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Research article Special Issues

Gevrey regularity for the generalized Kadomtsev-Petviashvili I (gKP-I) equation

  • The task of our work is to consider the initial value problem based on the model of the generalized Kadomtsev-Petviashvili I equation and prove the local well-posedness in an anisotropic Gevrey spaces and then global well-posedness which improves the recent results on the well-posedness of this model in anisotropic Sobolev spaces [17]. Also, wide information about the regularity of the solution in the time variable is provided.

    Citation: Aissa Boukarou, Kaddour Guerbati, Khaled Zennir, Mohammad Alnegga. Gevrey regularity for the generalized Kadomtsev-Petviashvili I (gKP-I) equation[J]. AIMS Mathematics, 2021, 6(9): 10037-10054. doi: 10.3934/math.2021583

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  • The task of our work is to consider the initial value problem based on the model of the generalized Kadomtsev-Petviashvili I equation and prove the local well-posedness in an anisotropic Gevrey spaces and then global well-posedness which improves the recent results on the well-posedness of this model in anisotropic Sobolev spaces [17]. Also, wide information about the regularity of the solution in the time variable is provided.



    The study of nonlinear wave processes in real media with dispersion, despite the significant progress in this area in recent years, for example, [1,2,3] and numerous references in these works are still relevant. This, in particular, concerns the dynamics of oscillations in cases where high-energy particle fluxes occur in the medium, which significantly change such parameters of propagating wave structures, such as their phase velocity, amplitude and characteristic length. In recent and earlier years, a fairly large number of works have been devoted to studies of this kind of relativistic effects (see [12,13,14]).

    Recently, the great interest on the KP equation has led to the construction and the study of many extensions to the KP equation. These new extended models propelled greatly the research that directly resulted in many promising findings and gave an insight into some novel physical features of scientific and engineering applications. Moreover, lump solutions, and interaction solutions between lump waves and solitons, have attracted a great amount of attentions aiming to make more progress in solitary waves theory. Lump solutions, have been widely studied by researchers for their significant features in physics and many other nonlinear fields[18,19,20].

    Let u=u(x,y,t),(x,y,t)R3 and α4. We consider the initial value problem for the generalized Kadomtsev-Petviashvili I equation,

    {tu+|Dx|αxu+1x2yu+uxu=0u(x,y,0)=f(x,y). (1.1)

    with

    Dαxu(x,y,t)=1(2π)32R3|ξ|αFu(ξ,μ,τ)eixξ+iyμ+itτdξdμdτ

    This equation belongs to the class of Kadomtsev-Petviashvili equations, which are models for the propagation of long dispersive nonlinear waves which are essentially unidirectional and have weak transverse effects. Due to the asymmetric nature of the equation with respect to the spatial derivatives, it is natural to consider the Cauchy problem for (1.1) with initial data in the anisotropic Sobolev spaces Hs1,s2(R2), defined by the norm

    uHs1,s2(R2)=(ξ2s1η2s2|ˆu(ξ,η)|2dξdη)1/2.

    Many authors have investigated the Cauchy problem for Kadomtsev-Petviashvili equations as in, for instance [4,8,16]. Yan et al. [17] established the local well-posedness of the Cauchy problem for the Kadomtsev-Petviashvili I equation in anisotropic Sobolev spaces Hs1,s2(R) with s1>α14, s20 with α4 and globally well-posed in Hs1,0(R) with s1>(α1)(3α4)4(5α+3) if 4α5 also proved that the Cauchy problem is globally well-posed in Hs1,0(R) with s1>α(3α4)4(5α+4) if α>5. The authors in [8] proposed the problem

    {tu5xu+1x2yu+uxu=0,u(x,y,0)=u0(x,y), (1.2)

    and proved that it is globally well-posed for given data in an anisotropic Gevrey space Gσ1,σ2(R2),σ1,σ20, with respect to the norm

    fGσ1,σ2(R2)=(R2e2σ1|ξ|e2σ2|η||ˆf(ξ,η)|2dξdη)1/2.

    With initial data in anisotropic Gevrey space

    Gσ1,σ2,κs1,s2(R2)=Gσ1,σ2,κs1,s2,σ1,σ20,s1,s2R,

    and κ1, we will consider the problem (1.1). The spaces Gσ1,σ2,κs1,s2 can be defined as the completion of the Schwartz functions with respect to the norm

    fGσ1,σ2,κs1,s2(R2)=(R2e2σ1|ξ|1κe2σ2|η|1κμ2(s1,s2)|ˆf(ξ,η)|2dξdη)1/2,

    where

    μ(s1,s2)=ξs1ηs2.

    In addition to the holomorphic extension property, Gevrey spaces satisfy the embeddings Gσ1,σ2s1Gσ1,σ2s1 for s1,s1R and σi<σi where Gσ1,σ2,1s1,0=Gσ1,σ2s1, which follow from the corresponding estimates

    fGσ1,σ2s1fGσ1,σ2s1.

    The main aim to consider initial data in these spaces is because of the Paley-Wiener Theorem.

    Proposition 1.1. Let σ1>0, sR. Then fGσ1x(R) if and only if it is the restriction to the to the real line of a function F which is holomorphic in the strip {x+iyC: |y|<σ}, and satisfies

    sup

    Notation

    We will also need the full space time Fourier transform denoted by

    \hat{f}(\xi, \eta, \tau) = \int_{\mathbb{R}^{3}} f(x, y, t) e^{-i (x \xi + y \eta + t \tau)}\ dx dy dt.

    In both cases, we will denote the corresponding inverse transform of a function

    f = f(\xi, \eta) \ or \ f = f(\xi, \eta, \tau) \ by \ \mathfrak{F}^{-1}(f).

    To simplify the notation, we introduce some operators. We first introduce the operator A_{\kappa}^{\sigma_1, \sigma_2} , which we define as

    \begin{equation} A_{\kappa}^{\sigma_1, \sigma_2}f = \mathfrak{F}^{-1}\left( e^{\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{\sigma_2 |\eta|^{\frac{1}{\kappa}}} \hat{f} \right). \end{equation} (1.3)

    Then, we may then define another useful operator

    \begin{equation} N^{\sigma_1, \sigma_2}_{\kappa}(f) = \partial_{x}\left[(A_{\kappa}^{\sigma_1, \sigma_2}f)^2 - A_{\kappa}^{\sigma_1, \sigma_2}(f^2)\right]. \end{equation} (1.4)

    For x \in \mathbb{R}^{n} , we denote \langle x \rangle = (1 + |x|^{2})^{1/2} . Finally, we write a \lesssim b if there exists a constant C > 0 such that a \leq Cb , and a \sim b if a \lesssim b \lesssim a . If the constant C depends on some quantity q , we denote this by a \lesssim_{q} b .

    Function spaces

    Since our proofs rely heavily on the theory developed by Yan et al., let us state the function spaces they used explicitly, so that we can state their useful properties which we will exploit in our modifications of their spaces. The main function spaces they used are the so-called anisotropic Bourgain spaces, adapted to the generalized Kadomtsev-Petviashvili I, whose norm is given by

    \| u \|_{X_{s_{1}, s_{2}, b}} = \left( \int_{\mathbb{R}^{3}} \theta^{2}(s_1, s_2, b) |\hat{u}(\xi, \eta, \tau)|^{2} d\xi d\eta d\tau \right) ^{\frac{1}{2}},

    where

    \theta(s_1, s_2, b) = \langle \xi \rangle^{s_1} \langle \eta \rangle^{s_2} \langle \tau + m(\xi, \eta) \rangle^{b},

    with m(\xi, \eta) = \xi|\xi|^{\alpha}+\frac{\eta^{2}}{\xi} .

