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Non-uniqueness of the transport equation at high spacial integrability

Jingpeng Wu Corresponding author. School of Mathematics and Statistics, Huazhong University of Science and Technology; Institute of Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, China (jpwu_postdoc@hust.edu.cn).    Xianwen Zhang School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan, 430074, China (xwzhang@hust.edu.cn)
Abstract

In this paper, we show the non-uniqueness of the weak solution in the class ρLtsLxp\rho\in L^{s}_{t}L^{p}_{x} for the transport equation driven by a divergence-free vector field 𝒖Lts~Wx1,qLtsLxp\boldsymbol{u}\in L^{\tilde{s}}_{t}W^{1,q}_{x}\cap L_{t}^{s^{\prime}}L_{x}^{p^{\prime}} happens in the range 1/p+1/q>1p14(p+1)p1/p+1/q>1-\frac{p-1}{4(p+1)p} with some s~>1\tilde{s}>1, as long as 1s<1\leq s<\infty, p>1p>1. As a corollary, LL^{\infty} in time of the density ρ\rho is critical in some sense for the uniqueness of weak solution. Our proof is based on the convex integration method developed in [39, 20].

Keywords: Transport equation; non-uniqueness; convex integration.

MR Subject Classification: 35A02; 35D30; 35Q35.

1 Introduction

This paper deals with the problem of (non-)uniqueness of weak solution to the linear transport equation on the torus 𝕋d:=dd\mathbb{T}^{d}:=\mathbb{R}^{d}\setminus\mathbb{Z}^{d} written by

{tρ+𝒖ρ=0,ρ|t=0=ρ0,\left\{\begin{split}&\partial_{t}\rho+\boldsymbol{u}\cdot\nabla\rho=0,\\ &\rho|_{t=0}=\rho_{0},\end{split}\right. (1.1)

where ρ:[0,T]×𝕋d\rho\colon[0,T]\times\mathbb{T}^{d}\to\mathbb{R} is the unknown density, ρ0\rho_{0} is the initial data and 𝒖:[0,T]×𝕋dd\boldsymbol{u}\colon[0,T]\times\mathbb{T}^{d}\to\mathbb{R}^{d} is a given divergence-free vector field, i.e. div𝒖=0\operatorname{div}\boldsymbol{u}=0 in the sense of distribution. In this case, the weak solution to (1.1) is defined as

𝕋dρ0ϕ(0,x)𝑑x=0T𝕋dρ(tϕ+𝒖ϕ)𝑑x𝑑t for all ϕCc([0,T)×𝕋d).\int_{\mathbb{T}^{d}}\rho_{0}\phi(0,x)\,dx=\int_{0}^{T}\int_{\mathbb{T}^{d}}\rho(\partial_{t}\phi+\boldsymbol{u}\cdot\nabla\phi)\,dx\,dt\,\text{ for all }\phi\in C_{c}^{\infty}([0,T)\times\mathbb{T}^{d}).

Another equivalent definition is (see e.g. [34, p276])

0T𝕋dρ(tϕ+𝒖ϕ)𝑑x𝑑t=0 for all ϕCc((0,T)×𝕋d),\int_{0}^{T}\int_{\mathbb{T}^{d}}\rho(\partial_{t}\phi+\boldsymbol{u}\cdot\nabla\phi)\,dx\,dt=0\,\text{ for all }\phi\in C_{c}^{\infty}((0,T)\times\mathbb{T}^{d}),

and ρ\rho is continuous in time with limt0+ρ(t)=ρ0\lim_{t\to 0^{+}}\rho(t)=\rho_{0} in the distributional sense.

Since the transport equation is linear, the existence of weak solutions can be obtained by the method of regularization even for very rough vector fields, see [35, Proposition II.1]. However, to obtain the uniqueness, more complicated discussions will be involved.

1.1 Background

In the smooth setting, the method of characteristics solves first-order PDE by converting the PDE into an appropriate system of ODE [37, Sec.3.2]. In particular, for Lipschitz vector fields uCtWx1,u\in C_{t}W^{1,\infty}_{x}, the solution to (1.1) can be given by the Lagrangian representation ρ(t,x)=ρ0(X(0,t,x))\rho(t,x)=\rho_{0}(X(0,t,x)) with the flow map XX solving the ODEs

{tX(t,τ,x)=𝒖(t,X(t,τ,x)),X(τ,τ,x)=x.\left\{\begin{split}\partial_{t}X(t,\tau,x)&=\boldsymbol{u}(t,X(t,\tau,x)),\\ X(\tau,\tau,x)&=x.\end{split}\right. (1.2)

This link results in the existence and uniqueness of the PDE (1.1) by the Cauchy-Lipschitz (Picard-Linderöf) theory for the ODE (1.2) (The Lipschitz condition on the vector fields can be replaced by one-side Lipschitz, log\log-Lipschitz or Osgood condition, we refer to [1] for the elaborate surveys).

For non-Lipschitz vector fields, the link is less obvious and the uniqueness issue of (1.1) becomes subtler. The first breakthrough result traces back to the celebrated work of DiPerna and Lions [35], they proved that for all p[1,]p\in[1,\infty], the Lagrangian representation and uniqueness hold in the class LtLxpL^{\infty}_{t}L^{p}_{x} for any given vector field 𝒖Lt1Wx1,p\boldsymbol{u}\in L^{1}_{t}W^{1,p^{\prime}}_{x} with div𝒖L\operatorname{div}\boldsymbol{u}\in L^{\infty}, where pp^{\prime} is the Hölder conjugate exponent of pp. This result was extended to the case ρLt,x,𝒖Lt1BV\rho\in L^{\infty}_{t,x},\boldsymbol{u}\in L^{1}_{t}BV by Ambrosio [6] with deep tools from geometric measure theory. Whereafter, there are abundant researches for the theory of non-smooth vector fields and their applications on non-linear PDEs. For instance, the analogous results of [35, 6] have been established, for vector fields with gradient given by a singular integral in [13] and for nearly incompressible BVBV vector fields in [11], and the results in [13] has been adapted to obtain the Lagrangian solutions for the Vlasov-Poisson system with L1L^{1} data [12], see also [8]. We refer to the works [22, 23, 38, 25, 18, 19] and the surveys [9, 28, 24, 7] for other important progresses and related results in this direction.

For the non-uniqueness issue of (1.1), two examples were given by DiPerna and Lions [35], for an autonomous vector field 𝒖W1,p\boldsymbol{u}\in W^{1,p^{\prime}} but div𝒖L\operatorname{div}\boldsymbol{u}\notin L^{\infty} and for an autonomous divergence-free vector field 𝒖0s<1Ws,1\boldsymbol{u}\in\cap_{0\leq s<1}W^{s,1} but 𝒖W1,1\boldsymbol{u}\notin W^{1,1}. Much later, based on the work [2], Depauw [33] constructed an example of a divergence-free vector field 𝒖Lloc1((0,T];BV(2))\boldsymbol{u}\in L^{1}_{\rm loc}((0,T];BV(\mathbb{R}^{2})) but 𝒖L1(0,T;BV(2))\boldsymbol{u}\notin L^{1}(0,T;BV(\mathbb{R}^{2})), in the class of bounded densities. See also [10, 42, 5]. In [3, 4], Alberti, Bianchini and Crippa showed an example of an autonomous divergence-free vector field 𝒖0α<1C0,α(2)\boldsymbol{u}\in\cap_{0\leq\alpha<1}C^{0,\alpha}(\mathbb{R}^{2}) but 𝒖C0,1(2)\boldsymbol{u}\notin C^{0,1}(\mathbb{R}^{2}), in the class of bounded densities. More recently, based on anomalous dissipation and mixing, Drivas, Elgindi, Iyer and Jeong proved non-uniqueness in the class ρLtLx2\rho\in L^{\infty}_{t}L^{2}_{x} for 𝒖Lt1C1\boldsymbol{u}\in L^{1}_{t}C^{1-} [36]. Roughly speaking, these results are proved by showing the non-uniqueness of the flow maps (the ODE level), with the violation of either the boundedness of div𝒖\operatorname{div}\boldsymbol{u} or the spacial Wloc1,1W^{1,1}_{\rm loc} regularity of 𝒖\boldsymbol{u}.

Another approach is based on the convex integration technique (for complete summaries on this enormous theory, we refer to the surveys articles [30, 31, 32, 15, 17]), which gives counterexamples of uniqueness directly at the PDE level. The first non-uniqueness result with this technique was obtained by Crippa et al in [26] using the framework of [29], but for vector field 𝒖\boldsymbol{u} was merely bounded. Later, a breakthrough result for the Sobolev vector field was obtained by Modena and Székelyhidi [40]. Based on their work, a series of works for the non-uniqueness to (1.1) have been done recently, we list the main functional setting of them below:

  1. (I).

    [40](Modena and Székelyhidi): ρCtLxp\rho\in C_{t}L^{p}_{x}, 𝒖Ct(Wx1,qLxp)\boldsymbol{u}\in C_{t}(W^{1,q}_{x}\cap L^{p^{\prime}}_{x}) for 1p+1q>1+1d1\frac{1}{p}+\frac{1}{q}>1+\frac{1}{d-1}, p>1p>1 and d3d\geq 3.

  2. (II).

    [41](Modena and Székelyhidi): ρCtLx1\rho\in C_{t}L^{1}_{x}, 𝒖CtWx1,qCt,x\boldsymbol{u}\in C_{t}W^{1,q}_{x}\cap C_{t,x} for q<d1q<d-1 and d3d\geq 3.(The case p=1p=1 of [40])

  3. (III).

    [39](Modena and Sattig): ρCtLxp\rho\in C_{t}L^{p}_{x}, 𝒖Ct(Wx1,qLxp)\boldsymbol{u}\in C_{t}(W^{1,q}_{x}\cap L^{p^{\prime}}_{x}) for 1p+1q>1+1d\frac{1}{p}+\frac{1}{q}>1+\frac{1}{d} and d2d\geq 2.

  4. (IV).

    [14](Bruè, Colombo and De Lellis): ρ>0\rho>0, ρCtLxp\rho\in C_{t}L^{p}_{x}, 𝒖Ct(Wx1,qLxp)\boldsymbol{u}\in C_{t}(W^{1,q}_{x}\cap L^{p^{\prime}}_{x}) for 1p+1q>1+1d\frac{1}{p}+\frac{1}{q}>1+\frac{1}{d}, p>1p>1 and d2d\geq 2.

  5. (V).

    [20](Cheskidov and Luo): ρLt1Lxp\rho\in L^{1}_{t}L^{p}_{x}, 𝒖Lt1Wx1,qLtLxp\boldsymbol{u}\in L^{1}_{t}W^{1,q}_{x}\cap L^{\infty}_{t}L^{p^{\prime}}_{x} for 1p+1q>1\frac{1}{p}+\frac{1}{q}>1, p>1p>1 and d3d\geq 3.

Comments:

Very recently, [19] proves that the uniqueness result holds for 𝒖LtWx1,q\boldsymbol{u}\in L^{\infty}_{t}W^{1,q}_{x} with q>dq>d in the class ρLt,x1\rho\in L^{1}_{t,x} under the assumption that the so called forward-backward integral curves of 𝒖\boldsymbol{u} are trivial. Whereas, the non-uniqueness result of [39] holds for 𝒖LtWx1,q\boldsymbol{u}\in L^{\infty}_{t}W^{1,q}_{x} with q<dq<d in the class ρCtLx1\rho\in C_{t}L^{1}_{x}. Hence, roughly speaking when p=1p=1, the regularity condition 𝒖LtWx1,q\boldsymbol{u}\in L^{\infty}_{t}W^{1,q}_{x} with q>dq>d is optimal for the uniqueness of the weak solution in the class Lt,x1L^{1}_{t,x}.

When p>1p>1, the uniqueness is unclear in the range 1<1p+1q1+1d1<\frac{1}{p}+\frac{1}{q}\leq 1+\frac{1}{d} for ρCtLxp\rho\in C_{t}L^{p}_{x}, 𝒖Ct(Wx1,qLxp)\boldsymbol{u}\in C_{t}(W^{1,q}_{x}\cap L^{p^{\prime}}_{x}). However, [14, Theorem 1.5] states that the uniqueness result holds for positive density ρLtLxp\rho\in L^{\infty}_{t}L^{p}_{x} and 𝒖Lt1Wx1,q\boldsymbol{u}\in L^{1}_{t}W^{1,q}_{x} with 1p+1q<1+q1(d1)q\frac{1}{p}+\frac{1}{q}<1+\frac{q-1}{(d-1)q}, which goes beyond the DiPerna-Lions range.

In [20], the non-uniqueness with the sharp spacial integrability (1/p+1/q>11/p+1/q>1) has been reached but at the expensive of time regularity. They proved the result using the convex integration scheme of [40] combined with temporal intermittency and oscillations in the spirit of [16]. We refer to [16, 20, 17] for a more comprehensive discussion of the temporal intermittency.

A few months after we finished this paper, we learn that Cheskidov and Luo post a extremely nice result [21] on arXiv, in which they show the non-uniqueness result for uLt1Wx1,pu\in L_{t}^{1}W_{x}^{1,p}, p<\forall p<\infty, ρp<,kLtpCk\rho\in\cap_{p<\infty,k\in\mathbb{N}}L_{t}^{p}C^{k}, it also implies that the time-integrability assumption in the uniqueness of the DiPerna-Lions theory is sharp. In view of this surprising result, we have reconsidered the implications of our study, see Remark 1.3.

1.2 Main results

Based on the frameworks of [39, 20], we obtain the following main result in this paper, which indicates that the non-uniqueness happens even in the range 1/p+1/q>1p14(p+1)p1/p+1/q>1-\frac{p-1}{4(p+1)p}, as long as 1s<1\leq s<\infty, p>1p>1.

Theorem 1.1.

