2}d\xi\right)^{\frac{1}{2}}\leq L \ \ \ \ \ (3)$

then ${T_{\sigma}}$ is a Fourier multiplier on ${L^p}$, ${1. In particular, ${T_{\sigma}}$ is a Fourier multiplier on ${L^p}$ if ${\sigma\in\Sigma_1^0(\mathbb{R}^n)}$, that is,

$\displaystyle \vert D^{\gamma}\sigma(\xi)\vert \leq C \vert \xi\vert ^{-\vert\gamma\vert}. \ \ \ \ \ (4)$

Let us recall some important definitions. Let ${1\leq p\leq \infty}$ and ${k\in\mathbb{Z}_{+}}$, a function ${f}$ lies in Sobolev spaces ${L^{p}_k(\mathbb{R}^{n})}$ if for every ${\gamma\in (\mathbb{N}\cup\{0\})^n}$ with ${\vert \gamma\vert\leq k}$ there exists ${g_{\gamma}\in L^{p}(\mathbb{R}^{n}) }$ such that

$\displaystyle \int_{\mathbb{R}^{n}}f(x)D^{\gamma}\varphi(x)dx= (-1)^{\vert \gamma\vert}\int_{\mathbb{R}^{n}}g_{\gamma}(x)\varphi(x)dx, \;\;\; \forall\varphi\in C^{\infty}_{0}(\mathbb{R}^{n}). \ \ \ \ \ (5)$

Here, we use the standard notations

$\displaystyle \begin{array}{rcl} \vert \gamma\vert=\sum_{i=1}^{n}\gamma_i \text{ and } D^{\gamma}\varphi=\frac{\partial^{\vert\gamma\vert} \varphi}{\partial^{\gamma_1} _{x_1}\partial^{\gamma_2} _{x_2}\cdots \partial^{\gamma_n} _{x_n}} \end{array}$

and we say that ${g_{\gamma}}$ is the derivative of ${f}$ in distribution sense (more precisely in ${\mathcal{D}'(\mathbb{R}^{n})}$) and we write ${D^{\gamma}f=g_{\gamma}}$ in ${\mathcal{D}'(\mathbb{R}^{n})}$ to mean (5). The space ${L^p_k}$ equipped with the norm

$\displaystyle \begin{array}{rcl} \vert f\vert_{L^p_k}=\sum_{\vert\gamma\vert\leq k}\vert D^{\gamma}f\vert_{L^p} \end{array}$

is a Banach space. Also, notice that Sobolev spaces ${L^{2}_k(\mathbb{R}^{n})}$ coincide with inhomogeneous fractional Sobolev spaces ${L^{2}_a(\mathbb{R}^{n})}$ because of the norm equivalence

$\displaystyle \begin{array}{rcl} \vert f\vert_{L^2_k}^2&\approx&\sum_{\vert\gamma\vert\leq k}\vert D^{\gamma}f\vert_{L^2}^2=\sum_{\vert\gamma\vert\leq k}\vert \xi^{\gamma}\widehat{f}\vert_{L^2}^2\\ &=&\int_{\mathbb{R}^{n}} \sum_{\vert\gamma\vert\leq k}\vert\xi^{2\gamma}\vert \vert\widehat{f}(\xi)\vert^2d\xi\\ &\approx& \int_{\mathbb{R}^{n}} (1+\vert\xi\vert^2)^{k}\vert\widehat{f}(\xi)\vert^2d\xi= \Vert f\Vert _{L^2_k}^{2}. \end{array}$

It follows that

$\displaystyle \begin{array}{rcl} \Vert \widehat{\psi}_{j}\sigma\Vert_{L^2_k}=\Vert \sigma(2^{j}\cdot)\widehat{\psi}\Vert_{L^2_k}=\sum_{\vert\gamma\vert \leq k}\vert D^{\gamma}(\sigma(2^{j}\cdot)\widehat{\psi})\vert_{L^2}. \end{array}$

Using Leibniz’s formula we written the term ${D^{\gamma}}$ as

$\displaystyle \begin{array}{rcl} D^{\gamma}(\sigma(2^{j}\cdot)\widehat{\psi})=\sum_{\vert \nu\vert\leq\vert \gamma\vert}\binom{\nu}{\gamma}(D^{\nu}\sigma(2^{j}\cdot))(D^{\gamma-\nu}\widehat{\psi}). \end{array}$

By observing that ${\vert D^{\gamma-\nu}\widehat{\psi}\vert\leq C}$ on ${supp(\widehat{\psi})\subset \{\xi\,:\, 1/2\leq \vert\xi\vert\leq2\}}$ and zero otherwise, we get

$\displaystyle \Vert \widehat{\psi}_{j}\sigma\Vert_{L^2_k}\leq C\sum_{\vert\gamma\vert \leq k}\sum_{\vert \nu\vert\leq\vert \gamma\vert}C_{\gamma,\nu}\vert D^{\nu}\sigma(2^{j}\cdot)\vert_{L^2(\{\xi\,:\,\frac{1}{2}< \vert\xi\vert<2\})}. \ \ \ \ \ (6)$

Now making the change of variable ${\xi\mapsto r\xi}$ one has ${D^{\nu}_{\xi}\sigma(r\cdot) =r^{\vert\nu\vert}(D_{\xi}^{\nu}\sigma)(r\xi)}$. Hence, by (3) it follows that

$\displaystyle \sup_{r>0}\left(\int_{\frac{1}{2}<\vert\xi\vert<2}\vert D^{\nu}_{\xi}\sigma(r\cdot)\vert^{2}d\xi\right)^{\frac{1}{2}}\leq L. \ \ \ \ \ (7)$

Let ${r=2^{j}}$. Therefore, inserting (7) into (6) easily gets

$\displaystyle \sup_{j}\Vert \widehat{\psi}_{j}\sigma\Vert_{L^2_k}\leq C\sum_{\vert\gamma\vert \leq k}\sum_{\vert \nu\vert\leq\vert \gamma\vert}C_{\gamma,\nu} L=C_{k}L \ \ \ \ \ (8)$

and Theorem 1 is a consequence of the Theorem 7 as we desired. Notice that if ${\vert D_{\xi}^{\gamma}\sigma (\xi)\vert\leq L\vert\xi\vert^{-\vert\gamma\vert}}$,

$\displaystyle \begin{array}{rcl} \vert D^{\nu}_{\xi}\sigma(2^j\cdot)\vert = 2^{j\vert\nu\vert} \vert (D^{\nu}_{\sigma}\sigma )(2^j\xi)\vert \leq L\vert\xi\vert^{-\vert\nu\vert}. \end{array}$

Hence ${\vert D^{\nu}\sigma(2^{j}\cdot)\vert_{L^2(\{\xi\,:\,\frac{1}{2}< \vert\xi\vert<2\})}\leq C}$ which implies (8).