    Furthermore, we will also need a hybrid of the anlytic Gevrey and anisotropic Bourgain spaces, designated X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}(\mathbb{R}^{3}) and defined by the standard

    \| u \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} = \left( \int_{\mathbb{R}^{3}}e^{2\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \theta^{2}(s_1, s_2, b) |\hat{u}(\xi, \eta, \tau)|^{2} d\xi d\eta d\tau \right) ^{\frac{1}{2}},

    It is well-known that these spaces satisfy the embedding

    X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa} \hookrightarrow C \left(\mathbb{R}; G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa} (\mathbb{R}^{2})\right).

    Thus, solutions constructed in X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa} belong to the natural solution space.

    When considering local solutions, it is useful to consider localized versions of these spaces. For a time interval I and a Banach space \mathcal{Y} , we define the localized space \mathcal{Y}(I) by the norm

    \| u \|_{\mathcal{Y}(I)} = \inf \{ \| v \|_{\mathcal{Y}}:\ v = u \text{ on }~~ I \}.

    The first result related to the short-term persistence of analyticity of solutions is given in the next Theorem.

    Theorem 2.1. Let s_{1} > -\frac{\alpha-1}{4}, s_{2} \geq 0 , \alpha\geq 4 , \sigma_1 \geq 0 , \sigma_2 \geq 0 and \kappa\geq1 . Then for all initial data f \in G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa} and \vert \xi\vert^{-1}\widehat{f}(\xi, \mu)\in L^{2}(\mathbb{R}^{2}) , there exists \delta = \delta(\parallel f\parallel_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}) > 0 and a unique solution u of (1.1) on the time interval [0, \delta] such that

    u \in C\left([0, \delta]; G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa} (\mathbb{R}^{2})\right).

    Moreover the solution depends continuously on the data f . In particular, the time of existence can be chosen to satisfy

    \delta = \frac{c_{0}}{(1 + \| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}})^{\gamma}},

    for some constants c_{0} > 0 and \gamma > 1 . Moreover, the solution u satisfies

    \sup\limits_{t \in [0, \delta]}\| u(t) \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}} \leq 4 \| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}.

    The second main result concerns the evolution of the radius of analyticity for the x -direction is given in the next Theorem. Here

    X_{s_{1}, 0, b}^{\sigma_1, 0, 1} = X_{s_{1}, b}^{\sigma_1, 0}, s_{2}, \sigma_2 = 0 \ and \ \kappa = 1.

    Theorem 2.2. Let \sigma_1 > 0 , s_{1} > -\frac{\alpha-1}{4}, \alpha = 4, 6, 8, ... and assume that f \in G_{s_{1}}^{\sigma_1, 0} , \vert \xi\vert^{-1}\widehat{f}(\xi, \mu)\in L^{2}(\mathbb{R}^{2}) . Then the solution u given by Theorem 2.1 extends globally in time, and for any T > 0 , we have

    u \in C\left([0, T], G_{s_{1}}^{\sigma_{1}(T), 0}(\mathbb{R}^{2}) \right) \quad \mathit{{with}} \quad \sigma_{1}(T) = \min\left\lbrace \sigma_1, C T^{-\rho}\right\rbrace,

    with \rho = \frac{4}{\alpha-1}+\varepsilon for \varepsilon > 0 when \alpha = 4 and \rho = 1 when \alpha = 6, 8, 10, ... and the constant C is a positive.

    The method used here for proving lower bounds on the radius of analyticity was introduced in [15] in the study of the non-periodic KdV equation. It was applied to the the higher order nonlinear dispersive equation in [9] and the system of mKdV equation in [10].

    Our last aim is to show the regularity of the solution in the time. A non-periodic function \phi(x) is the Gevrey class of order \kappa i.e, \phi(x)\in G^{\kappa} , if there exists a constant C > 0 such that

    \begin{eqnarray} | \partial_{x}^{k}\phi(x)| \leq C^{k+1}(k!)^{\kappa} \ \ \ k = 0, 1, 2, \dots. \end{eqnarray} (2.1)

    Here we will show that for x, y\in \mathbb{R} , for every t\in [0, \delta] and j, l, n \in \lbrace 0, 1, 2, \dots \rbrace , there exist C > 0 such that,

    \begin{eqnarray} | \partial_{t}^{j} \partial_{x}^{l}\partial_{y}^{n}u(x, y, t)| \leq C^{j+l+n+1}(j!)^{(\alpha+1)\kappa}(l!)^{\kappa}(n!)^{\kappa}. \end{eqnarray} (2.2)

    i.e, u(\cdot, \cdot, t)\in G^{\sigma}(\mathbb{R})\times G^{\sigma}(\mathbb{R}) in x, y and u(x, y, \cdot)\in G^{(\alpha+1)\kappa}([0, \delta]) in time variable.

    Theorem 2.3. Let s_{1} > -\frac{\alpha-1}{4}, s_{2} \geq 0 , \alpha\geq 4 , \sigma_1 \geq 0 , \sigma_2 \geq 0 and \kappa\geq1 .

    If f \in G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa} then the solution

    u \in C\left([0, \delta], G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa} \right),

    given by Theorem 2.1, belongs to the Gevrey class G^{(\alpha+1)\kappa} in time variable.

    Corollary 2.4. Let \sigma_1 > 0, s_{1} > -\frac{\alpha-1}{4}, \alpha = 4, 6, 8, .... If f \in G_{s_{1}}^{\sigma_1, 0} then the solution

    u \in C\left([0, T], G_{s_{1}}^{\sigma_{1}(T), 0}(\mathbb{R}^{2}) \right),

    given by Theorem 2.2, belongs to the Gevrey class G^{(\alpha+1)} in time variable.

    The rest of the paper is organized as follows: In section 3, we present all the auxiliary estimates that will be employed in the remaining sections. We prove Theorem 2.1 in subsection 4.1 using the standard contraction method and Theorem 2.2 in subsection 4.2. Finally, in section 5, we prove G^{(\alpha+1)} regularity in time.

    To begin with, let us consider the related linear problem

    \begin{align*} & \partial_{t} u + |D_{x}|^{\alpha}\partial_{x}u + \partial^{-1}_{x} \partial^{2}_{y} u = F, \\ & u(0) = f. \end{align*}

    By Duhamel's principle the solution can be written as

    \begin{equation} u(t) = S(t)f - \dfrac{1}{2} \int_{0}^{t} S(t-t') F(t') dt', \end{equation} (3.1)

    where

    \widehat{S(t)f} (\xi, \eta) = e^{i t m(\xi, \eta)} \widehat{f} (\xi, \eta).

    We localize it in t by using a cut-off function satisfying \psi\in C_{0}^{\infty}(\mathbb{R}) , with \psi = 1 in [-1, 1] and supp \psi \subset [-2, 2] .

    We consider the operator \Phi given by

    \begin{equation} \Phi(u) = \psi(t)S(t)f-\dfrac{\psi_{\delta}(t)}{2}\int_{0}^{t}S(t-t')\left(\partial_{x}u^{2}(t')\right)dt', \end{equation} (3.2)

    where \psi_{\delta}(t) = \psi(\frac{t}{\delta}) . To this operator, we apply the following estimates.