Let d3d\geq 3 and p,q,s,s~[1,)p,q,s,\tilde{s}\in[1,\infty), p,sp^{\prime},s^{\prime} are Hölder conjugate exponents of p,sp,s respectively, satisfying p>1p>1 and

1p+1q>1p14(p+1)p,s~ss/s+(1+2β)/(1+4β)\frac{1}{p}+\frac{1}{q}>1-\frac{p-1}{4(p+1)p},\quad\tilde{s}\leq\frac{s}{s/s^{\prime}+(1+2\beta)/(1+4\beta)} (1.3)

with β=(p1)(d1)/4p(p+1)\beta=(p-1)(d-1)/4p(p+1).

Then there exists a divergence-free vector field

𝒖Ls~(0,T;W1,q(𝕋d))Ls(0,T;Lp(𝕋d)),\boldsymbol{u}\in L^{\tilde{s}}(0,T;W^{1,q}(\mathbb{T}^{d}))\cap L^{s^{\prime}}(0,T;L^{p^{\prime}}(\mathbb{T}^{d})),

such that the uniqueness of (1.1) fails in the class ρLs(0,T;Lp(𝕋d))\rho\in L^{s}(0,T;L^{p}(\mathbb{T}^{d})).

Remark 1.1.

On the one hand, Theorem 1.1 means that even for the spacial integrability higher than the DiPerna-Lions regime (1p14(p+1)p<1/p+1/q<1)(1-\frac{p-1}{4(p+1)p}<1/p+1/q<1), non-uniqueness still happens, which might be new in contrast to the previous works [39, 14, 20]. On the other hand, notice for p>1p>1 and 1/s+1/s=11/s+1/s^{\prime}=1,

s>ss/s+(1+2β)/(1+4β)>1,s^{\prime}>\frac{s}{s/s^{\prime}+(1+2\beta)/(1+4\beta)}>1,

s~\tilde{s} might be taken greater than 1, hence we improve the result of [20] in two aspects: the restrictions on time integrability (s,s~s,\tilde{s}) and on spacial integrability (p,qp,q).

Remark 1.2.

After suitable parameters setting, the condition (1.3) might be replaced by

1p+1q>1p,s~1,\frac{1}{p}+\frac{1}{q}>\frac{1}{p},\quad\tilde{s}\equiv 1, (1.4)

i.e., we allow the spatial integrability of uu can be arbitrary q[1,)q\in[1,\infty). However, since the low time integrability s~1\tilde{s}\equiv 1, Cheskidov and Luo’s work [21] fully covers our result in this case. We mention that a comfortable condition on s~\tilde{s} might be s~s\tilde{s}\leq s^{\prime}. However, it can not be reached in this paper, since the second condition in (1.3) or (1.4) plays a significant role in the proof of Lemma 4.8 (When s~s\tilde{s}\to s^{\prime}, we need to set α0\alpha\to 0 in the proof of Lemma 4.8, then the balance of parameters setting in Sec.4.3 will be upset).

Remark 1.3.

Cheskidov and Luo’s work [21] is very exciting, since they improve extremely the spatial regularity for the non-uniqueness. However, this is achieved by abandoning all the time regularity of the vector field uu except L1L^{1} integrability. A significant difference between Theorem 1.1 and Cheskidov, Luo’s result [21] is that we can provide non-uniqueness with a little higher temporal integrability of u\nabla u (s~>1\tilde{s}>1). To the best of the authors’ knowledge, there is no result of the non-uniqueness for uLts~Wx1,qLtsLx1,pu\in L_{t}^{\tilde{s}}W_{x}^{1,q}\cap L_{t}^{s^{\prime}}L_{x}^{1,p^{\prime}}, ρLtsLxp\rho\in L_{t}^{s}L_{x}^{p} under the range 1/q+1/p1+1/d1/q+1/p\leq 1+1/d, 1<s~s<1<\tilde{s}\leq s^{\prime}<\infty before Theorem 1.1. Notice also when s~=s=\tilde{s}=s^{\prime}=\infty, [19] has proved the uniqueness for 𝐮LtWx1,q\boldsymbol{u}\in L^{\infty}_{t}W^{1,q}_{x} with q>dq>d, ρLt,x1\rho\in L^{1}_{t,x} under some additional assumptions of integral curves of 𝐮\boldsymbol{u}. Hence it might be an interesting and valuable problem to consider uniqueness/non-uniqueness under high temporal integrability of u\nabla u and high spatial integrability of ρu\rho\nabla u (1/p+1/q1+1/d1/p+1/q\leq 1+1/d).

Remark 1.4.

It seems possible to extend Theorem 1.1 to the border case p=1p=1 and to the transport-diffusion equation

tρ+𝒖ρΔρ=0\partial_{t}\rho+\boldsymbol{u}\cdot\nabla\rho-\Delta\rho=0

by utilizing the technique in [41, 39]. We finally mention that the two dimensional case d=2d=2 is not treated in this paper due to the stationary Mikado flow, see Remark 3.4. However, thanks to the recent tricks given by Cheskidov and Luo [21], our result can be extended to the two dimensional case without difficulty.

Notice 1p14(p+1)p<11-\frac{p-1}{4(p+1)p}<1 as long as p>1p>1. Hence, combine the uniqueness result in [35, Corollary II.1], we obtain immediately from Theorem 1.1 that at least in the following sense, the LL^{\infty} in time of the density ρ\rho is critical for the uniqueness of weak solutions to (1.1).

Corollary 1.2.

Let d3d\geq 3, p(1,)p\in(1,\infty) and s[1,]s\in[1,\infty]. The following holds.

  1. (i).

    If s<s<\infty, then there exists a divergence-free vector field

    𝒖L1(0,T;W1,p(𝕋d))Ls(0,T;Lp(𝕋d)),\boldsymbol{u}\in L^{1}(0,T;W^{1,p^{\prime}}(\mathbb{T}^{d}))\cap L^{s^{\prime}}(0,T;L^{p^{\prime}}(\mathbb{T}^{d})),

    such that the uniqueness of (1.1) fails in the class Ls(0,T;Lp(𝕋d))L^{s}(0,T;L^{p}(\mathbb{T}^{d})).

  2. (ii).

    If s=s=\infty, then for any divergence-free field 𝒖L1(0,T;W1,p(𝕋d))\boldsymbol{u}\in L^{1}(0,T;W^{1,p^{\prime}}(\mathbb{T}^{d})) and any initial data ρ0Lp(𝕋d)\rho_{0}\in L^{p}(\mathbb{T}^{d}), there exists a uniqueness solution of (1.1) in the class L(0,T;Lp(𝕋d))L^{\infty}(0,T;L^{p}(\mathbb{T}^{d})).

We identify [0,T][0,T] with an 1-dimensional torus and the time-periodic function ff on [0,T][0,T] means f(t+nT)=f(t)f(t+nT)=f(t) for all nn\in\mathbb{Z}. Theorem 1.1 follows immediately from the following theorem.

Theorem 1.3.

Let d3d\geq 3 and p,q,s,s~[1,)p,q,s,\tilde{s}\in[1,\infty), p,sp^{\prime},s^{\prime} are Hölder conjugate exponents of p,sp,s respectively, satisfying p>1p>1 and (1.3). For any ϵ>0\epsilon>0 and any time-periodic ρ~C([0,T]×𝕋d)\tilde{\rho}\in C^{\infty}([0,T]\times\mathbb{T}^{d}) with constant mean

𝕋dρ~(t,x)𝑑x=𝕋dρ~(0,x)𝑑x for all t[0,T],\fint_{\mathbb{T}^{d}}\tilde{\rho}(t,x)\,dx=\fint_{\mathbb{T}^{d}}\tilde{\rho}(0,x)\,dx\text{ for all }t\in[0,T],

there exists a divergence-free vector field 𝐮\boldsymbol{u} and a density ρ\rho such that the following holds.

  1. (i).

    𝒖Ls~(0,T;W1,q(𝕋d))Ls(0,T;Lp(𝕋d))\boldsymbol{u}\in L^{\tilde{s}}(0,T;W^{1,q}(\mathbb{T}^{d}))\cap L^{s^{\prime}}(0,T;L^{p^{\prime}}(\mathbb{T}^{d})) and ρLs(0,T;Lp(𝕋d))\rho\in L^{s}(0,T;L^{p}(\mathbb{T}^{d})).

  2. (ii).

    ρ(t)\rho(t) is continuous in the distributional sense and for t=0,Tt=0,T, ρ(t)=ρ~(t)\rho(t)=\tilde{\rho}(t).

  3. (iii).

    (ρ,𝒖)(\rho,\boldsymbol{u}) is a weak solution to (1.1) with initial data ρ~(0)\tilde{\rho}(0).

  4. (iv).

    The deviation of LpL^{p} norm is small on average: ρρ~LtsLxpϵ\|\rho-\tilde{\rho}\|_{L^{s}_{t}L^{p}_{x}}\leq\epsilon.

Proof of Theorem 1.1. Let ρ¯C0(𝕋d)\bar{\rho}\in C_{0}^{\infty}(\mathbb{T}^{d}) with ρ¯Lxp=1\|\bar{\rho}\|_{L^{p}_{x}}=1. We take ρ~=χ(t)ρ¯(x)\tilde{\rho}=\chi(t)\bar{\rho}(x) with χC([0,T];[0,1])\chi\in C^{\infty}([0,T];[0,1]) satisfying χ=1\chi=1 if |tT2|T4|t-\frac{T}{2}|\leq\frac{T}{4} and χ=0\chi=0 if |tT2|3T8|t-\frac{T}{2}|\geq\frac{3T}{8}. We apply Theorem 1.3 with ϵ=14(T4)1/s\epsilon=\frac{1}{4}(\frac{T}{4})^{1/s} and obtain (ρ,𝒖)(\rho,\boldsymbol{u}) solving (1.1) with ρ00\rho_{0}\equiv 0. By the choice of ϵ\epsilon, we claim that ρ\rho cannot have a constant LxpL^{p}_{x} norm and obviously ρ0\rho\not\equiv 0, which implies the non-uniqueness (as well as the existence of non-renormalized solution).

Indeed, assume ρ(t)LpC\|\rho(t)\|_{L^{p}}\equiv C for some C>0C>0. On the one hand, due to ρρ~LtsLxp14(T4)1/s\|\rho-\tilde{\rho}\|_{L^{s}_{t}L^{p}_{x}}\leq\frac{1}{4}(\frac{T}{4})^{1/s}, we have

T2|C1|T43T4ρ(t)ρ~(t)Lxp𝑑t(T2)1/sρρ~LtsLxpT8,\frac{T}{2}|C-1|\leq\int_{\frac{T}{4}}^{\frac{3T}{4}}\|\rho(t)-\tilde{\rho}(t)\|_{L^{p}_{x}}\,dt\leq\big{(}\frac{T}{2}\big{)}^{1/s^{\prime}}\|\rho-\tilde{\rho}\|_{L^{s}_{t}L^{p}_{x}}\leq\frac{T}{8},

hence |C1|1/4|C-1|\leq 1/4, which implies C>3/4C>3/4.

On the other hand,

T8(T4)1/sρρ~LtsLxp[0,T8][7T8,T]ρ(t)ρ~(t)Lxp𝑑t=T4C,\frac{T}{8}\geq\big{(}\frac{T}{4}\big{)}^{1/s^{\prime}}\|\rho-\tilde{\rho}\|_{L^{s}_{t}L^{p}_{x}}\geq\int_{[0,\frac{T}{8}]\cup[\frac{7T}{8},T]}\|\rho(t)-\tilde{\rho}(t)\|_{L^{p}_{x}}\,dt=\frac{T}{4}C,

hence C1/2C\leq 1/2, in contradiction with C>3/4C>3/4, we prove the claim. ∎

1.3 Notations

The norms of Lp(𝕋d)L^{p}(\mathbb{T}^{d}), Ls(0,T)L^{s}(0,T), Ls(0,T;Lp(𝕋d))L^{s}(0,T;L^{p}(\mathbb{T}^{d})) will be denoted standardly as Lxp\|\cdot\|_{L^{p}_{x}}, Lts\|\cdot\|_{L^{s}_{t}}, LtsLxp\|\cdot\|_{L^{s}_{t}L^{p}_{x}} or just Lp\|\cdot\|_{L^{p}} when there is no confusion. The norm of Ck([0,T]×𝕋d)C^{k}([0,T]\times\mathbb{T}^{d}) will be denoted as Ck\|\cdot\|_{C^{k}}.

For any fL1(𝕋d)f\in L^{1}(\mathbb{T}^{d}), its spacial mean is 𝕋df𝑑x=𝕋df𝑑x\fint_{\mathbb{T}^{d}}f\,dx=\int_{\mathbb{T}^{d}}f\,dx and denote simply as f\fint f. We denote C0(𝕋d)C_{0}^{\infty}(\mathbb{T}^{d}) as the space of smooth periodic functions with zero mean.

Denote the standard partial differential operators with multiindex 𝒌d{\boldsymbol{k}}\in\mathbb{N}^{d} as 𝒌:=x1k1xdkd\partial^{\boldsymbol{k}}:=\partial_{x_{1}}^{k_{1}}\cdots\partial_{x_{d}}^{k_{d}}. For any fC(𝕋d)f\in C^{\infty}(\mathbb{T}^{d}), the obvious facts are 𝒌(f(σ))Lp=σ|𝒌|𝒌fLp\|\partial^{\boldsymbol{k}}(f(\sigma\cdot))\|_{L^{p}}=\sigma^{|\boldsymbol{k}|}\|\partial^{\boldsymbol{k}}f\|_{L^{p}} for any p[1,)\forall p\in[1,\infty), σ+\forall\sigma\in\mathbb{N}_{+} and of course 𝒌fC0(𝕋d)\partial^{\boldsymbol{k}}f\in C_{0}^{\infty}(\mathbb{T}^{d}) as long as 𝒌0{\boldsymbol{k}}\neq 0.

aba\lesssim b will be denoted as aCba\leq Cb with some inessential constant CC. If the constant depends on some quantities, for instance rr, it will be denoted as CrC_{r}, and arba\lesssim_{r}b means aCrba\leq C_{r}b.