    Lemma 3.1. (Linear estimate) Let s_{1}, s_{2}\in \mathbb{R}, -\frac{1}{2} < b'\leq 0 \leq b \leq b'+1, \sigma_1 \geq 0, \sigma_2 \geq 0, \kappa\geq1 \ and \ \delta\in (0, 1). Then

    \begin{align} \|\psi(t)S(t)f\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\leq C\|f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}, \end{align} (3.3)
    \begin{align} \Bigg\|\psi_{\delta}(t)\int_{0}^{t}S(t-t')F(x, y, t')\mathrm{d}t' \Bigg\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\leq C\delta^{1-b+b'}\| F\|_{X_{s_{1}, s_{2}, b'}^{\sigma_1, \sigma_2, \kappa}}. \end{align} (3.4)

    Proof. The proofs of (3.3) and (3.4) for \sigma_1 = \sigma_2 = 0 can be found in Lemma 2.1 of [17]. These inequalities clearly remain valid for \sigma_1, \sigma_2 > 0 , as one merely has to replace f by A_{\kappa}^{\sigma_1, \sigma_2}f , F by A_{\kappa}^{\sigma_1, \sigma_2}F .

    The final preliminary fact we must state is the following bilinear estimate, which is Lemma 3.1 of [17].

    Lemma 3.2. (Bilinear estimate in Bourgain space.)

    Let s_{1}\geq-\frac{\alpha-1}{4}+4\alpha\epsilon, s_{2} \geq 0 , \alpha\geq 4 , b = \frac{1}{2}+\epsilon and b' = -\frac{1}{2}+2\epsilon . Then, we have

    \| \partial_{x} (u_{1}u_{2}) \|_{X^{s_1, s_2, b'}} \lesssim \| u_{1} \|_{X^{s_1, s_2, b}} \| u_{2} \|_{X^{s_1, s_2, b}}.

    To this result, we apply the following Lemma, which is a corollary of Lemma 3.2.

    Lemma 3.3. (Bilinear estimate in Gevrey-Bourgain space.)

    Let s_{1} > -\frac{\alpha-1}{4}+4\alpha\epsilon, s_{2} \geq 0, \alpha\geq 4, \sigma_1 \geq 0, \sigma_2 \geq 0, \kappa\geq1, b = \frac{1}{2}+\epsilon \ and \ b' = -\frac{1}{2}+2\epsilon. Then, we have

    \| \partial_{x} (u_{1}u_{2}) \|_{X_{s_{1}, s_{2}, b'}^{\sigma_1, \sigma_2, \kappa}} \lesssim \| u_{1} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \| u_{2} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}.

    Proof. It is not hard to see that

    \begin{align*} & e^{2 (\sigma_1 |\xi|^{\frac{1}{\kappa}} + \sigma_2 |\eta|^{\frac{1}{\kappa}})} \left| \widehat{u_{1}u_{2}}(\xi, \eta, \tau) \right|^{2} \\ & \quad = e^{2 (\sigma_1 |\xi|^{\frac{1}{\kappa}} + \sigma_2 |\eta|^{\frac{1}{\kappa}})} \left| \int \hat{u_{1}}(\xi - \xi_1, \eta - \eta_1, \tau - \tau_1) \hat{u_{2}}(\xi_1, \eta_1, \tau_1)\ d\xi_{1} d\eta_{1} d\tau_{1} \right|^{2} \\ & \quad \leq \left| \int e^{\sigma_1 |\xi - \xi_1|^{\frac{1}{\kappa}} + \sigma_2 |\eta - \eta_1|^{\frac{1}{\kappa}}}\hat{u_{1}}(\xi - \xi_1, \eta - \eta_1, \tau - \tau_1) e^{\sigma_1 |\xi_1|^{\frac{1}{\kappa}} + \sigma_2 |\eta_1|^{\frac{1}{\kappa}}} \hat{u_{2}}(\xi_1, \eta_1, \tau_1)\ d\xi_{1} d\eta_{1} d\tau_{1} \right|^{2} \\ & \quad = \left| \widehat{A_{\kappa}^{\sigma_1, \sigma_2}u A_{\kappa}^{\sigma_1, \sigma_2}v} \right|^{2}. \end{align*}

    By Lemma 3.2, we get

    \begin{align*} \| \partial_{x}(u_{1}u_{2}) \|_{X_{s_{1}, s_{2}, b'}^{\sigma_1, \sigma_2, \kappa}} & \leq \| \partial_{x}(A_{\kappa}^{\sigma_1, \sigma_2}u_{1} A_{\kappa}^{\sigma_1, \sigma_2}u_{2}) \|_{X^{s_{1}, s_{2}, b'}} \\ & \lesssim \| A_{\kappa}^{\sigma_1, \sigma_2}u_{1} \|_{X^{s_{1}, s_{2}, b}} \| A_{\kappa}^{\sigma_1, \sigma_2}v \|_{X^{s_{1}, s_{2}, b}} \\ & = \| u_{1} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \|u_{2} \|_{X_{s_{1}, s_{2}, b'}^{\sigma_1, \sigma_2, \kappa}}. \end{align*}

    The above Lemmas will be used without somtimes mention to prove Theorem 2.1.

    Lemma 4.1. Let s_{1} > -\frac{\alpha-1}{4}+4\alpha\epsilon, s_{2} \geq 0, \alpha\geq 4, \sigma_1 \geq 0, \sigma_2 \geq 0, \kappa\geq1, b = \frac{1}{2}+\epsilon, b' = -\frac{1}{2}+2\epsilon \ and \ 0 < \delta < 1. Then

    \| \Phi(u) \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \leq C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}} + C \delta^{\epsilon} \| u \|^{2}_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}},

    and

    \| \Phi(u_{1})-\Phi(u_{2}) \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \leq\dfrac{1}{2} \| u_{1}-u_{2} \|^{2}_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}.

    Proof. Combining Lemma 3.3 and Lemma 3.1 with the fixed point Theorem. We define

    \mathbb{B}(0, 2C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}) = \left\lbrace u : \| u\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\leq 2C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}\right\rbrace.

    Then, we have

    \begin{align*} \| \Phi(u) \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}&\leq\|\psi(t)S(t)f\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}+ \|\dfrac{1}{2}\psi_{\delta}(t)\int_{0}^{t}S(t-t')\partial_{x}u^{2}\mathrm{d}t' \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\\&\leq C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}+C\delta^{\epsilon}\| \partial_{x}u^{2}\|_{X_{s_{1}, s_{2}, b'}^{\sigma_1, \sigma_2, \kappa}} \\&\leq C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}} + C \delta^{\epsilon} \| u \|^{2}_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}. \end{align*}

    We choose \delta such that

    \begin{equation} \delta < \frac{1}{(C^{2} \| f \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}})^{\frac{1}{\epsilon}}}. \end{equation} (4.1)

    We have

    \begin{align*} \| \Phi(u) \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\leq 2C \| f \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}. \end{align*}

    Thus, \Phi(u) maps \mathbb{B}(0, 2C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}) into \mathbb{B}(0, 2C\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}) which is a contraction, since

    \begin{align*} \| \Phi(u_{1})-\Phi(u_{2}) \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} &\leq C \Bigg\|\dfrac{1}{2}\psi_{\delta}(t)\int_{0}^{t}S(t-t')(\partial_{x}u_{1}^{2}-\partial_{x}u_{1}^{2})\mathrm{d}t' \Bigg\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \\&\leq C\delta^{\epsilon}\| u_{1}-u_{2} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}\left[\| u_{1}\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}+\|u_{2} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \right] \\&\leq 4C^{2}\delta^{\epsilon}\| f \|_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}\| u_{1}-u_{2} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} \\&\leq\dfrac{1}{2} \| u_{1}-u_{2} \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}}. \end{align*}

    Here we choose \delta such that

    \begin{equation} \delta < \frac{1}{(8C^{2} \| f \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}})^{\frac{1}{\epsilon}}}. \end{equation} (4.2)

    We choose the time of existence where

    \delta = \frac{c_{0}}{(1 + \| f \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}})^{\frac{1}{\epsilon}}}.

    For appropriate choice of c_{0} , this will satisfy inequalities (4.1) and (4.2).

    From Lemma 4.1, we see that for initial data f(x, y)\in G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}(\mathbb{R}^{2}) if the lifespan \delta = c_{0}/(1 + \| f \|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}})^{\frac{1}{\epsilon}} then the map \Phi(u) is a contraction on a small ball centered at the origin in X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa} . Hence, the map \Phi(u) has a unique fixed point u in a neighborhood of 0 with respect to the norm \|\cdot\|_{X_{s_{1}, s_{2}, b}^{\sigma_1, \sigma_2, \kappa}} .

    The rest of the proof follows the standard argument.

    In this section, we prove Theorem 2.2. The first step is to obtain estimates on the growth of the norm of the solutions. For this end, we need to prove the following approximate conservation law.

    Theorem 4.2. Let \sigma_{1} > 0 and \delta be as in Theorem 2.1, there exist b\in (1/2, 1) and C > 0 , such that for any solution u\in X_{0, b}^{\sigma_1, 0}(I) to the Cauchy problem (1.1) on the time interval I \subset [0, \delta] , we have the estimate

    \begin{equation} \sup\limits_{ t\in[0, \delta]}\Vert u(t)\Vert^{2}_{G_{0}^{\sigma_1, 0}}\leq \Vert f\Vert^{2}_{G_{0}^{\sigma_1, 0}}+C\sigma_1^{\varrho}\Vert u\Vert^{3}_{X_{0, b}^{\sigma_1, 0}(I)}. \end{equation} (4.3)

    with \varrho\in [0, \frac{3}{4}) if \alpha = 4 , and \varrho = 1 if \alpha = 6, 8, 10, \dots .

    Before we may show the proof, let us first state some preliminary Lemmas. The first one is an immediate consequence of Lemma 12 in [15].

    Lemma 4.3. For \sigma > 0 , 0\leq\theta\leq1 and \xi, \xi_{1} \in \mathbb{R} , we have

    \begin{align*} e^{\sigma |\xi - \xi_1|} e^{\sigma |\xi_1|} - e^{\sigma |\xi|} \lesssim \sigma^{\theta} \frac{\langle \xi - \xi_1 \rangle \langle \xi_1 \rangle}{\langle \xi \rangle} e^{\sigma |\xi - \xi_1|} e^{\sigma |\xi_1|}. \end{align*}

    This will be used to prove the following key estimate.

    Lemma 4.4. Let N^{\sigma_1, 0}_{1}(u) be as in Eq (1.4) for \sigma_1 \geq 0 and \sigma_2 = 0 . Then for b as in Lemma 3.2, we have

    \| N^{\sigma_1, 0}_{1}(u) \|_{X_{0, b-1}} \leq C \sigma_{1}^{\varrho} \| u \|^{2}_{X_{0, b}^{\sigma_1, 0}},

    with \varrho\in [0, \frac{3}{4}) if \alpha = 4 and \varrho = 1 if \alpha = 6, 8, 10, ...

    Proof. We first observe that the inequality in Lemma 3.2, is equivalent to

    \begin{align*} & \left\| \xi \theta(s_1, s_2, b-1) \int \frac{\hat{f}(\xi - \xi_1, \eta - \eta_1, \tau - \tau_1)}{\langle \xi - \xi_1 \rangle^{s_1} \langle \eta - \eta_1 \rangle^{s_2} \langle \phi(\xi - \xi_1, \eta - \eta_1, \tau - \tau_1) \rangle^{b-1}} \right. \times \\ & \times \left. \frac{\hat{g}(\xi_1, \eta_1, \tau_1)}{\langle \xi_1 \rangle^{s_1} \langle \eta_1 \rangle^{s_2} \langle \phi(\xi_1, \eta_1, \tau_1) \rangle^{b-1}} \ d\xi_1 d\eta_1 d\tau_1 \right\|_{L^{2}_{\xi, \eta}} \lesssim \| f \|_{L^{2}_{x, y}} \| g \|_{L^{2}_{x, y}}, \end{align*}

    where we denote \phi(\tau, \xi, \eta) = \langle \tau + m(\xi, \eta)\rangle . With this, we observe that the left side of the inequality in Lemma 4.4 can be estimated by Lemma 4.3 as

    \begin{align*} \| N_{1}^{\sigma_1, 0}(u) \|_{X_{0, b-1}} & \lesssim \sigma \left\| \frac{\xi \langle \xi \rangle^{-1}}{\langle \phi(\tau, \xi, \eta)\rangle^{\beta}} \int \frac{e^{\sigma_1 |\xi - \xi_1|} \hat{u}(\xi - \xi_1, \eta - \eta_1, \tau - \tau_1)}{\langle \xi - \xi_1 \rangle^{-1}} \right. \times \\ & \qquad \qquad \times \left. \frac{e^{\sigma_1 |\xi_1|} \hat{u}(\xi_1, \eta_1, \tau_1)}{\langle \xi_1 \rangle^{-1}} \ d\xi_1 d\eta_1 \right\|_{L^{2}_{\xi, \eta}}. \end{align*}

    If we apply Lemma 3.2 with s_1 = -\varrho , s_2 = 0 , it will follow, from the comments above, that

    \| N_{1}^{\sigma_1, 0}(u) \|_{X_{0, b-1}} \lesssim \sigma_{1}^{\varrho}\| u \|_{X_{0, b}^{\sigma_1, 0}}^{2}.

    Proof of Theorem 4.2. Begin by applying the operator A_{1}^{\sigma_1, 0} to Eq (1.1). If we let U = A_{1}^{\sigma_1, 0} u , then Eq (1.1) becomes

    \begin{eqnarray} \partial_{t}U - \partial_{x}^{\alpha}U + \partial_{x}^{-1}\partial^{2}_{y} U + U\partial_{x}U = N^{\sigma_1, 0}_{1}(u), \end{eqnarray} (4.4)

    where \alpha = 4, 6, 8, .. and N^{\sigma_1, 0}_{1}(u) is defined in Lemma 4.4. Multiplying (4.4) by U and integrating with respect to the spatial variables, we obtain

    \int U\partial_{t} U - U \partial_{x}^{\alpha}U + U \partial^{-1}_{x}\partial^{2}_{y} U + U^2 \partial_{x}U\ dxdy = \int U N^{\sigma_1, 0}_{1}(u)\ dxdy.

    If we apply integration by parts, we may rewrite the left-hand side as

    \partial_{t} \int \frac{1}{2} U^{2}\ dxdy + \int \partial_{x}^{\frac{\alpha}{2}}U \partial_{x}^{\frac{\alpha}{2}+1}U dx dy - \int\partial_{y} U \partial_{x}^{-1} \partial_{y}U\ dxdy + \int U^2 \partial_{x}U\ dxdy = \int U N^{\sigma_1, 0}_{1}(u)\ dxdy,

    which can then be rewritten as

    By noticing that \partial_{x}^{j} U(x, t) \rightarrow 0 as |x| \rightarrow \infty (see [15]) we obtaining

    \partial_{t} \int U^{2}(x, y, t)\ dxdy = 2\int U(x, y, t) N^{\sigma_1, 0}_{1}(u)(x, y, t)\ dx dy.