CC_{*} represents a positive constant that might depend on the old solution (ρ,𝒖,𝑹)(\rho,\boldsymbol{u},\boldsymbol{R}) and the constant NN but never on ν,δ\nu,\delta given in Proposition 2.1. CC_{*} may change from line to line.

2 Main Proposition and the Proof of Theorem 1.3

Without loss of generality, in the rest of the paper, we assume T=1T=1 and identify the time interval [0,1][0,1] with an 1-dimensional torus.

We follow the framework of [20] (see [40] for the earliest version) to obtain space-time periodic approximate solutions (ρ,𝒖,𝑹)(\rho,\boldsymbol{u},\boldsymbol{R}) to the transport equation by solving the continuity-defect equation

{tρ+div(ρ𝒖)=div𝑹,div𝒖=0,\left\{\begin{split}&\partial_{t}\rho+\operatorname{div}(\rho\boldsymbol{u})=\operatorname{div}\boldsymbol{R},\\ &\operatorname{div}\boldsymbol{u}=0,\end{split}\right. (2.1)

where 𝑹:[0,1]×𝕋dd\boldsymbol{R}\colon[0,1]\times\mathbb{T}^{d}\to\mathbb{R}^{d} is called the defect field.

For any 0<r<10<r<1, denote Ir:=[r,1r]I_{r}:=[r,1-r]. To build a iteration scheme for proving Theorem 1.3, we will construct the small perturbations on Ir×𝕋dI_{r}\times\mathbb{T}^{d} of (ρ,𝒖)(\rho,\boldsymbol{u}) to obtain a new solution (ρ1,𝒖1,𝑹1)(\rho^{1},\boldsymbol{u}^{1},\boldsymbol{R}^{1}) such that the new defect field 𝑹1\boldsymbol{R}^{1} has small Lt,x1L^{1}_{t,x} norm. This is the following main proposition of the paper.

Proposition 2.1.

Let d3d\geq 3 and p,q,s,s~[1,)p,q,s,\tilde{s}\in[1,\infty), p,sp^{\prime},s^{\prime} are Hölder conjugates of p,sp,s respectively, satisfying p>1p>1 and (1.3). There exist a universal constant M>0M>0 and a large integer NN\in\mathbb{N} such that the following holds.

Suppose (ρ,𝐮,𝐑)(\rho,\boldsymbol{u},\boldsymbol{R}) is a smooth solution of (2.1) on [0,1][0,1]. Then for any δ,ν>0\delta,\nu>0, there exists another smooth solution (ρ1,𝐮1,𝐑1)(\rho^{1},\boldsymbol{u}^{1},\boldsymbol{R}^{1}) of (2.1) on [0,1][0,1] which fulfills the estimates

ρ1ρLtsLxp\displaystyle\|\rho^{1}-\rho\|_{L^{s}_{t}L^{p}_{x}} νM𝑹Lt,x11/p,\displaystyle\leq\nu M\|\boldsymbol{R}\|^{1/p}_{L^{1}_{t,x}},
𝒖1𝒖LtsLxp\displaystyle\|\boldsymbol{u}^{1}-\boldsymbol{u}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} ν1M𝑹Lt,x11/p,\displaystyle\leq\nu^{-1}M\|\boldsymbol{R}\|^{1/p^{\prime}}_{L^{1}_{t,x}},
𝒖1𝒖Lts~Wx1,q\displaystyle\|\boldsymbol{u}^{1}-\boldsymbol{u}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} δ,𝑹1Lt,x1δ.\displaystyle\leq\delta,\quad\|\boldsymbol{R}^{1}\|_{L^{1}_{t,x}}\leq\delta.

In addition, the density perturbation ρ1ρ\rho^{1}-\rho has zero spacial mean and satisfies

|𝕋d(ρ1ρ)(t,x)ϕ(x)𝑑x|\displaystyle\Big{|}\int_{\mathbb{T}^{d}}(\rho^{1}-\rho)(t,x)\phi(x)\,dx\Big{|} δϕCNt[0,1],ϕC(𝕋d),\displaystyle\leq\delta\|\phi\|_{C^{N}}\quad\forall t\in[0,1],\,\forall\phi\in C^{\infty}(\mathbb{T}^{d}), (2.2)
suppt(ρ1ρ)\displaystyle\operatorname{supp}_{t}(\rho^{1}-\rho) Ir for some r>0.\displaystyle\in I_{r}\,\text{ for some }r>0. (2.3)

Proof of Theorem 1.3. Assume T=1T=1. We will construct a sequence (ρn,𝒖n,𝑹n)(\rho^{n},\boldsymbol{u}^{n},\boldsymbol{R}^{n}) of solutions to (2.1). For n=1n=1, we set

(ρ1,𝒖1,𝑹1):=(ρ~,0,(tρ~)).(\rho^{1},\boldsymbol{u}^{1},\boldsymbol{R}^{1}):=(\tilde{\rho},0,\mathcal{R}(\partial_{t}\tilde{\rho})).

Notice the constant mean assumption on ρ~\tilde{\rho} implies zero mean of tρ~\partial_{t}\tilde{\rho}, hence (ρ1,𝒖1,𝑹1)(\rho^{1},\boldsymbol{u}^{1},\boldsymbol{R}^{1}) solves (2.1).

Next we apply Proposition 2.1 inductively to obtain (ρn,𝒖n,𝑹n)(\rho^{n},\boldsymbol{u}^{n},\boldsymbol{R}^{n}) for n=2,3n=2,3\cdots as follows. Set ν1:=ϵ(2M𝑹1Lt,x11/p)1\nu_{1}:=\epsilon(2M\|\boldsymbol{R}^{1}\|^{1/p}_{L^{1}_{t,x}})^{-1} and choose sequence {(δn,νn)}n=2(0,)2\{(\delta_{n},\nu_{n})\}_{n=2}^{\infty}\subset(0,\infty)^{2} such that nδn1/2=1\sum_{n}\delta_{n}^{1/2}=1, δn1/pνn=ϵδn1/2/2M\delta_{n}^{1/p}\nu_{n}=\epsilon\delta^{1/2}_{n}/2M. Observe that δn1/p/νn=2Mδn1/2/ϵ\delta_{n}^{1/p^{\prime}}/\nu_{n}=2M\delta^{1/2}_{n}/\epsilon.

Given (ρn,𝒖n,𝑹n)(\rho^{n},\boldsymbol{u}^{n},\boldsymbol{R}^{n}), we apply Proposition 2.1 with parameters ν=νn\nu=\nu_{n} and δ=δn+1\delta=\delta_{n+1} to obtain a new triple (ρn+1,𝒖n+1,𝑹n+1)(\rho^{n+1},\boldsymbol{u}^{n+1},\boldsymbol{R}^{n+1}) which verifies

ρn+1ρnLtsLxp\displaystyle\|\rho^{n+1}-\rho^{n}\|_{L^{s}_{t}L^{p}_{x}} νnM𝑹nLt,x11/p,\displaystyle\leq\nu_{n}M\|\boldsymbol{R}^{n}\|^{1/p}_{L^{1}_{t,x}},
𝒖n+1𝒖nLtsLxp\displaystyle\|\boldsymbol{u}^{n+1}-\boldsymbol{u}^{n}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} νn1M𝑹nLt,x11/p,\displaystyle\leq\nu_{n}^{-1}M\|\boldsymbol{R}^{n}\|^{1/p^{\prime}}_{L^{1}_{t,x}},
𝒖n+1𝒖nLts~Wx1,q\displaystyle\|\boldsymbol{u}^{n+1}-\boldsymbol{u}^{n}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} δn+1,𝑹n+1Lt,x1δn+1,\displaystyle\leq\delta_{n+1},\quad\|\boldsymbol{R}^{n+1}\|_{L^{1}_{t,x}}\leq\delta_{n+1},
|𝕋d(ρn+1ρn)(t,x)ϕ(x)𝑑x|\displaystyle\Big{|}\int_{\mathbb{T}^{d}}(\rho^{n+1}-\rho^{n})(t,x)\phi(x)\,dx\Big{|} δn+1ϕCNt[0,1],ϕC(𝕋d).\displaystyle\leq\delta_{n+1}\|\phi\|_{C^{N}}\quad\forall t\in[0,1],\,\forall\phi\in C^{\infty}(\mathbb{T}^{d}).

When n2n\geq 2, we have

ρn+1ρnLtsLxp\displaystyle\|\rho^{n+1}-\rho^{n}\|_{L^{s}_{t}L^{p}_{x}} ϵδn1/22,\displaystyle\leq\frac{\epsilon\delta^{1/2}_{n}}{2},
𝒖n+1𝒖nLtsLxp\displaystyle\|\boldsymbol{u}^{n+1}-\boldsymbol{u}^{n}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} 2M2δn1/2ϵ.\displaystyle\leq\frac{2M^{2}\delta^{1/2}_{n}}{\epsilon}.

Clearly there are functions ρLtsLxp\rho\in L^{s}_{t}L^{p}_{x} and 𝒖LtsLxpLts~Wx1,q\boldsymbol{u}\in L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}\cap L^{\tilde{s}}_{t}W^{1,q}_{x} such that ρnρ\rho^{n}\to\rho in LtsLxpL^{s}_{t}L^{p}_{x} and 𝒖n𝒖\boldsymbol{u}^{n}\to\boldsymbol{u} in LtsLxpLts~Wx1,qL^{s^{\prime}}_{t}L^{p^{\prime}}_{x}\cap L^{\tilde{s}}_{t}W^{1,q}_{x}. Moreover, we have ρn𝒖nρ𝒖\rho^{n}\boldsymbol{u}^{n}\to\rho\boldsymbol{u} and 𝑹n0\boldsymbol{R}^{n}\to 0 in Lt,x1L^{1}_{t,x}, and 𝕋dρn(,x)ϕ(x)𝑑x𝕋dρ(,x)ϕ(x)𝑑x\int_{\mathbb{T}^{d}}\rho^{n}(\cdot,x)\phi(x)\,dx\to\int_{\mathbb{T}^{d}}\rho(\cdot,x)\phi(x)\,dx in LtL^{\infty}_{t}. Combine the fact suppt(ρn+1ρn)Irn\operatorname{supp}_{t}(\rho^{n+1}-\rho^{n})\in I_{r_{n}} for some rn>0r_{n}>0, we obtain the temporal continuity of ρ\rho in the distributional sense and for t=0,1t=0,1, ρ(t)=ρ~(t)\rho(t)=\tilde{\rho}(t), furthermore (ρ,𝒖)(\rho,\boldsymbol{u}) is a weak solution to (1.1) with initial data ρ~(0)\tilde{\rho}(0).

Finally, thanks to the choice of {δn},{νn}\{\delta_{n}\},\{\nu_{n}\}, we have

ρρ~LtsLxpρ2ρ1LtsLxp+n=2ρn+1ρnLtsLxpϵ2+ϵ2n=2δn1/2=ϵ.\|\rho-\tilde{\rho}\|_{L^{s}_{t}L^{p}_{x}}\leq\|\rho^{2}-\rho^{1}\|_{L^{s}_{t}L^{p}_{x}}+\sum_{n=2}^{\infty}\|\rho^{n+1}-\rho^{n}\|_{L^{s}_{t}L^{p}_{x}}\leq\frac{\epsilon}{2}+\frac{\epsilon}{2}\sum_{n=2}^{\infty}\delta^{1/2}_{n}=\epsilon.

3 Technical tools

In this section, we collect the technical tools prepared in [40, 20] for the proof of the main proposition (Proposition 2.1). We refer to [40, 39, 20] for more details.

3.1 Anti-divergence operators

By the classical Fourier analysis, for any fC(𝕋d)f\in C^{\infty}(\mathbb{T}^{d}), a unique solution in C0(𝕋d)C_{0}^{\infty}(\mathbb{T}^{d}) of the Poisson equation

Δu=ff\Delta u=f-\fint f

is given by u(x)=kd{0}(4π|k|2)1e2πikxf^(k)u(x)=\sum_{k\in\mathbb{Z}^{d}\setminus\{0\}}(4\pi|k|^{2})^{-1}e^{2\pi ik\cdot x}\hat{f}(k). Hence the standard anti-divergence operator :C(𝕋d)C0(𝕋d;d)\mathcal{R}\colon C^{\infty}(\mathbb{T}^{d})\to C^{\infty}_{0}(\mathbb{T}^{d};\mathbb{R}^{d}) can be defined as

f:=Δ1f,\mathcal{R}f:=\Delta^{-1}\nabla f,

which satisfies

div(f)=ff.\operatorname{div}(\mathcal{R}f)=f-\fint f.

Obviously, for every σ+\sigma\in\mathbb{N}_{+} and fC0(𝕋d)f\in C_{0}^{\infty}(\mathbb{T}^{d}) there holds

[f(σ)](x)=σ1(f)(σx).\mathcal{R}[f(\sigma\cdot)](x)=\sigma^{-1}(\mathcal{R}f)(\sigma x).

Further, the first order bilinear anti-divergence operator :C(𝕋d)×C(𝕋d)C(𝕋d;d)\mathcal{B}\colon C^{\infty}(\mathbb{T}^{d})\times C^{\infty}(\mathbb{T}^{d})\to C^{\infty}(\mathbb{T}^{d};\mathbb{R}^{d}) can be defined as

(a,f):=af(af),\mathcal{B}(a,f):=a\mathcal{R}f-\mathcal{R}(\nabla a\cdot\mathcal{R}f),

which satisfies

div((a,f))=afaf provided that fC0(𝕋d).\operatorname{div}(\mathcal{B}(a,f))=af-\fint af\text{ provided that }f\in C^{\infty}_{0}(\mathbb{T}^{d}).

The bilinear anti-divergence operator \mathcal{B} has the additional advantage of gaining derivative from ff when ff has zero mean and a very small period. See also higher order variants in [39].

Remark 3.1.

Notice the definitions of ,\mathcal{R},\mathcal{B} in [39] are slightly different from the definitions in this paper, which actually are defined as

f=Δ1f,(a,f)=af(afaf).\mathcal{R}f=\nabla\Delta^{-1}f,\quad\mathcal{B}(a,f)=a\mathcal{R}f-\mathcal{R}(\nabla a\cdot\mathcal{R}f-\fint af).

In this case, ff must be mean zero.

Lemma 3.1 ([20, Lemma 2.1]).

Let d2d\geq 2. For every mm\in\mathbb{N} and r[1,]r\in[1,\infty], the anti-divergence operator \mathcal{R} is bounded on Wm,r(𝕋d)W^{m,r}(\mathbb{T}^{d}):

fWm,rfWm,r.\|\mathcal{R}f\|_{W^{m,r}}\lesssim\|f\|_{W^{m,r}}. (3.1)

Moreover for all fC(𝕋d)f\in C^{\infty}(\mathbb{T}^{d}) and 1<r<1<r<\infty, the Calderón-Zygmund inequality holds:

(divf)LrfLr.\|\mathcal{R}(\operatorname{div}f)\|_{L^{r}}\lesssim\|f\|_{L^{r}}. (3.2)
Lemma 3.2 ([20, Lemma 2.2]).

Let d2d\geq 2 and r[1,]r\in[1,\infty]. Then for any a,fC(𝕋d)a,f\in C^{\infty}(\mathbb{T}^{d}):

(a,f)LraC1fLr.\|\mathcal{B}(a,f)\|_{L^{r}}\lesssim\|a\|_{C^{1}}\|\mathcal{R}f\|_{L^{r}}.
Lemma 3.3 ([20, Lemma 2.4]).

Let σ\sigma\in\mathbb{N} and a,fC(𝕋d)a,f\in C^{\infty}(\mathbb{T}^{d}). Then for all r[1,]r\in[1,\infty],

|a()f(σ)LraLrfLr|Crσ1/raC1fLr.\Big{|}\|a(\cdot)f(\sigma\cdot)\|_{L^{r}}-\|a\|_{L^{r}}\|f\|_{L^{r}}\Big{|}\leq C_{r}\sigma^{-1/r}\|a\|_{C^{1}}\|f\|_{L^{r}}.
Remark 3.2.

Lemma 3.3 is called the improved Hölder inequality, which is established in [40, Lemma 2.1], inspired by [16, Lemma 3.7].

Lemma 3.4 ([20, Lemma 2.5]).

Let σ\sigma\in\mathbb{N}, aC(𝕋d)a\in C^{\infty}(\mathbb{T}^{d}) and fC0(𝕋d)f\in C_{0}^{\infty}(\mathbb{T}^{d}). Then for all even n0n\geq 0

|𝕋da(x)f(σx)𝑑x|nσnaCnfL2.\Big{|}\fint_{\mathbb{T}^{d}}a(x)f(\sigma x)\,dx\Big{|}\lesssim_{n}\sigma^{-n}\|a\|_{C^{n}}\|f\|_{L^{2}}.
Remark 3.3.

Lemma 3.4 is used to estimate the space mean of the perturbations and obtain that the density perturbations converges to 0 in the distributional sense in space, uniformly in time, see (2.2).

3.2 Mikado flows

Now we define the Mikado flow (Φjμ,𝑾jμ)(\Phi_{j}^{\mu},\boldsymbol{W}_{j}^{\mu}) given in [20], which are a family of periodic stationary solutions to the transport equation (1.1). Where Φjμ\Phi_{j}^{\mu} is the Mikado density, 𝑾jμ\boldsymbol{W}_{j}^{\mu} is the Mikado filed.

Let d3d\geq 3. Fix 𝛀Cc(d1;d1)\boldsymbol{\Omega}\in C_{c}^{\infty}(\mathbb{R}^{d-1};\mathbb{R}^{d-1}) satisfying

supp𝛀(0,1)d1,d1(div𝛀)2𝑑x=1.\operatorname{supp}\boldsymbol{\Omega}\subset(0,1)^{d-1},\quad\int_{\mathbb{R}^{d-1}}(\operatorname{div}\boldsymbol{\Omega})^{2}\,dx=1.

Denote ϕ=div𝛀\phi=\operatorname{div}\boldsymbol{\Omega} and 𝛀μ(x)=𝛀(μx)\boldsymbol{\Omega}^{\mu}(x)=\boldsymbol{\Omega}(\mu x), ϕμ(x)=ϕ(μx)\phi^{\mu}(x)=\phi(\mu x). We can define a family of non-periodic stationary solutions to (1.1) as

Φ~jμ(x)\displaystyle\tilde{\Phi}_{j}^{\mu}(x) =μd1pϕμ(x1,,xj1,xj+1,,xd),\displaystyle=\mu^{\frac{d-1}{p}}\phi^{\mu}(x_{1},\dots,x_{j-1},x_{j+1},\dots,x_{d}),
𝑾~jμ(x)\displaystyle\tilde{\boldsymbol{W}}_{j}^{\mu}(x) =μd1pϕμ(x1,,xj1,xj+1,,xd)𝒆j.\displaystyle=\mu^{\frac{d-1}{p^{\prime}}}\phi^{\mu}(x_{1},\dots,x_{j-1},x_{j+1},\dots,x_{d})\boldsymbol{e}_{j}.

The potential is defined as

𝛀~jμ(x)=μ1+d1p𝛀μ(x1,,xj1,xj+1,,xd).\tilde{\boldsymbol{\Omega}}_{j}^{\mu}(x)=\mu^{-1+\frac{d-1}{p}}\boldsymbol{\Omega}^{\mu}(x_{1},\dots,x_{j-1},x_{j+1},\dots,x_{d}).

The periodic solutions (Φjμ,𝑾jμ)(\Phi_{j}^{\mu},\boldsymbol{W}_{j}^{\mu}) with mutually disjoint supports can be constructed by translation and periodization of the non-periodic flow (Φ~jμ,𝑾~jμ)(\tilde{\Phi}_{j}^{\mu},\tilde{\boldsymbol{W}}_{j}^{\mu}). This is based on the geometrical fact that along any two directions in d\mathbb{R}^{d} for d3d\geq 3, there exist two disjoint lines.

For instance, notice {suppΦ~jμ}j=1d\{\operatorname{supp}\tilde{\Phi}_{j}^{\mu}\}_{j=1}^{d} are dd cylinders with side length 1/μ1/\mu lying at xjx_{j}-axis respectively. When μ8d\mu\geq 8d, one can move the jj-th cylinder with length 14d\frac{1}{4d} along a direction 𝒑j{𝒆j}j=1d\boldsymbol{p}_{j}\in\{\boldsymbol{e}_{j}\}_{j=1}^{d}, such that all cylinders are mutually disjoint and keep lying in j=1d[(0,1)d+𝒆j]\cup_{j=1}^{d}[(0,1)^{d}+\mathbb{R}\boldsymbol{e}_{j}]. By means of the Possion summation, we define periodic Mikado flow as

Φjμ(x)\displaystyle\Phi_{j}^{\mu}(x) =𝒏d,𝒏j=0Φ~jμ(x14d𝒑j+𝒏),\displaystyle=\sum_{\boldsymbol{n}\in\mathbb{Z}^{d},\boldsymbol{n}_{j}=0}\tilde{\Phi}_{j}^{\mu}\Big{(}x-\frac{1}{4d}\boldsymbol{p}_{j}+\boldsymbol{n}\Big{)},
𝑾jμ(x)\displaystyle\boldsymbol{W}_{j}^{\mu}(x) =𝒏d,𝒏j=0𝑾~jμ(x14d𝒑j+𝒏),\displaystyle=\sum_{\boldsymbol{n}\in\mathbb{Z}^{d},\boldsymbol{n}_{j}=0}\tilde{\boldsymbol{W}}_{j}^{\mu}\Big{(}x-\frac{1}{4d}\boldsymbol{p}_{j}+\boldsymbol{n}\Big{)},

and the periodic potential is defined as

𝛀jμ(x)=𝒏d,𝒏j=0𝛀~jμ(x14d𝒑j+𝒏).\boldsymbol{\Omega}_{j}^{\mu}(x)=\sum_{\boldsymbol{n}\in\mathbb{Z}^{d},\boldsymbol{n}_{j}=0}\tilde{\boldsymbol{\Omega}}_{j}^{\mu}\Big{(}x-\frac{1}{4d}\boldsymbol{p}_{j}+\boldsymbol{n}\Big{)}.

For the Mikado flow, we have the following proposition.

Proposition 3.5 ([20, Proposition 4.3, Theorem 4.4]).

Let d3d\geq 3 and μ8d\mu\geq 8d. Then the periodic functions Φjμ,𝐖jμC0(𝕋d)\Phi_{j}^{\mu},\boldsymbol{W}_{j}^{\mu}\in C^{\infty}_{0}(\mathbb{T}^{d}), 𝛀jμC(𝕋d)\boldsymbol{\Omega}_{j}^{\mu}\in C^{\infty}(\mathbb{T}^{d}) verify the following.

  1. (i).

    For any 1r1\leq r\leq\infty, mm\in\mathbb{N},

    mΦjμLrmμm+d1pd1r,m𝛀jμLrmμm1+d1pd1r,m𝑾jμLrmμm+d1pd1r.\begin{split}\|\nabla^{m}\Phi_{j}^{\mu}\|_{L^{r}}&\lesssim_{m}\mu^{m+\frac{d-1}{p}-\frac{d-1}{r}},\\ \|\nabla^{m}\boldsymbol{\Omega}_{j}^{\mu}\|_{L^{r}}&\lesssim_{m}\mu^{m-1+\frac{d-1}{p}-\frac{d-1}{r}},\\ \|\nabla^{m}\boldsymbol{W}_{j}^{\mu}\|_{L^{r}}&\lesssim_{m}\mu^{m+\frac{d-1}{p^{\prime}}-\frac{d-1}{r}}.\end{split} (3.3)
  2. (ii).

    Φjμ,𝑾jμ,𝛀jμ\Phi_{j}^{\mu},\boldsymbol{W}_{j}^{\mu},\boldsymbol{\Omega}_{j}^{\mu} solve

    {div(Φjμ𝑾jμ)=0,div𝑾jμ=0,div𝛀jμ=Φjμ.\left\{\begin{split}&\operatorname{div}(\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu})=0,\\ &\operatorname{div}\boldsymbol{W}_{j}^{\mu}=0,\quad\operatorname{div}\boldsymbol{\Omega}_{j}^{\mu}=\Phi_{j}^{\mu}.\end{split}\right. (3.4)
  3. (iii).

    There hold

    𝕋dΦjμ𝑾jμ=𝒆j for all 1jd;Φjμ𝑾kμ=0 if jk,\int_{\mathbb{T}^{d}}\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}=\boldsymbol{e}_{j}\text{ for all }1\leq j\leq d;\quad\Phi_{j}^{\mu}\boldsymbol{W}_{k}^{\mu}=0\text{ if }j\neq k, (3.5)

where 𝐞j\boldsymbol{e}_{j} is the jj-th standard Euclidean basis.

Remark 3.4.

The concept of Mikado flow was introduced in [27] firstly and then adapted in [40, 41, 39, 14, 20] for the non-uniqueness results of the transport equation. Notice the construction of stationary Mikado flow requires the dimension dd is not less than three. An alternative is the space-time Mikado flow introduced in [39] (see also [14]), which can be constructed in 𝕋2\mathbb{T}^{2}. However, the space-time flow brings new difficulty when applying the temporal intermittency.

3.3 Intermittent functions in time

In this subsection, we define the intermittent oscillatory functions g¯κ\bar{g}_{\kappa} and g~κ\tilde{g}_{\kappa}. Take gCc()g\in C_{c}^{\infty}(\mathbb{R}) satisfying suppg(0,1)\operatorname{supp}g\subset(0,1) and

[0,1]g2𝑑t=1.\int_{[0,1]}g^{2}\,dt=1.

For κ1\kappa\geq 1, define

gκ(t):=ng(κt+κn),g¯κ(t):=κ1/sgκ(t),g~κ(t):=κ1/sgκ(t).g_{\kappa}(t):=\sum_{n\in\mathbb{Z}}g(\kappa t+\kappa n),\quad\bar{g}_{\kappa}(t):=\kappa^{1/s^{\prime}}g_{\kappa}(t),\quad\tilde{g}_{\kappa}(t):=\kappa^{1/s}g_{\kappa}(t).

In this case, we have that g¯κ,g~κC([0,1])\bar{g}_{\kappa},\tilde{g}_{\kappa}\in C^{\infty}([0,1]) be 1-periodic functions and the following facts (similar to Proposition 3.5) hold

[0,1]g¯κg~κ𝑑t=1,tmg¯κLtrκm+1s1r,tmg~κLtrκm+1s1r.\int_{[0,1]}\bar{g}_{\kappa}\tilde{g}_{\kappa}\,dt=1,\quad\|\partial_{t}^{m}\bar{g}_{\kappa}\|_{L^{r}_{t}}\lesssim\kappa^{m+\frac{1}{s^{\prime}}-\frac{1}{r}},\quad\|\partial_{t}^{m}\tilde{g}_{\kappa}\|_{L^{r}_{t}}\lesssim\kappa^{m+\frac{1}{s}-\frac{1}{r}}. (3.6)

Define hκ(t):=0t(g¯κg~κ1)𝑑τh_{\kappa}(t):=\int_{0}^{t}(\bar{g}_{\kappa}\tilde{g}_{\kappa}-1)\,d\tau, which obviously satisfies

thκ=g¯κg~κ1,hκLt1.\partial_{t}h_{\kappa}=\bar{g}_{\kappa}\tilde{g}_{\kappa}-1,\quad\|h_{\kappa}\|_{L^{\infty}_{t}}\leq 1. (3.7)

We write 𝑹=jRj𝒆j\boldsymbol{R}=\sum_{j}R_{j}\boldsymbol{e}_{j}, where 𝒆j\boldsymbol{e}_{j} is the jj-th standard Euclidean basis.