    Integrating with respect to time yields

    \int U^{2}(x, y, t)\ dxdy = \int U^{2}(x, y, 0)\ dxdy + 2\int_{0}^{t} \int U(x, y, t') \partial_{x} N^{\sigma_1, 0}_{1}(u)(x, y, t')\ dx dy dt'.

    Applying Cauchy-Schwarz and the definition of U , we obtain

    \| u(t) \|_{G_{0}^{\sigma_1, 0}}^{2} \leq \| f \|_{G_{0}^{\sigma_1, 0}}^{2} + \| u \|_{X_{0, b}^{\sigma_1, 0}} \| N^{\sigma_1, 0}_{1}(u) \|_{X_{0, b-1}^{0, 0}(I)}.

    We now apply Lemma 4.4 and the fact that b = \frac{1}{2}+\epsilon , we can further estimate this by

    \begin{equation} \| u(t) \|_{G_{0}^{\sigma_1, 0}}^{2} \leq \| f \|_{G_{0}^{\sigma_1, 0}}^{2} + C\sigma_{1}^{\varrho} \| u \|_{X_{0, b}^{\sigma_1, 0}}^{3}, \end{equation} (4.5)

    as desired.

    Proof of Theorem 2.2. With the tools established in the previous subsection, we may begin the proof of Theorem 2.2. Let us first suppose that T^{*} is the supremum of the set of times T for which

    u \in C([0, T]; G_{x}^{\sigma_{1}, 0}).

    If T^{*} = \infty , there is nothing to prove, so let us assume that T^{*} < \infty . In this case, it suffices to prove that

    \begin{equation} u \in C\left([0, T], G_{x}^{\sigma_{1}(T), 0} \right), \end{equation} (4.6)

    for all T > T^{*} . To show that this is the case, we will use Theorem 2.1 and Theorem 4.2 to construct a solution which exists over subintervals of width \delta , using the parameter \sigma_{1} to control the growth of the norm of the solution. We first prove the case s = 0 and then we will generalize the case.

    The desired result will follow from the following proposition.

    Proposition 4.5. Let T > 0 , x = 0 , 0 < \sigma_{1}\leq \sigma_{0} and \delta > 0 be numbers such that n \delta \leq T < (n + 1) \delta . Then the solution u to the Cauchy problem (1.1) satisfies

    \begin{equation} \sup\limits_{t \in [0, n \delta]} \| u(t) \|_{G_{0}^{\sigma_{1}, 0}}^{2} \leq \| f \|_{G_{0}^{\sigma_{1}, 0}}^{2} + 2^3 C \sigma_{0}^{\varrho} n \| f \|_{G_{0}^{\sigma_{0}, 0}}^{3}, \end{equation} (4.7)

    and

    \begin{equation} \sup\limits_{t \in [0, n \delta]} \| u(t) \|_{G_{0}^{\sigma_{1}, 0}}^{2} \leq 4 \| u(t) \|_{G_{0}^{\sigma_{0}, 0}}^{2}, \end{equation} (4.8)

    if

    \sigma_{1} = C_{1}T^{-\frac{1}{\varrho}}, and~~ C_{1} = \left( \dfrac{c_{0}}{C2^{5}\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}}(1+2\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}})^{\frac{1}{\epsilon}}}\right)^{\frac{1}{\varrho}},

    for some constant C > 0 .

    Proof. For fixed T \geq T^{*} , we will prove, for sufficiently small \sigma_{1} > 0 , that

    \begin{equation} \sup\limits_{t\in[0, T]}\Vert u(0)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}\leq 4\Vert u(0)\Vert^{2}_{G_{0}^{\sigma_{0}, 0}}. \end{equation} (4.9)

    We will use the Theorem 2.1 and Theorem 4.2 with the time step

    \begin{equation} \delta = \frac{c_{0}}{(1+4\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}})^{\frac{1}{\epsilon}}}. \end{equation} (4.10)

    The smallness conditions on \sigma_{1} will be

    \begin{equation} \sigma_{1}\leq\sigma_{0}\ \ and \ \ \ \frac{2T}{\delta}C\sigma_{1}^{\varrho}4^{\frac{3}{2}}\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}}\leq 1, \end{equation} (4.11)

    where C > 0 is the constant in Theorem 4.2. Proceeding by induction, we will verify that

    \begin{equation} \sup\limits_{t\in[0, \delta]}\Vert u(t)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}\leq \Vert f\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+nC\sigma_{1}^{\varrho}2^{3}\Vert f\Vert^{3}_{G_{0}^{\sigma_{0}, 0}}, \end{equation} (4.12)
    \begin{equation} \sup\limits_{t\in[0, \delta]}\Vert u(t)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}\leq 4\Vert f\Vert^{2}_{G_{0}^{\sigma_{0}, 0}}, \end{equation} (4.13)

    for n\in \lbrace 1, \cdot\cdot\cdot, m+1\rbrace , where m\in \mathbb{N} is chosen, so that T \in [m\delta, (m+1)\delta) . This m does exist, since by Theorem 2.1 and the definition of T^{*} , we have

    \delta < \frac{c_{0}}{(1+\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}})^{\frac{1}{\epsilon}}} < T^{*}, \ \ hence \ \ \delta < T.

    We cover now, the interval [0, \delta] , and by Theorem 4.2, we have

    \begin{eqnarray} \sup\limits_{t\in[0, \delta]}\Vert u(t)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}\leq \Vert f\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+C\sigma_{1}^{\varrho}\Vert f\Vert^{3}_{G_{0}^{\sigma, 0}}\leq \Vert f\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+C\sigma_{1}^{\varrho}\Vert f\Vert^{3}_{G_{0}^{\sigma_{0}, 0}}, \end{eqnarray}

    where we used that

    \Vert f\Vert_{G_{0}^{\sigma_{1}, 0}}\leq \Vert f\Vert_{G_{0}^{\sigma_{0}, 0}},

    since \sigma_{1}\leq \sigma_{0} . This verifies (4.12) for n = 1 and now, (4.13) follows using again

    \Vert f\Vert_{G_{0}^{\sigma_{1}, 0}}\leq \Vert f\Vert_{G_{0}^{\sigma_{0}, 0}},

    as well as C\sigma_{1}^{\varrho}\Vert f\Vert_{G_{0}^{\sigma_{0}, 0}}\leq 1. Next, assuming that (4.12) and (4.13) hold for some n \in \lbrace 1, \cdot\cdot\cdot, m\rbrace , we will prove that they hold for n+1 . We estimate

    \begin{eqnarray} \begin{array}{ll} \sup\limits_{t\in[n\delta, (n+1)\delta]}\Vert u(t)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}&\leq \Vert u(n\delta)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+C\sigma_{1}^{\varrho}\Vert u(n\delta)\Vert^{3}_{G_{0}^{\sigma_{1}, 0}}\\ \\&\leq \Vert u(n\delta)\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+C\sigma_{1}^{\varrho}2^{3}\Vert f\Vert^{3}_{G_{0}^{\sigma_{0}, 0}}\nonumber\\\nonumber \\ &\leq \Vert f\Vert^{2}_{G_{0}^{\sigma_{1}, 0}}+nC\sigma_{1}^{\varrho}2^{3}\Vert f\Vert^{3}_{G_{0}^{\sigma_{0}, 0}}+C\sigma_{1}^{\varrho}2^{3}\Vert f\Vert^{3}_{G_{0}^{\sigma_{0}, 0}}, \nonumber \end{array} \end{eqnarray} (4.14)

    verifying (4.12) with n replaced by n+1 . To get (4.13) with n replaced by n+1 , it is then enough to have

    (n+1)C\sigma_{1}^{\varrho}2^{3}\Vert f\Vert_{G_{0}^{\sigma_{0}, 0}}\leq 1.