Recall the notation Ir=[r,1r](0,1)I_{r}=[r,1-r]\subset(0,1) for 0<r<10<r<1. Define the smooth cutoff functions χjCc(×𝕋d)\chi_{j}\in C_{c}^{\infty}(\mathbb{R}\times\mathbb{T}^{d}) satisfying

0χj1,χj(t,x)={0, if |Rj|δ8d or tIr/2,1, if |Rj|δ4d and tIr.0\leq\chi_{j}\leq 1,\quad\chi_{j}(t,x)=\left\{\begin{split}0,&\text{ if }|R_{j}|\leq\frac{\delta}{8d}\text{ or }t\notin I_{r/2},\\ 1,&\text{ if }|R_{j}|\geq\frac{\delta}{4d}\text{ and }t\in I_{r}.\end{split}\right. (3.8)

Where r>0r>0 is fixed sufficiently small enough such that

𝑹Lt,xδ8rd.\|\boldsymbol{R}\|_{L^{\infty}_{t,x}}\leq\frac{\delta}{8rd}. (3.9)

Notice suppχjIr/2(0,1)\operatorname{supp}\chi_{j}\subset I_{r/2}\subset(0,1). By a slight abuse of notation, χj\chi_{j} denote the 1-periodic extension in time of χj\chi_{j}. Define R~j:=χjRj\widetilde{R}_{j}:=\chi_{j}R_{j}.

4 Proof of Proposition 2.1

In this section, we follow the lines in [20] to construct the perturbations and defect field, and then finish the proof of Proposition 2.1. In particular, we set that the concentration in time is stronger than in space, the oscillation in time is weaker than in space, see Sec. 4.3.

4.1 Constructing perturbations

We first define the principle part of the perturbations by the Mikado flows given in Proposition 3.5. Let

θp(t,x):=g~κ(λt)jaj(t,x)Φjμ(σx),𝒘p(t,x):=g¯κ(λt)jbj(t,x)𝑾jμ(σx),\begin{split}\theta_{p}(t,x)&:=\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}a_{j}(t,x)\Phi_{j}^{\mu}(\sigma x),\\ \boldsymbol{w}_{p}(t,x)&:=\bar{g}_{\kappa}(\lambda t)\sum\nolimits_{j}b_{j}(t,x)\boldsymbol{W}_{j}^{\mu}(\sigma x),\end{split} (4.1)

where

aj(t,x):=ν(R~j(t)L1R~jLt,x1)1s1psign(Rj)χj|Rj|1p,\displaystyle a_{j}(t,x):=\nu\Big{(}\frac{\|\widetilde{R}_{j}(t)\|_{L^{1}}}{\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}}\Big{)}^{\frac{1}{s}-\frac{1}{p}}\operatorname{sign}(-R_{j})\chi_{j}|R_{j}|^{\frac{1}{p}},
bj(t,x):=ν1(R~j(t)L1R~jLt,x1)1p1sχj|Rj|1p.\displaystyle b_{j}(t,x):=\nu^{-1}\Big{(}\frac{\|\widetilde{R}_{j}(t)\|_{L^{1}}}{\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}}\Big{)}^{\frac{1}{p}-\frac{1}{s}}\chi_{j}|R_{j}|^{\frac{1}{p^{\prime}}}.

Notice ajbj=χj2Rja_{j}b_{j}=-\chi_{j}^{2}R_{j}. By [20, Lemma 7.1], we have

aj,bjC([0,1]×𝕋d),R~j(t)L1C([0,1]),a_{j},b_{j}\in C^{\infty}([0,1]\times\mathbb{T}^{d}),\quad\|\widetilde{R}_{j}(t)\|_{L^{1}}\in C^{\infty}([0,1]),

and the following estimates hold true:

aj(t)LpνR~jLt,x11p1sR~j(t)L11s,bj(t)Lpν1R~jLt,x11s1pR~j(t)L11s.\begin{split}&\|a_{j}(t)\|_{L^{p}}\leq\nu\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{p}-\frac{1}{s}}\|\widetilde{R}_{j}(t)\|_{L^{1}}^{\frac{1}{s}},\\ &\|b_{j}(t)\|_{L^{p^{\prime}}}\leq\nu^{-1}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{s}-\frac{1}{p}}\|\widetilde{R}_{j}(t)\|_{L^{1}}^{\frac{1}{s^{\prime}}}.\end{split} (4.2)

Moreover for any kk\in\mathbb{N}, there exists a constant CC_{*} such that

ajCkCν,bjCkCν1.\|a_{j}\|_{C^{k}}\leq C_{*}\nu,\quad\|b_{j}\|_{C^{k}}\leq C_{*}\nu^{-1}. (4.3)

Notice θp\theta_{p} is not mean zero and 𝒘p\boldsymbol{w}_{p} is not divergence-free. To make sure the zero mean of ρ1\rho^{1} and divergence-free 𝒖1\boldsymbol{u}^{1}, we need the corrections of the perturbations. The correctors are defined by

θc(t)\displaystyle\theta_{c}(t) :=𝕋dθp(t,x)𝑑x,\displaystyle:=-\fint_{\mathbb{T}^{d}}\theta_{p}(t,x)\,dx,
𝒘c(t,x)\displaystyle\boldsymbol{w}_{c}(t,x) :=g¯κ(λt)j(jbj,𝑾jμ(σx)𝒆j).\displaystyle:=-\bar{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\mathcal{B}(\partial_{j}b_{j},\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}).

Notice by Proposition 3.5, 𝑾jμ\boldsymbol{W}_{j}^{\mu} has zero mean, we have

div(jbj,𝑾jμ(σx)𝒆j)\displaystyle\operatorname{div}\mathcal{B}(\partial_{j}b_{j},\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}) =jbj𝑾jμ(σx)𝒆jjbj𝑾jμ(σx)𝒆j\displaystyle=\partial_{j}b_{j}\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}-\fint\partial_{j}b_{j}\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}
=div(bj𝑾jμ(σx)),\displaystyle=\operatorname{div}(b_{j}\boldsymbol{W}_{j}^{\mu}(\sigma x)),

hence

div𝒘c(t,x)=g¯κ(λt)jdiv(bj𝑾jμ(σx))=div𝒘p(t,x).\operatorname{div}\boldsymbol{w}_{c}(t,x)=-\bar{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\operatorname{div}(b_{j}\boldsymbol{W}_{j}^{\mu}(\sigma x))=-\operatorname{div}\boldsymbol{w}_{p}(t,x).

Finally, to take advantage of the temporal oscillations, we define the temporal oscillator

θo(t,x):=λ1hκ(λt)divjχj2Rj𝒆j.\theta_{o}(t,x):=\lambda^{-1}h_{\kappa}(\lambda t)\operatorname{div}\sum\nolimits_{j}\chi_{j}^{2}R_{j}\boldsymbol{e}_{j}.

Notice by definition, θo\theta_{o} has zero mean.

Now we are able to define the perturbations by

θ:=θp+θc+θo,𝒘:=𝒘p+𝒘c,\theta:=\theta_{p}+\theta_{c}+\theta_{o},\quad\boldsymbol{w}:=\boldsymbol{w}_{p}+\boldsymbol{w}_{c}, (4.4)

and ρ1,𝒖1\rho^{1},\boldsymbol{u}^{1} are defined by

ρ1:=ρ+θ,𝒖1:=𝒖+𝒘.\rho^{1}:=\rho+\theta,\quad\boldsymbol{u}^{1}:=\boldsymbol{u}+\boldsymbol{w}. (4.5)

4.2 Constructing the defect field

Now we define the new defect field 𝑹1\boldsymbol{R}^{1} satisfying the continuity-defect equation

tρ1+𝒖1ρ1=div𝑹1.\partial_{t}\rho^{1}+\boldsymbol{u}^{1}\cdot\nabla\rho^{1}=\operatorname{div}\boldsymbol{R}^{1}.

We split 𝑹1\boldsymbol{R}^{1} into four parts

𝑹1:=𝑹lin+𝑹cor+𝑹tem+𝑹osc,\boldsymbol{R}^{1}:=\boldsymbol{R}_{\rm lin}+\boldsymbol{R}_{\rm cor}+\boldsymbol{R}_{\rm tem}+\boldsymbol{R}_{\rm osc}, (4.6)

satisfying

t(θp+θc)\displaystyle\partial_{t}(\theta_{p}+\theta_{c}) =div𝑹tem,\displaystyle=\operatorname{div}\boldsymbol{R}_{\rm tem},
tθo+div(θp𝒘p+𝑹)\displaystyle\partial_{t}\theta_{o}+\operatorname{div}(\theta_{p}\boldsymbol{w}_{p}+\boldsymbol{R}) =div𝑹osc,\displaystyle=\operatorname{div}\boldsymbol{R}_{\rm osc},
div(θ𝒖+ρ𝒘)\displaystyle\operatorname{div}(\theta\boldsymbol{u}+\rho\boldsymbol{w}) =div𝑹lin,\displaystyle=\operatorname{div}\boldsymbol{R}_{\rm lin},
div(θ𝒘c)+div(θo𝒘p+θc𝒘p)\displaystyle\operatorname{div}(\theta\boldsymbol{w}_{c})+\operatorname{div}(\theta_{o}\boldsymbol{w}_{p}+\theta_{c}\boldsymbol{w}_{p}) =div𝑹cor.\displaystyle=\operatorname{div}\boldsymbol{R}_{\rm cor}.

Obviously, 𝑹lin,𝑹cor\boldsymbol{R}_{\rm lin},\boldsymbol{R}_{\rm cor} can be defined by

𝑹lin\displaystyle\boldsymbol{R}_{\rm lin} :=θ𝒖+ρ𝒘,\displaystyle:=\theta\boldsymbol{u}+\rho\boldsymbol{w},
𝑹cor\displaystyle\boldsymbol{R}_{\rm cor} :=θ𝒘c+(θo+θc)𝒘p.\displaystyle:=\theta\boldsymbol{w}_{c}+(\theta_{o}+\theta_{c})\boldsymbol{w}_{p}.

Since

t(θp+θc)=t{g~κ(λt)j(aj(t,x)Φjμ(σx)𝕋daj(t,x)Φjμ(σx)𝑑x)},\partial_{t}(\theta_{p}+\theta_{c})=\partial_{t}\Big{\{}\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\Big{(}a_{j}(t,x)\Phi_{j}^{\mu}(\sigma x)-\fint_{\mathbb{T}^{d}}a_{j}(t,x)\Phi_{j}^{\mu}(\sigma x)\,dx\Big{)}\Big{\}},

with the help of \mathcal{B}, we define 𝑹tem\boldsymbol{R}_{\rm tem} by

𝑹tem:=t(g~κ(λt)j(aj,Φjμ(σx))).\boldsymbol{R}_{\rm tem}:=\partial_{t}\left(\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\mathcal{B}(a_{j},\Phi_{j}^{\mu}(\sigma x))\right).

Now we consider 𝑹osc\boldsymbol{R}_{\rm osc}. We split 𝑹osc\boldsymbol{R}_{{\rm osc}} into three parts

𝑹osc:=𝑹osc,x+𝑹osc,t+𝑹rem,\boldsymbol{R}_{{\rm osc}}:=\boldsymbol{R}_{{\rm osc},x}+\boldsymbol{R}_{{\rm osc},t}+\boldsymbol{R}_{{\rm rem}},

where

𝑹osc,t\displaystyle\boldsymbol{R}_{{\rm osc},t} :=λ1hκ(λt)jt(χj2Rj)𝒆j,\displaystyle:=\lambda^{-1}h_{\kappa}(\lambda t)\sum\nolimits_{j}\partial_{t}(\chi_{j}^{2}R_{j})\boldsymbol{e}_{j},
𝑹rem\displaystyle\boldsymbol{R}_{\rm rem} :=j(1χj2)Rj𝒆j.\displaystyle:=\sum\nolimits_{j}(1-\chi_{j}^{2})R_{j}\boldsymbol{e}_{j}.

Firstly notice

tθo\displaystyle\partial_{t}\theta_{o} =(thκ)(λt)divjχj2Rj𝒆j+λ1hκ(λt)t(divjχj2Rj𝒆j)\displaystyle=(\partial_{t}h_{\kappa})(\lambda t)\operatorname{div}\sum\nolimits_{j}\chi_{j}^{2}R_{j}\boldsymbol{e}_{j}+\lambda^{-1}h_{\kappa}(\lambda t)\partial_{t}\Big{(}\operatorname{div}\sum\nolimits_{j}\chi_{j}^{2}R_{j}\boldsymbol{e}_{j}\Big{)}
=[1g¯κg~κ(λt)]jj(ajbj)+div𝑹osc,t.\displaystyle=[1-\bar{g}_{\kappa}\tilde{g}_{\kappa}(\lambda t)]\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})+\operatorname{div}\boldsymbol{R}_{{\rm osc},t}.

According to div(Φjμ𝑾jμ)=0\operatorname{div}(\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu})=0, and when iji\neq j, there holds Φjμ𝑾iμ=0,𝒆j𝑾iμ=0\Phi_{j}^{\mu}\boldsymbol{W}_{i}^{\mu}=0,\boldsymbol{e}_{j}\cdot\boldsymbol{W}_{i}^{\mu}=0. We have

div(θp𝒘p)\displaystyle\operatorname{div}(\theta_{p}\boldsymbol{w}_{p}) =g¯κg~κ(λt)divjajbjΦjμ𝑾jμ\displaystyle=\bar{g}_{\kappa}\tilde{g}_{\kappa}(\lambda t)\operatorname{div}\sum\nolimits_{j}a_{j}b_{j}\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}
=g¯κg~κ(λt)jj(ajbj)Φjμ𝑾jμ𝒆j.\displaystyle=\bar{g}_{\kappa}\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}\cdot\boldsymbol{e}_{j}.

Hence

tθo+div(θp𝒘p+𝑹)\displaystyle\partial_{t}\theta_{o}+\operatorname{div}(\theta_{p}\boldsymbol{w}_{p}+\boldsymbol{R})
=g¯κg~κ(λt)jj(ajbj)(Φjμ𝑾jμ𝒆j1)+div𝑹osc,t+jj(ajbj)+div𝑹,\displaystyle=\bar{g}_{\kappa}\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})\big{(}\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}\cdot\boldsymbol{e}_{j}-1\big{)}+\operatorname{div}\boldsymbol{R}_{{\rm osc},t}+\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})+\operatorname{div}\boldsymbol{R},

Notice

jj(ajbj)+div𝑹=divj(1χj2)Rj𝒆j=div𝑹rem.\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})+\operatorname{div}\boldsymbol{R}=\operatorname{div}\sum\nolimits_{j}(1-\chi_{j}^{2})R_{j}\boldsymbol{e}_{j}=\operatorname{div}\boldsymbol{R}_{\rm rem}.

Hence 𝑹osc,x\boldsymbol{R}_{{\rm osc},x} satisfies

div𝑹osc,x=g¯κg~κ(λt)jj(ajbj)(Φjμ𝑾jμ𝒆j1).\operatorname{div}{\boldsymbol{R}_{{\rm osc},x}}=\bar{g}_{\kappa}\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\partial_{j}(a_{j}b_{j})\big{(}\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}\cdot\boldsymbol{e}_{j}-1\big{)}.

Since

𝕋dΦjμ𝑾jμ𝒆j𝑑x=𝒆j𝒆j=1,\int_{\mathbb{T}^{d}}\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}\cdot\boldsymbol{e}_{j}\,dx=\boldsymbol{e}_{j}\cdot\boldsymbol{e}_{j}=1,

𝑹osc,x\boldsymbol{R}_{{\rm osc},x} can be defined by

𝑹osc,x:=g~κg¯κ(λt)j(j(ajbj),Φjμ𝑾jμ(σx)𝒆j1).\boldsymbol{R}_{{\rm osc},x}:=\tilde{g}_{\kappa}\bar{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\mathcal{B}(\partial_{j}(a_{j}b_{j}),\Phi_{j}^{\mu}\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}-1).

4.3 Setting the parameters

There are four controllable parameters μ,κ,σ,λ\mu,\kappa,\sigma,\lambda. We will set κ,σ,λ\kappa,\sigma,\lambda as some positive powers of μ\mu and then let μ\mu large enough.

Concentration parameter in space μ\mu: hereafter, we take μμ0\mu\geq\mu_{0} with μ0\mu_{0} large enough depending on the old solution (ρ,𝒖,𝑹)(\rho,\boldsymbol{u},\boldsymbol{R}) and N,ν,δN,\nu,\delta given in Proposition 2.1, such that all lemmas below hold. Actually, how large μ0\mu_{0} is and what quantities do μ0\mu_{0} depend on are inessential as long as μ\mu is taken to be finite at last, since the most significant matter is that we need to balance the estimates on the perturbations and the new defect field by reasonable setting of κ,σ,λ\kappa,\sigma,\lambda. Recall s~<s\tilde{s}<s^{\prime}, the following setting works well.

Concentration parameter in time κ\kappa: setting κ=μαss~ss~\kappa=\mu^{\alpha\frac{s^{\prime}\tilde{s}}{s^{\prime}-\tilde{s}}} with

α=1+(p1)(d1)2(p+1)p.\alpha=1+\frac{(p-1)(d-1)}{2(p+1)p}. (4.7)

Oscillation parameter in space σ\sigma\in\mathbb{N}: setting σ=μβ2μβ\sigma=\lfloor\mu^{\beta}\rfloor\leq 2\mu^{\beta} with

β=(p1)(d1)4(p+1)p.\beta=\frac{(p-1)(d-1)}{4(p+1)p}. (4.8)

Oscillation parameter in time λ\lambda\in\mathbb{N}: setting λ=μβ/24σ1/2\lambda=\lfloor\mu^{\beta/2}\rfloor\leq 4\sigma^{1/2}.

Finally, we choose N=αss~βs(ss~)+dβN=\lceil\frac{\alpha s^{\prime}\tilde{s}}{\beta s(s^{\prime}-\tilde{s})}+\frac{d}{\beta}\rceil. Where \lfloor\cdot\rfloor is the floor function and \lceil\cdot\rceil is the ceiling function.

Remark 4.1.

For the condition (1.4), setting

κ=μαss~ss~,σ=μϵ,λ=μϵ/2\displaystyle\kappa=\mu^{\alpha\frac{s^{\prime}\tilde{s}}{s^{\prime}-\tilde{s}}},\quad\sigma=\lfloor\mu^{\epsilon}\rfloor,\quad\lambda=\lfloor\mu^{\epsilon/2}\rfloor

with ϵ>0\epsilon>0 small enough and

α=1+2β,β=(p1)(d1)p2ϵ.\displaystyle\alpha=1+2\beta,\quad\beta=\frac{(p-1)(d-1)}{p}-2\epsilon.

4.4 Estimates on the perturbations

Lemma 4.1 (Estimate on θp\theta_{p}).
θpLtsLxpν𝑹Lt,x11/p+νC(σ1/p+λ1/s).\|\theta_{p}\|_{L^{s}_{t}L^{p}_{x}}\lesssim\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}+\nu C_{*}(\sigma^{-1/p}+\lambda^{-1/s}).

In particular, for μ\mu large enough,

θpLtsLxpν𝑹Lt,x11/p.\|\theta_{p}\|_{L^{s}_{t}L^{p}_{x}}\lesssim\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}.
Proof.
θp(t)Lp|g~κ(λt)|jaj(t)Φjμ(σ)Lp.\|\theta_{p}(t)\|_{L^{p}}\leq|\tilde{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|a_{j}(t)\Phi_{j}^{\mu}(\sigma\cdot)\|_{L^{p}}.

Since aj(t,)a_{j}(t,\cdot) is smooth on 𝕋d\mathbb{T}^{d}, by Lemma 3.3 and (4.3), we have

aj(t)Φjμ(σ)Lpaj(t)LpΦjμLp+νCσ1/pΦjμLp.\|a_{j}(t)\Phi_{j}^{\mu}(\sigma\cdot)\|_{L^{p}}\leq\|a_{j}(t)\|_{L^{p}}\|\Phi_{j}^{\mu}\|_{L^{p}}+\nu C_{*}\sigma^{-1/p}\|\Phi_{j}^{\mu}\|_{L^{p}}.

Combining (3.3) and (4.2), we obtain

θp(t)Lpν|g~κ(λt)|j(R~jLt,x11p1sR~j(t)L11s+Cσ1/p).\|\theta_{p}(t)\|_{L^{p}}\lesssim\nu|\tilde{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}(\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{p}-\frac{1}{s}}\|\widetilde{R}_{j}(t)\|_{L^{1}}^{\frac{1}{s}}+C_{*}\sigma^{-1/p}).

Now we take LsL^{s} in time to obtain

θpLtsLxpνjR~jLt,x11p1s([0,1]|g~κ(λt)|sR~j(t)L1𝑑t)1/s+νg~κLtsCσ1/p.\|\theta_{p}\|_{L^{s}_{t}L^{p}_{x}}\lesssim\nu\sum\nolimits_{j}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{p}-\frac{1}{s}}\Big{(}\int_{[0,1]}|\tilde{g}_{\kappa}(\lambda t)|^{s}\|\widetilde{R}_{j}(t)\|_{L^{1}}\,dt\Big{)}^{1/s}+\nu\|\tilde{g}_{\kappa}\|_{L^{s}_{t}}C_{*}\sigma^{-1/p}.

Applying Lemma 3.3 in time once again gives

[0,1]|g~κ(λt)|sR~j(t)L1𝑑tR~jLt,x1g~κLtss+Cλ1\int_{[0,1]}|\tilde{g}_{\kappa}(\lambda t)|^{s}\|\widetilde{R}_{j}(t)\|_{L^{1}}\,dt\leq\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}\|\tilde{g}_{\kappa}\|^{s}_{L^{s}_{t}}+C_{*}\lambda^{-1}

Finally, by (3.6) we have

θpLtsLxp\displaystyle\|\theta_{p}\|_{L^{s}_{t}L^{p}_{x}} νjR~jLt,x11/pg~κLts+νC(σ1/p+λ1/s)\displaystyle\lesssim\nu\sum\nolimits_{j}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{1/p}\|\tilde{g}_{\kappa}\|_{L^{s}_{t}}+\nu C_{*}(\sigma^{-1/p}+\lambda^{-1/s})
ν𝑹Lt,x11/p+νC(σ1/p+λ1/s).\displaystyle\lesssim\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}+\nu C_{*}(\sigma^{-1/p}+\lambda^{-1/s}).

Lemma 4.2 (Estimate on θc\theta_{c}).

For N=αss~βs(ss~)+dβN=\lceil\frac{\alpha s^{\prime}\tilde{s}}{\beta s(s^{\prime}-\tilde{s})}+\frac{d}{\beta}\rceil, we have

θcLtCνμd1pd12.\|\theta_{c}\|_{L^{\infty}_{t}}\leq C_{*}\nu\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}}.

In particular, for μ\mu large enough,

θcLtsLxpν𝑹Lt,x11/p.\|\theta_{c}\|_{L^{s}_{t}L^{p}_{x}}\leq\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}.
Proof.

Since

θc=g~κ(λt)j𝕋daj(t,x)Φjμ(σx)𝑑x,\theta_{c}=\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\fint_{\mathbb{T}^{d}}a_{j}(t,x)\Phi_{j}^{\mu}(\sigma x)\,dx,

by Lemma 3.4 and notice N>αss~βs(ss~)+dβN>\frac{\alpha s^{\prime}\tilde{s}}{\beta s(s^{\prime}-\tilde{s})}+\frac{d}{\beta}, we have

θcLt\displaystyle\|\theta_{c}\|_{L^{\infty}_{t}} σNg~κLjajCNΦjμL2\displaystyle\leq\sigma^{-N}\|\tilde{g}_{\kappa}\|_{L^{\infty}}\sum\nolimits_{j}\|a_{j}\|_{C^{N}}\|\Phi_{j}^{\mu}\|_{L^{2}}
by Proposition 3.5,(3.6),(4.3) CνσNκ1sμd1pd12\displaystyle\leq C_{*}\nu\sigma^{-N}\kappa^{\frac{1}{s}}\mu^{\frac{d-1}{p}-\frac{d-1}{2}}
by (4.7),(4.8) Cνμd1pd12d.\displaystyle\leq C_{*}\nu\mu^{\frac{d-1}{p}-\frac{d-1}{2}-d}.

Lemma 4.3 (Estimate on θo\theta_{o}).
θoLt,xCλ1.\|\theta_{o}\|_{L^{\infty}_{t,x}}\leq C_{*}\lambda^{-1}.

In particular, for μ\mu large enough,

θoLtsLxpν𝑹Lt,x11/p.\|\theta_{o}\|_{L^{s}_{t}L^{p}_{x}}\leq\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}.
Proof.

We control (χj2Rj)Lt,x\|\nabla(\chi_{j}^{2}R_{j})\|_{L^{\infty}_{t,x}} simply by a constant CC_{*}, then by (3.7) we obtain

θoLt,xλ1hκLtjej(χj2Rj)Lt,xCλ1.\|\theta_{o}\|_{L^{\infty}_{t,x}}\leq\lambda^{-1}\|h_{\kappa}\|_{L^{\infty}_{t}}\sum\nolimits_{j}\|e_{j}\cdot\nabla(\chi_{j}^{2}R_{j})\|_{L^{\infty}_{t,x}}\leq C_{*}\lambda^{-1}.

Lemma 4.4 (Estimate on 𝒘p\boldsymbol{w}_{p} with LtsLxpL^{s^{\prime}}_{t}L^{p^{\prime}}_{x} norm).
𝒘pLtsLxpjν1R~jLt,x111p+ν1C(λ1/s+σ1/p)\|\boldsymbol{w}_{p}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\lesssim\sum\nolimits_{j}\nu^{-1}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{1-\frac{1}{p}}+\nu^{-1}C_{*}(\lambda^{-1/s^{\prime}}+\sigma^{-1/p^{\prime}})

In particular, for μ\mu large enough,

𝒘pLtsLxpν1𝑹Lt,x11/p.\|\boldsymbol{w}_{p}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\lesssim\nu^{-1}\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p^{\prime}}.
Proof.

By Lemma 3.3 and (4.3),

𝒘p(t)Lp\displaystyle\|\boldsymbol{w}_{p}(t)\|_{L^{p^{\prime}}} |g¯κ(λt)|jbj(t)𝑾jμ(σ)Lp\displaystyle\leq|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|b_{j}(t)\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\|_{L^{p^{\prime}}}
|g¯κ(λt)|j(bj(t)Lp𝑾jμLp+ν1Cσ1/p𝑾jμLp).\displaystyle\leq|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}(\|b_{j}(t)\|_{L^{p^{\prime}}}\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}+\nu^{-1}C_{*}\sigma^{-1/p^{\prime}}\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}).