    But this holds by (4.11), since

    n+1 \leq m+1 \leq \frac{T}{\delta} + 1 < \frac{2T}{\delta}.

    Finally, the condition (4.11) is satisfied for \sigma_{1} \in (0, \sigma_{0}) such that

    \begin{eqnarray} \frac{2T}{\delta}C\sigma_{1}^{\varrho}2^{3}\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}} = 1. \end{eqnarray}

    Thus, \sigma_{1} = C_{1}T^{-\frac{1}{\varrho}} , where

    C_{1} = \left( \dfrac{c_{0}}{C2^{5}\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}}(1+2\parallel f\parallel_{G_{0}^{\sigma_{0}, 0}})^{\frac{1}{\epsilon}}}\right)^{\frac{1}{\varrho}}.

    For general s , we have

    u_{0}\in G_{s}^{\sigma_{0}, 0}\subset G_{0}^{\sigma_{0}/2, 0}.

    The case s = 0 already being proved, we know that there is a T_{1} > 0 , such hat

    u\in C\left([0, T_{1}), G_{0}^{\sigma_{0}/2, 0} \right),

    and

    u\in C\left([0, T], G_{0}^{2\varsigma T^{-1/\varrho}, 0} \right), \ \ for \ T\geq T_{1},

    where \varsigma > 0 depends on f, \sigma_{0} and \varsigma . We now conclude that

    u\in C\left([0, T_{1}), G_{s}^{\sigma_{0}/4, 0} \right),

    and

    u\in C\left([0, T], G_{s}^{\varsigma T^{-1/\varrho}, 0} \right), \ \ for \ T\geq T_{1}.

    The proof of Theorem 2.2 is now completed.

    We follow the methods found in [5,6,7,11] to treat the regularity in time in Gevrey sens for unique solution of (1.1).

    Proposition 5.1. Let \delta > 0, s_{1} > -\frac{\alpha-1}{4} , s_{2}\geq0 and

    u \in C\left( [0, \delta ];G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}\right),

    be the solution of (1.1). Then u belong in x, y to G^{\kappa} for all times near the zero. In other words,

    \begin{equation} \vert \partial_{x}^{l} \partial_{y}^{n}u(x, y, t)\vert\leq C^{l+n+1}(l!)^{\kappa}(n!)^{\kappa}, \ \end{equation} (5.1)

    for all (x, y) \in \mathbb{R}^{2} \quad, C > 0, t \in [0, \delta], l, n \in \lbrace 0, 1, ...\rbrace.

    Proof. We have, for any t \in [0, \delta]

    \begin{equation*} \begin{array}{ll} \Vert \partial_{x}^{l}\partial_{y}^{n}u(\cdot, \cdot, t)\Vert^{2}_{H^{s_{1}, s_{2}}}& = \int_{\mathbb{R}^{2}}\langle \xi \rangle ^{2s_{1}}\langle \eta \rangle ^{2s_{2}} \vert\widehat{\partial_{x}^{l}\partial_{y}^{n}u}(\xi, \eta, t)\vert^{2} d\xi d\eta\\ \\ & = \int_{\mathbb{R}^{2}}\vert \xi\vert^{2l}\vert \eta\vert^{2n}\langle \xi \rangle ^{2s_{1}}\langle \eta \rangle ^{2s_{2}} \vert\widehat{u}(\xi, \eta, t)\vert^{2} d\xi d\eta \\ \\ & = \int_{\mathbb{R}^{2}}\vert \xi\vert^{2l}\vert \eta\vert^{2n}e^{-2\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{-2\sigma_2 |\eta|^{\frac{1}{\kappa}}}\langle \xi \rangle ^{2s_{1}}\langle \eta \rangle ^{2s_{2}}e^{2\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \vert\widehat{u}(\xi, \eta, t)\vert^{2} d\xi d\eta. \end{array} \end{equation*}

    We observe that

    \begin{equation*} e^{\frac{2\sigma_1}{\kappa} |\xi|^{\frac{1}{\kappa}}} = \sum\limits_{j = 0}^{\infty}\frac{1}{j!}\left(\frac{2\sigma_1}{\kappa}\vert \xi\vert^{\frac{1}{\kappa}} \right)^{j} \geq \frac{1}{(2l)!}\bigg(\frac{2\sigma_1}{\kappa}\bigg) ^{2l}\vert \xi\vert^{\frac{2l}{\kappa}}, \quad\forall l \in \lbrace 0, 1, ...\rbrace, \xi\in \mathbb{R}, \end{equation*}

    and

    \begin{equation*} e^{\frac{2\sigma_2}{\kappa} |\eta|^{\frac{1}{\kappa}}} = \sum\limits_{j = 0}^{\infty}\frac{1}{j!}\left(\frac{2\sigma_2}{\kappa}\vert \eta\vert^{\frac{1}{\kappa}} \right)^{j} \geq \frac{1}{(2n)!}\bigg(\frac{2\sigma_2}{\kappa}\bigg) ^{2n}\vert \eta\vert^{\frac{2l}{\kappa}}, \quad\forall n \in \lbrace 0, 1, ...\rbrace, \eta\in \mathbb{R}. \end{equation*}

    This implies that

    \vert \xi\vert^{2l}e^{-{2\sigma_{1}}\vert \xi\vert^{\frac{1}{\kappa}}}\leq C_{\sigma_{1}, \kappa}^{2l}(2l)!^{\kappa},
    \vert \eta\vert^{2n}e^{-{2\sigma_{2}}\vert \eta\vert^{\frac{1}{\kappa}}}\leq C_{\sigma_{2}, \kappa}^{2n}(2n)!^{\kappa}.

    Thus,

    \begin{eqnarray} \Vert \partial_{x}^{l}\partial_{y}^{n}u(\cdot, \cdot, t)\Vert^{2}_{H^{s_{1}, s_{2}}}&\leq& C_{\sigma_{1}, \sigma_{2}, \kappa}^{2l+2n}(2l)!^{\kappa} (2n)!^{\kappa} \int_{\mathbb{R}^{2}}\langle \xi \rangle ^{2s_{1}}\langle \eta \rangle ^{2s_{2}}e^{2\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \vert\widehat{u}(\xi, \eta, t)\vert^{2} d\xi d\eta \\ & = &C_{\sigma_{1}, \sigma_{2}, \kappa}^{2l+2n}(2l)!^{\kappa} (2n)!^{\kappa}\Vert u(\cdot, \cdot, t)\Vert^{2}_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}}. \end{eqnarray}

    Since (2l)!^{\kappa} \leq c_{1}^{2l}(l!)^{2\kappa} and (2n)!^{\kappa} \leq c_{2}^{2n}(n!)^{2\kappa} , for some c_{1}, c_{2} > 0 , we have for all l, n \in \{0, 1, 2, \dots \}

    \begin{equation*} \vert \partial_{x}^{l} \partial_{y}^{n}u\vert\lesssim\Vert \partial_{x}^{l}\partial_{y}^{n}u(\cdot, \cdot, t)\Vert_{H^{s_{1}, s_{2}}}\leq C_{0}C_{1}^{l+n}(l)!^{\kappa}(n)!^{\kappa}\ \ \ \text{for}\quad \forall t \in [0, \delta ], \end{equation*}

    where C_{0} = \Vert u(\cdot, \cdot, t)\Vert_{G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}} and C_{1} = c_{0}^{2}C_{\sigma_{1}, \sigma_{2}, \kappa} and c_{0} = \max(c_{1}, c_{2}) , which implies that the solution u is analytic in x, y for all time near zero and s_{1}, s_{2} \geq 0 .