By Proposition 3.5 and (3.6), we have 𝑾jμLp1\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}\lesssim 1 and g¯κ(λ)Lts=g¯κLts1\|\bar{g}_{\kappa}(\lambda\cdot)\|_{L^{s^{\prime}}_{t}}=\|\bar{g}_{\kappa}\|_{L^{s^{\prime}}_{t}}\lesssim 1. Hence

𝒘pLtsLxp\displaystyle\|\boldsymbol{w}_{p}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} j([0,1]|g¯κ(λt)|sbj(t)Lps𝑑t)1/s+ν1Cσ1/p\displaystyle\lesssim\sum\nolimits_{j}\Big{(}\int_{[0,1]}|\bar{g}_{\kappa}(\lambda t)|^{s^{\prime}}\|b_{j}(t)\|_{L^{p^{\prime}}}^{s^{\prime}}\,dt\Big{)}^{1/s^{\prime}}+\nu^{-1}C_{*}\sigma^{-1/p^{\prime}}
by (4.2) jν1R~jLt,x11s1p([0,1]|g¯κ(λt)|sR~j(t)L1𝑑t)1s+ν1Cσ1p\displaystyle\lesssim\sum\nolimits_{j}\nu^{-1}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{s}-\frac{1}{p}}\Big{(}\int_{[0,1]}|\bar{g}_{\kappa}(\lambda t)|^{s^{\prime}}\|\widetilde{R}_{j}(t)\|_{L^{1}}\,dt\Big{)}^{\frac{1}{s^{\prime}}}+\nu^{-1}C_{*}\sigma^{-\frac{1}{p^{\prime}}}
by Lemma 3.3 jν1R~jLt,x11s1p(R~jLt,x1g¯κLtss+Cλ1)1s+ν1Cσ1p\displaystyle\lesssim\sum\nolimits_{j}\nu^{-1}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{\frac{1}{s}-\frac{1}{p}}\Big{(}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}\|\bar{g}_{\kappa}\|^{s^{\prime}}_{L^{s^{\prime}}_{t}}+C_{*}\lambda^{-1}\Big{)}^{\frac{1}{s^{\prime}}}+\nu^{-1}C_{*}\sigma^{-\frac{1}{p^{\prime}}}
jν1R~jLt,x111p+ν1C(λ1/s+σ1/p)\displaystyle\lesssim\sum\nolimits_{j}\nu^{-1}\|\widetilde{R}_{j}\|_{L^{1}_{t,x}}^{1-\frac{1}{p}}+\nu^{-1}C_{*}(\lambda^{-1/s^{\prime}}+\sigma^{-1/p^{\prime}})

Lemma 4.5 (Estimate on 𝒘p\boldsymbol{w}_{p} with Lts~Wx1,qL^{\tilde{s}}_{t}W^{1,q}_{x} norm).
𝒘pLts~Wx1,qν1Cμγ1,\|\boldsymbol{w}_{p}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}}\leq\nu^{-1}C_{*}\mu^{\gamma_{1}},

for some γ1<0\gamma_{1}<0. In particular, for μ\mu large enough, we have

𝒘pLts~Wx1,qδ20.\|\boldsymbol{w}_{p}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}}\leq\frac{\delta}{20}.
Remark 4.2.

s<s<\infty and the first condition of (1.3) are required in this estimate.

Proof.
𝒘p(t)Wx1,q\displaystyle\|\boldsymbol{w}_{p}(t)\|_{W^{1,q}_{x}} |g¯κ(λt)|jbj(t)𝑾jμ(σ)Wx1,q\displaystyle\leq|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|b_{j}(t)\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\|_{W^{1,q}_{x}}
|g¯κ(λt)|jbjC1𝑾jμ(σ)Wx1,q\displaystyle\leq|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|b_{j}\|_{C^{1}}\|\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\|_{W^{1,q}_{x}}
by (4.3) ν1C|g¯κ(λt)|j(𝑾jμq+σ𝑾jμLq)\displaystyle\leq\nu^{-1}C_{*}|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}(\|\boldsymbol{W}_{j}^{\mu}\|_{q}+\sigma\|\nabla\boldsymbol{W}_{j}^{\mu}\|_{L^{q}})
by Proposition 3.5 ν1C|g¯κ(λt)|σμ1+d1pd1q.\displaystyle\leq\nu^{-1}C_{*}|\bar{g}_{\kappa}(\lambda t)|\sigma\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}.

Hence

𝒘pLts~Wx1,q\displaystyle\|\boldsymbol{w}_{p}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} ν1Cσμ1+d1pd1qg¯κLs~([0,1])\displaystyle\leq\nu^{-1}C_{*}\sigma\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}\|\bar{g}_{\kappa}\|_{L^{\tilde{s}}([0,1])}
by (3.6) ν1Cσμ1+d1pd1qκs~sss~\displaystyle\leq\nu^{-1}C_{*}\sigma\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}\kappa^{\frac{\tilde{s}-s^{\prime}}{s^{\prime}\tilde{s}}}
by (4.7),(4.8) ν1Cμ1+d1pd1q+βα\displaystyle\leq\nu^{-1}C_{*}\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}+\beta-\alpha}
ν1Cμγ1,\displaystyle\leq\nu^{-1}C_{*}\mu^{\gamma_{1}},

where γ1=(d1)[1p14(p+1)p(1p+1q)]<0\gamma_{1}=(d-1)[1-\frac{p-1}{4(p+1)p}-(\frac{1}{p}+\frac{1}{q})]<0 by the assumption (1.3). ∎

Lemma 4.6 (Estimate on 𝒘c\boldsymbol{w}_{c}).
𝒘cLtsLxp\displaystyle\|\boldsymbol{w}_{c}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} ν1Cσ1,\displaystyle\leq\nu^{-1}C_{*}\sigma^{-1},
𝒘cLts~Wx1,q\displaystyle\|\boldsymbol{w}_{c}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} ν1Cμγ2\displaystyle\leq\nu^{-1}C_{*}\mu^{\gamma_{2}}

for some γ2<0\gamma_{2}<0. In particular, for μ\mu large enough, we have

𝒘cLtsLxp\displaystyle\|\boldsymbol{w}_{c}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} ν1𝑹Lt,x11/p,\displaystyle\leq\nu^{-1}\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p^{\prime}},
𝒘cLts~Wx1,q\displaystyle\|\boldsymbol{w}_{c}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} δ20.\displaystyle\leq\frac{\delta}{20}.
Remark 4.3.

s<s<\infty and the first condition of (1.3) are required in this estimate.

Proof.

By Lemma 3.2, Proposition 3.5 and (4.3), we have

𝒘c(t)Lp\displaystyle\|\boldsymbol{w}_{c}(t)\|_{L^{p^{\prime}}} |g¯κ(λt)|jbjC2𝑾jμ(σ)Lp\displaystyle\lesssim|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|b_{j}\|_{C^{2}}\|\mathcal{R}\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\|_{L^{p^{\prime}}}
ν1C|g¯κ(λt)|jσ1𝑾jμLp\displaystyle\leq\nu^{-1}C_{*}|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\sigma^{-1}\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}
ν1C|g¯κ(λt)|σ1.\displaystyle\leq\nu^{-1}C_{*}|\bar{g}_{\kappa}(\lambda t)|\sigma^{-1}.

Hence by (3.6), we have

𝒘cLtsLxpν1Cg¯κLtsσ1ν1Cσ1.\|\boldsymbol{w}_{c}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\leq\nu^{-1}C_{*}\|\bar{g}_{\kappa}\|_{L^{s^{\prime}}_{t}}\sigma^{-1}\leq\nu^{-1}C_{*}\sigma^{-1}.

By Lemma 3.1, Proposition 3.5 and the definition of \mathcal{B}, we have

𝒘c(t)Wx1,q\displaystyle\|\boldsymbol{w}_{c}(t)\|_{W^{1,q}_{x}} |g¯κ(λt)|j(jbj,𝑾jμ(σ)𝒆j)Wx1,q\displaystyle\lesssim|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|\mathcal{B}(\partial_{j}b_{j},\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\cdot\boldsymbol{e}_{j})\|_{W^{1,q}_{x}}
|g¯κ(λt)|j(jbj(𝑾jμ(σ)𝒆j)Wx1,q\displaystyle\lesssim|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}(\|\partial_{j}b_{j}\mathcal{R}(\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\cdot\boldsymbol{e}_{j})\|_{W^{1,q}_{x}}
+((jbj)((𝑾jμ(σ)𝒆j)))Wx1,q)\displaystyle\quad+\|\mathcal{R}(\nabla(\partial_{j}b_{j})\cdot(\mathcal{R}(\boldsymbol{W}_{j}^{\mu}(\sigma\cdot)\cdot\boldsymbol{e}_{j})))\|_{W^{1,q}_{x}})
|g¯κ(λt)|j(bjC2𝑾jμ()𝒆jWx1,q+bjC3𝑾jμ()𝒆jWx1,q)\displaystyle\lesssim|\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}(\|b_{j}\|_{C^{2}}\|\boldsymbol{W}_{j}^{\mu}(\cdot)\cdot\boldsymbol{e}_{j}\|_{W^{1,q}_{x}}+\|b_{j}\|_{C^{3}}\|\boldsymbol{W}_{j}^{\mu}(\cdot)\cdot\boldsymbol{e}_{j}\|_{W^{1,q}_{x}})
by (4.3) ν1C|g¯κ(λt)|μ1+d1pd1q\displaystyle\leq\nu^{-1}C_{*}|\bar{g}_{\kappa}(\lambda t)|\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}

Hence

𝒘cLts~Wx1,q\displaystyle\|\boldsymbol{w}_{c}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} ν1Cμ1+d1pd1qg¯κLts~\displaystyle\leq\nu^{-1}C_{*}\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}\|\bar{g}_{\kappa}\|_{L^{\tilde{s}}_{t}}
by (3.6) ν1Cμ1+d1pd1qκs~sss~\displaystyle\leq\nu^{-1}C_{*}\mu^{1+\frac{d-1}{p^{\prime}}-\frac{d-1}{q}}\kappa^{\frac{\tilde{s}-s^{\prime}}{s^{\prime}\tilde{s}}}
by (4.7) ν1Cμγ2\displaystyle\leq\nu^{-1}C_{*}\mu^{\gamma_{2}}

where γ2=(d1)[1p12(p+1)p(1p+1q)]<0\gamma_{2}=(d-1)[1-\frac{p-1}{2(p+1)p}-(\frac{1}{p}+\frac{1}{q})]<0 by the assumption (1.3). ∎

Lemma 4.7.

For N=αss~βs(ss~)+dβN=\lceil\frac{\alpha s^{\prime}\tilde{s}}{\beta s(s^{\prime}-\tilde{s})}+\frac{d}{\beta}\rceil and μ\mu large enough, we have

|𝕋dθ(t,x)ϕ(x)𝑑x|δϕCNt[0,1],ϕC(𝕋d).\Big{|}\int_{\mathbb{T}^{d}}\theta(t,x)\phi(x)\,dx\Big{|}\leq\delta\|\phi\|_{C^{N}}\quad\forall t\in[0,1],\,\forall\phi\in C^{\infty}(\mathbb{T}^{d}).

Moreover supptθIr\operatorname{supp}_{t}\theta\in I_{r}.

Proof.

By the definition, it is obvious that supptθIr\operatorname{supp}_{t}\theta\in I_{r}. Notice

|𝕋dθ(t,x)ϕ(x)𝑑x|\displaystyle\Big{|}\int_{\mathbb{T}^{d}}\theta(t,x)\phi(x)\,dx\Big{|}
|𝕋dθp(t,x)ϕ(x)𝑑x|+|𝕋dθc(t,x)ϕ(x)𝑑x|+|𝕋dθo(t,x)ϕ(x)𝑑x|.\displaystyle\leq\Big{|}\int_{\mathbb{T}^{d}}\theta_{p}(t,x)\phi(x)\,dx\Big{|}+\Big{|}\int_{\mathbb{T}^{d}}\theta_{c}(t,x)\phi(x)\,dx\Big{|}+\Big{|}\int_{\mathbb{T}^{d}}\theta_{o}(t,x)\phi(x)\,dx\Big{|}.

By Lemma 3.4, Proposition 3.5 and notice N>αss~βs(ss~)+dβN>\frac{\alpha s^{\prime}\tilde{s}}{\beta s(s^{\prime}-\tilde{s})}+\frac{d}{\beta}, we have

|𝕋dθp(t,x)ϕ(x)𝑑x|\displaystyle\Big{|}\int_{\mathbb{T}^{d}}\theta_{p}(t,x)\phi(x)\,dx\Big{|} σNg~κLjajϕCNΦjμL2\displaystyle\leq\sigma^{-N}\|\tilde{g}_{\kappa}\|_{L^{\infty}}\sum\nolimits_{j}\|a_{j}\phi\|_{C^{N}}\|\Phi_{j}^{\mu}\|_{L^{2}}
by (3.6),(4.3) νCσNκ1sμd1pd12ϕCN\displaystyle\leq\nu C_{*}\sigma^{-N}\kappa^{\frac{1}{s}}\mu^{\frac{d-1}{p}-\frac{d-1}{2}}\|\phi\|_{C^{N}}
by (4.7),(4.8) νCμd1pd12ϕCN.\displaystyle\leq\nu C_{*}\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}}\|\phi\|_{C^{N}}.

By Lemma 4.2, we have

|𝕋dθc(t,x)ϕ(x)𝑑x|θcLt,xϕLνCμd1pd12ϕL.\Big{|}\int_{\mathbb{T}^{d}}\theta_{c}(t,x)\phi(x)\,dx\Big{|}\leq\|\theta_{c}\|_{L^{\infty}_{t,x}}\|\phi\|_{L^{\infty}}\leq\nu C_{*}\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}}\|\phi\|_{L^{\infty}}.

Similarly, by Lemma 4.3, we have

|𝕋dθo(t,x)ϕ(x)𝑑x|θoLt,xϕLCλ1ϕL.\Big{|}\int_{\mathbb{T}^{d}}\theta_{o}(t,x)\phi(x)\,dx\Big{|}\leq\|\theta_{o}\|_{L^{\infty}_{t,x}}\|\phi\|_{L^{\infty}}\leq C_{*}\lambda^{-1}\|\phi\|_{L^{\infty}}.