    Now, for -\frac{\alpha-1}{4} < s_{1} < 0 , s_{2} \geq 0 and for any 0 < \epsilon < \sigma_{1} , there exists a positive constant C = C_{s, \epsilon} > 0 such that

    \begin{equation*} \begin{array}{l} \int_{\mathbb{R}^{2}}e^{2(\sigma_{1}-\epsilon)\vert \xi\vert^{\frac{1}{\kappa}}}e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \langle \eta\rangle^{2s_{2}} \vert\widehat{u}(\xi, \eta, t)\vert^{2}d\xi d\eta \\ \\ \leq C \int_{\mathbb{R}^{2}}\frac{e^{2\epsilon\vert \xi\vert^{\frac{1 }{\kappa}}}}{\langle \xi \rangle ^{-2s_{1}}}e^{2(\sigma_{1}-\epsilon)\vert \xi\vert^{\frac{1}{\kappa}}}e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \langle \eta\rangle^{2s_{2}} \vert\widehat{u}(\xi, \eta, t)\vert^{2}d\xi d\eta \\ \\ = C \int_{\mathbb{R}^{2}}\langle \xi \rangle ^{2s_{1}}\langle \eta \rangle ^{2s_{2}}e^{2\sigma_1 |\xi|^{\frac{1}{\kappa}}} e^{2\sigma_2 |\eta|^{\frac{1}{\kappa}}} \vert\widehat{u}(\xi, \eta, t)\vert^{2} d\xi d\eta. \end{array} \end{equation*}

    This implies that if

    u \in C\left( [0, T ];G_{s_{1}, s_{2}}^{\sigma_1, \sigma_2, \kappa}\right) \ and \ s_{1} < 0, s_{2}\geq 0,

    then

    u \in C\left( [0, T ];G_{0, s_{2}}^{\sigma_1-\epsilon, \sigma_2, \kappa}\right),

    which allows us to conclude that u is in G^{\kappa} in x, y for all s_{1} > -\frac{\alpha-1}{4} , s_{2}\geq0 .

    In order to prove Theorem 2.3 it is enough to prove the following result.

    Lemma 5.2. For j, l, n \in \lbrace 0, 1, 2, \dots\rbrace , the next inequality

    \begin{equation} \big\vert \partial_{t}^{j}\partial_{x}^{l}\partial_{y}^{n}u \big\vert\leq C^{j+l+n+1}((l+n+(\alpha+1) j)!)^{\kappa} L^{j}, \end{equation} (5.2)

    holds, where L = C^{\alpha}+\frac{1}{120^{\kappa}}+\frac{C}{40^{\kappa}} , \forall x, y \in \mathbb{R} , t \in [0, \delta] .

    In fact, taking l = n = 0 we obtain

    \begin{equation*} \big\vert \partial_{t}^{j}u \big\vert\leq C^{j+1}((\alpha+1) j!)^{\kappa} L^{j}\leq K^{j+1}(j!)^{(\alpha+1)\kappa}. \end{equation*}

    Proof. We use the induction on j to prove Lemma 5.2.

    For j = 0 and l, n\in \lbrace 0, 1, 2, \dots\rbrace , we have, by (5.1)

    \begin{equation} \big\vert \partial_{x}^{l} \partial_{y}^{n}u(x, y, t)\big\vert\leq C^{l+n+1}(l!)^{\kappa}(n!)^{\kappa}\leq C^{l+n+1}(l+n)!^{\kappa}. \end{equation} (5.3)

    For j = 1 and l, n\in \lbrace 0, 1, 2, \dots\rbrace , we have

    \begin{equation} \big\vert \partial_{t}\partial_{x}^{l}\partial_{y}^{k}u \big\vert \leq\big\vert |D_{x}|^{\alpha}\partial_{x}^{l+1}\partial_{y}^{n}u \big\vert+ \big\vert \partial_{x}^{l-1}\partial_{y}^{n+2}u \big\vert+ \big\vert \partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) \big\vert. \end{equation} (5.4)

    The terms of (5.4) can be estimated as

    \begin{equation} \begin{array}{ll} \big\vert |D_{x}|^{\alpha}\partial_{x}^{l+1}\partial_{y}^{n}u \big\vert &\leq C^{l+1+\alpha+n+1}(l+1+\alpha+n)!^{\kappa} \\ \\&\leq C^{l+n+1+1}(l+n+(\alpha+1)\cdot 1)!^{\kappa}C^{\alpha}, \end{array} \end{equation} (5.5)
    \begin{equation} \begin{array}{ll} \big\vert \partial_{x}^{l-1}\partial_{y}^{n+2}u \big\vert &\leq C^{l-1+n+2+1}(l-1+n+2)!^{\kappa} \\ \\&\leq C^{l+n+1+1}(l+n+5\cdot1)!\dfrac{1}{(l+n+2)^{\kappa}(l+n+3)^{\kappa}(l+n+4)^{\kappa}(l+n+5)^{\kappa}} \\ \\ &\leq C^{l+n+1+1}(l+n+5\cdot1)!\dfrac{1}{120^{\kappa}}. \end{array} \end{equation} (5.6)

    The nonlinear terms are treated as follows

    \begin{equation*} \begin{array}{ll} \big\vert \partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) \big\vert & = \Bigg\vert \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l}{p}\binom{n}{k}\left(\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{x}^{p+1}\partial_{y}^{k}u \right) \Bigg \vert. \end{array} \end{equation*}

    Recalling that for l \geq p and n \geq k , we have the next inequality

    \begin{equation} \binom{l}{p}\binom{n}{k}\leq \binom{l+n}{p+k}. \end{equation} (5.7)

    By (5.7), we have

    \begin{eqnarray} \big\vert \partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) \big\vert &\leq&\Bigg\vert \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l+n}{p+k}^{{ }}\left(\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{x}^{p+1}\partial_{y}^{k}u \right) \Bigg \vert \\ \\ &\leq& \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\dfrac{((l+n)!)^{\kappa}}{((p+k)!)^{\kappa}((l+n-p-k)!)^{\kappa}}C^{l-p+n-k+1}((l+n-p-k)!)^{\kappa}\\ \\ &&C^{p+1+k+1}((p+1+k)!)^{\kappa} \\ \\ & = &C^{l+n+3}((l+n)!)^{\kappa}\sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}(p+1+k)^{\kappa}. \end{eqnarray}

    At this stage, we use the fact that

    \begin{equation} \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}(p+1+k) = \dfrac{(l+1)(n+1)(l+n+2)}{2}. \end{equation} (5.8)

    Then,

    \begin{equation} \begin{array}{ll} \big\vert \partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) \big\vert &\leq C^{l+n+3}((l+n)!)^{\kappa}\dfrac{(l+1)^{\kappa}(n+1)^{\kappa}(l+n+2)^{\kappa}}{2^{\kappa}}\\ \\ &\leq C^{l+n+1+1}((l+n)!)^{\kappa}(l+n+1)^{\kappa}(l+n+2)^{\kappa}(l+n+3)^{\kappa}\dfrac{C}{2^{\kappa}}\\ \\& = C^{l+n+1+1}((l+n+(\alpha+1))!)^{\kappa}\dfrac{1}{(l+n+4)^{\kappa}(l+n+(\alpha+1))^{\kappa}} \dfrac{C}{2^{\kappa}} \\ \\ &\leq C^{l+n+1+1}((l+n+(\alpha+1)\cdot 1)!)^{\kappa} \dfrac{C}{40^{\kappa}}. \end{array} \end{equation} (5.9)

    From (5.5), (5.6) and (5.9), it follows that

    \begin{equation*} \big\vert \partial_{t}\partial_{x}^{l}\partial_{y}^{k}u \big\vert\leq C^{l+n+1+1}((l+n+(\alpha+1)\cdot 1)!)^{\kappa} L^{1}, \forall x, y \in \mathbb{R}, t \in [0, \delta]. \end{equation*}

    We assume that (5.2) is correct for j \geq m \geq 1 where l, n\in \lbrace 0, 1, 2, \dots \rbrace and then we prove it for m = j+1 and l, n\in \lbrace 0, 1, 2, \dots \rbrace .

    We obtain

    \big\vert \partial_{t}^{j+1}\partial_{x}^{l}\partial_{y}^{k}u \big\vert \leq \big\vert\partial_{t}^{j} |D_{x}|^{\alpha}\partial_{x}^{l+1}\partial_{y}^{n}u \big\vert+\big\vert\partial_{t}^{j} \partial_{x}^{l-1}\partial_{y}^{n+2}u \big\vert+ \big\vert\partial_{t}^{j} \partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) \big\vert.

    These terms are estimated as follows

    \begin{equation} \begin{array}{ll} \big\vert\partial_{t}^{j}|D_{x}|^{\alpha}\partial_{x}^{l+1}\partial_{y}^{n}u \big\vert &\leq C^{j+l+(\alpha+1)+n+1}(l+n+((\alpha+1)(j+1))!)^{\kappa}L^{j} \\ \\&\leq C^{(j+1)+l+n+1}(l+n+((\alpha+1)(j+1))!)^{\kappa}C^{\alpha}L^{j}, \end{array} \end{equation} (5.10)

    and

    \begin{equation} \begin{array}{ll} \big\vert\partial_{t}^{j} \partial_{x}^{l-1}\partial_{y}^{n+2}u \big\vert &\leq C^{j+l-1+n+2+1}((j+l-1+n+2)!)^{\kappa}L^{j}\\ \\ &\leq C^{(j+1)+l+n+1}((l+n+(\alpha+1)(j+1))!)^{\kappa}\dfrac{L^{j}}{120^{\kappa}}. \end{array} \end{equation} (5.11)

    The nonlinear terms are treated as follows

    \begin{equation} \begin{array}{ll} \partial_{t}^{j}\partial_{x}^{l}\partial_{y}^{n}(u\partial_{x}u) & = \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l}{p}\binom{n}{k}\left(\partial_{t}^{j}\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{x}^{p+1}\partial_{y}^{k}u \right)\\&+ \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l}{p}\binom{n}{k}\left(\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{t}^{j}\partial_{x}^{p+1}\partial_{y}^{k}u \right)\\&+ \sum\limits_{q = 1}^{j-1}\sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{j}{q}\binom{l}{p}\binom{n}{k}\left(\partial_{t}^{j-q}\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{t}^{q}\partial_{x}^{p+1}\partial_{y}^{k}u \right). \end{array} \end{equation} (5.12)

    Using (5.7) to estimate (5.12) _1

    \begin{eqnarray} &&\left \vert \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l}{p}\binom{n}{k}\left(\partial_{t}^{j}\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{x}^{p+1}\partial_{y}^{k}u \right) \right\vert\\ &&\leq\dfrac{1}{3} C^{(j+1)+l+n+1}((l+n+(\alpha+1)(j+1))!)^{\kappa}\dfrac{C}{40^{\kappa}}L^{j}. \end{eqnarray} (5.13)

    We estimate (5.12) _2 as

    \begin{eqnarray} &&\bigg\vert \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{l}{p}\binom{n}{k}\left(\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{t}^{j}\partial_{x}^{p+1}\partial_{y}^{k}u \right) \bigg\vert \leq\\ &&\dfrac{1}{3} C^{(j+1)+l+n+1}((l+n+(\alpha+1)(j+1))!)^{\kappa}\dfrac{C}{40^{\kappa}}L^{j}. \end{eqnarray} (5.14)

    To estimate (5.12) _3 , we recall that for j \geq q , l\geq p and n \geq k , we have the next inequality

    \begin{equation*} \binom{j}{q}\binom{l}{p}\binom{n}{k}\leq \binom{j+l+n}{q+p+k}. \end{equation*}

    Then

    \begin{equation} \begin{array}{l} \left\vert \sum\limits_{q = 1}^{j-1} \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{j}{q}\binom{l}{p}\binom{n}{k}\left(\partial_{t}^{j-q}\partial_{x}^{l-p}\partial_{y}^{n-k}u \right)\left(\partial_{t}^{q}\partial_{x}^{p+1}\partial_{y}^{k}u \right) \right\vert \\ \\ \leq \sum\limits_{q = 1}^{j-1} \sum\limits_{p = 0}^{l}\sum\limits_{k = 0}^{n}\binom{j+l+n}{q+p+k} C^{j-q+l-p+n-k+1} ((l-p+n-k+(\alpha+1)(j-q))!)^{\kappa}L^{j-q}\\ \\ C^{q+p+1+k+1}((p+1+k+(\alpha+1)q)!)^{\kappa} L^{q} \\ \\ \leq \dfrac{1}{3}C^{(j+1)+l+n+1}((l+n+(\alpha+1)(j+1))!)^{\kappa} \dfrac{C}{40^{\kappa}}L^{j}. \end{array} \end{equation} (5.15)

    Finally by using (5.13)-(5.15) we arrive at

    \begin{equation*} \big\vert \partial_{t}^{j+1}\partial_{x}^{l}\partial_{y}^{k}u\big \vert\leq C^{(j+1)+l+n+1}((l+n+(\alpha+1)(j+1))!)^{\kappa} L^{j+1}, \end{equation*}

    for all (x, y) \in \mathbb{R}^{2}, t \in [0, \delta] .

    The detailed proof of (5.12) for \kappa = 1 is given in [6].

    We have discussed the local well-posedness for a generalized Kadomtsev-Petviashvili I equation in an anisotropic Gevrey space. We proved the existence of solutions using the Banach contraction mapping principle. This was done by using the bilinear estimates in anisotropic Gevrey-Bourgain. We used this local result and a Gevrey approximate conservation law to prove that global solutions exist. These solutions are Gevrey class of order (\alpha+1)\kappa in the time variable. The results of the present paper are new and significantly contribute to the existing literature on the topic.

    The authors wish to thank deeply the anonymous referee for his/here useful remarks and his/here careful reading of the proofs presented in this paper.

    The authors declare that they have no conflict of interest.



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