In conclusion, we have

|𝕋dθ(t,x)ϕ(x)𝑑x|νC(μd1pd12+ν1λ1)ϕCN.\Big{|}\int_{\mathbb{T}^{d}}\theta(t,x)\phi(x)\,dx\Big{|}\leq\nu C_{*}\Big{(}\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}}+\nu^{-1}\lambda^{-1}\Big{)}\|\phi\|_{C^{N}}.

4.5 Estimates on the new defect field

Lemma 4.8 (Estimate on 𝑹tem\boldsymbol{R}_{\rm tem}).

For μ\mu large enough, we have

𝑹temLt,x1δ10.\|\boldsymbol{R}_{\rm tem}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}. (4.9)
Remark 4.4.

p>1p>1 (for the C-Z inequality (3.2)) and the second condition of (1.3) are required in this estimate.

Proof.
𝑹tem\displaystyle\boldsymbol{R}_{\rm tem} =t(g~κ(λt))j(aj,Φjμ(σx))+g~κ(λt)j(taj,Φjμ(σx))\displaystyle=\partial_{t}(\tilde{g}_{\kappa}(\lambda t))\sum\nolimits_{j}\mathcal{B}(a_{j},\Phi_{j}^{\mu}(\sigma x))+\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\mathcal{B}(\partial_{t}a_{j},\Phi_{j}^{\mu}(\sigma x))
=:𝑹tem,1+𝑹tem,2.\displaystyle=:\boldsymbol{R}_{\rm tem,1}+\boldsymbol{R}_{\rm tem,2}.

For 𝑹tem,1\boldsymbol{R}_{\rm tem,1}, by Lemma 3.2 and notice [Φjμ(σ)](x)=σ1(Φjμ)(σx)\mathcal{R}[\Phi_{j}^{\mu}(\sigma\cdot)](x)=\sigma^{-1}(\mathcal{R}\Phi_{j}^{\mu})(\sigma x), we have

𝑹tem,1(t)L1\displaystyle\|\boldsymbol{R}_{\rm tem,1}(t)\|_{L^{1}} λ(tg~κ)(λt)j(aj,Φjμ(σ))L1\displaystyle\leq\lambda(\partial_{t}\tilde{g}_{\kappa})(\lambda t)\sum\nolimits_{j}\|\mathcal{B}(a_{j},\Phi_{j}^{\mu}(\sigma\cdot))\|_{L^{1}}
by (4.3) λ(tg~κ)(λt)jC(Φjμ(σ))L1\displaystyle\leq\lambda(\partial_{t}\tilde{g}_{\kappa})(\lambda t)\sum\nolimits_{j}C_{*}\|\mathcal{R}(\Phi_{j}^{\mu}(\sigma\cdot))\|_{L^{1}}
λ(tg~κ)(λt)jCσ1ΦjμL1\displaystyle\leq\lambda(\partial_{t}\tilde{g}_{\kappa})(\lambda t)\sum\nolimits_{j}C_{*}\sigma^{-1}\|\mathcal{R}\Phi_{j}^{\mu}\|_{L^{1}}
by (3.4) λσ1(tg~κ)(λt)jC(div𝛀jμ)L1\displaystyle\leq\lambda\sigma^{-1}(\partial_{t}\tilde{g}_{\kappa})(\lambda t)\sum\nolimits_{j}C_{*}\|\mathcal{R}(\operatorname{div}\boldsymbol{\Omega}_{j}^{\mu})\|_{L^{1}}
by (3.2) and p>1p>1 λσ1(tg~κ)(λt)jC𝛀jμLp+12.\displaystyle\leq\lambda\sigma^{-1}(\partial_{t}\tilde{g}_{\kappa})(\lambda t)\sum\nolimits_{j}C_{*}\|\boldsymbol{\Omega}_{j}^{\mu}\|_{L^{\frac{p+1}{2}}}.

(When under the conditions (1.4), we apply (3.2) to the last inequality with r>1r>1 sufficiently close to 1). Hence by (3.6) and Proposition 3.5

𝑹tem,1Lt,x1\displaystyle\|\boldsymbol{R}_{\rm tem,1}\|_{L^{1}_{t,x}} λσ1tg~κLt1jC𝛀jμLp+12\displaystyle\leq\lambda\sigma^{-1}\|\partial_{t}\tilde{g}_{\kappa}\|_{L^{1}_{t}}\sum\nolimits_{j}C_{*}\|\boldsymbol{\Omega}_{j}^{\mu}\|_{L^{\frac{p+1}{2}}}
Cλσ1κ1/sμ1+d1p2(d1)p+1\displaystyle\leq C_{*}\lambda\sigma^{-1}\kappa^{1/s}\mu^{-1+\frac{d-1}{p}-\frac{2(d-1)}{p+1}}
by (4.7),(4.8) Cσ1/2μ1+4βμ14β\displaystyle\leq C_{*}\sigma^{-1/2}\mu^{1+4\beta}\mu^{-1-4\beta}
Cμβ/2.\displaystyle\leq C_{*}\mu^{-\beta/2}.

where we have used κ1/sμ1+4β\kappa^{1/s}\leq\mu^{1+4\beta} by the second assumption of (1.3). Hence take μ\mu large enough, we have

𝑹tem,1Lt,x1δ20.\|\boldsymbol{R}_{\rm tem,1}\|_{L^{1}_{t,x}}\leq\frac{\delta}{20}. (4.10)

For 𝑹tem,2\boldsymbol{R}_{\rm tem,2}, we have by Lemma 3.2

𝑹tem,2(t)L1\displaystyle\|\boldsymbol{R}_{\rm tem,2}(t)\|_{L^{1}} g~κ(λt)j(taj,Φjμ(σ))L1\displaystyle\leq\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}\|\mathcal{B}(\partial_{t}a_{j},\Phi_{j}^{\mu}(\sigma\cdot))\|_{L^{1}}
g~κ(λt)jC(Φjμ(σ))L1\displaystyle\leq\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}C_{*}\|\mathcal{R}(\Phi_{j}^{\mu}(\sigma\cdot))\|_{L^{1}}
σ1g~κ(λt)jCΦjμL1.\displaystyle\leq\sigma^{-1}\tilde{g}_{\kappa}(\lambda t)\sum\nolimits_{j}C_{*}\|\Phi_{j}^{\mu}\|_{L^{1}}.

Now by Proposition 3.5 and (3.6), we have

𝑹tem,2Lt,x1Cσ1κ1sμd1p,\|\boldsymbol{R}_{\rm tem,2}\|_{L^{1}_{t,x}}\leq C_{*}\sigma^{-1}\kappa^{-\frac{1}{s^{\prime}}}\mu^{-\frac{d-1}{p^{\prime}}},

take μ\mu large enough, we have

𝑹tem,2Lt,x1δ20.\|\boldsymbol{R}_{\rm tem,2}\|_{L^{1}_{t,x}}\leq\frac{\delta}{20}. (4.11)

Adding (4.10),(4.11) results in (4.9). ∎

Lemma 4.9 (Estimate on 𝑹lin\boldsymbol{R}_{\rm lin}).

For μ\mu large enough, we have

𝑹linLt,x1δ10.\|\boldsymbol{R}_{\rm lin}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.
Proof.
𝑹linLt,x1\displaystyle\|\boldsymbol{R}_{\rm lin}\|_{L^{1}_{t,x}} θLt,x1𝒖Lt,x+𝒘Lt,x1ρLt,x.\displaystyle\leq\|\theta\|_{L^{1}_{t,x}}\|\boldsymbol{u}\|_{L^{\infty}_{t,x}}+\|\boldsymbol{w}\|_{L^{1}_{t,x}}\|\rho\|_{L^{\infty}_{t,x}}.

Notice by Proposition 3.5 and (3.6)

θp+θcLt,x1\displaystyle\|\theta_{p}+\theta_{c}\|_{L^{1}_{t,x}} 2jg~κ(λt)aj(t,x)Φjμ(σ)Lt,x1\displaystyle\leq 2\sum\nolimits_{j}\|\tilde{g}_{\kappa}(\lambda t)a_{j}(t,x)\Phi_{j}^{\mu}(\sigma\cdot)\|_{L^{1}_{t,x}}
by (4.3) νCjg~κLt1ΦjμL1\displaystyle\leq\nu C_{*}\sum\nolimits_{j}\|\tilde{g}_{\kappa}\|_{L^{1}_{t}}\|\Phi_{j}^{\mu}\|_{L^{1}}
νCκ1/sμ(1p)(d1)p.\displaystyle\leq\nu C_{*}\kappa^{-1/s^{\prime}}\mu^{\frac{(1-p)(d-1)}{p}}.

By Lemma 4.3

θoLt,x1θoLt,xCλ1.\|\theta_{o}\|_{L^{1}_{t,x}}\leq\|\theta_{o}\|_{L^{\infty}_{t,x}}\leq C_{*}\lambda^{-1}.

By Lemma 4.5 and 4.6

𝒘Lt,x1\displaystyle\|\boldsymbol{w}\|_{L^{1}_{t,x}} 𝒘pLts~Wx1,q+𝒘cLts~Wx1,q\displaystyle\leq\|\boldsymbol{w}_{p}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}}+\|\boldsymbol{w}_{c}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}}
ν1Cμγ1+ν1Cμγ2.\displaystyle\leq\nu^{-1}C_{*}\mu^{\gamma_{1}}+\nu^{-1}C_{*}\mu^{\gamma_{2}}.

In conclusion, we have

𝑹linLt,x1C(νκ1/sμ(1p)(d1)p+λ1+ν1μγ1+ν1μγ2),\|\boldsymbol{R}_{\rm lin}\|_{L^{1}_{t,x}}\leq C_{*}\Big{(}\nu\kappa^{-1/s^{\prime}}\mu^{\frac{(1-p)(d-1)}{p}}+\lambda^{-1}+\nu^{-1}\mu^{\gamma_{1}}+\nu^{-1}\mu^{\gamma_{2}}\Big{)},

take μ\mu large enough, we have

𝑹linLt,x1δ10.\|\boldsymbol{R}_{\rm lin}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.

Lemma 4.10 (Estimate on 𝑹cor\boldsymbol{R}_{\rm cor}).

For μ\mu large enough, we have

𝑹corLt,x1δ10.\|\boldsymbol{R}_{\rm cor}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.
Proof.
𝑹corLt,x1θLtsLxp𝒘cLtsLxp+θo+θcLtsLxp𝒘LtsLxp.\|\boldsymbol{R}_{\rm cor}\|_{L^{1}_{t,x}}\leq\|\theta\|_{L^{s}_{t}L^{p}_{x}}\|\boldsymbol{w}_{c}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}+\|\theta_{o}+\theta_{c}\|_{L^{s}_{t}L^{p}_{x}}\|\boldsymbol{w}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}.

Notice by Lemma 4.1-4.3 and Lemma 4.6, we have

θLtsLxp𝒘cLtsLxp𝑹Lt,x11/pCσ1.\|\theta\|_{L^{s}_{t}L^{p}_{x}}\|\boldsymbol{w}_{c}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\leq\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p}C_{*}\sigma^{-1}.

By Lemma 4.2-4.6, we have

θo+θcLtsLxp𝒘LtsLxpC(λ1+νμd1pd12)ν1𝑹Lt,x11/p.\|\theta_{o}+\theta_{c}\|_{L^{s}_{t}L^{p}_{x}}\|\boldsymbol{w}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\leq C_{*}(\lambda^{-1}+\nu\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}})\nu^{-1}\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p^{\prime}}.

Hence

𝑹corLt,x1C(σ1+ν1λ1+μd1pd12),\|\boldsymbol{R}_{\rm cor}\|_{L^{1}_{t,x}}\leq C_{*}(\sigma^{-1}+\nu^{-1}\lambda^{-1}+\mu^{-\frac{d-1}{p^{\prime}}-\frac{d-1}{2}}),

take μ\mu large enough, we have

𝑹corLt,x1δ10.\|\boldsymbol{R}_{\rm cor}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.

Lemma 4.11 (Estimate on 𝑹osc,x\boldsymbol{R}_{{\rm osc},x}).

For μ\mu large enough, we have

𝑹osc,xLt,x1δ10.\|\boldsymbol{R}_{{\rm osc},x}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.
Proof.

Denote Θj(σx):=Φjμ(σx)𝑾jμ(σx)𝒆j1\Theta_{j}(\sigma x):=\Phi_{j}^{\mu}(\sigma x)\boldsymbol{W}_{j}^{\mu}(\sigma x)\cdot\boldsymbol{e}_{j}-1. By Lemma 3.1-3.2 and notice [Θj(σ)](x)=σ1(Θj)(σx)\mathcal{R}[\Theta_{j}(\sigma\cdot)](x)=\sigma^{-1}(\mathcal{R}\Theta_{j})(\sigma x), we have

𝑹osc,x(t)L1\displaystyle\|\boldsymbol{R}_{{\rm osc},x}(t)\|_{L^{1}} |g~κg¯κ(λt)|j(j(ajbj),Θj(σ))L1\displaystyle\leq|\tilde{g}_{\kappa}\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|\mathcal{B}(\partial_{j}(a_{j}b_{j}),\Theta_{j}(\sigma\cdot))\|_{L^{1}}
|g~κg¯κ(λt)|jajbjC2(Θj(σ))L1\displaystyle\leq|\tilde{g}_{\kappa}\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\|a_{j}b_{j}\|_{C^{2}}\|\mathcal{R}(\Theta_{j}(\sigma\cdot))\|_{L^{1}}
by (4.3) C|g~κg¯κ(λt)|jσ1ΘjL1\displaystyle\leq C_{*}|\tilde{g}_{\kappa}\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\sigma^{-1}\|\Theta_{j}\|_{L^{1}}
C|g~κg¯κ(λt)|jσ1(ΦjμLp𝑾jμLp+1).\displaystyle\leq C_{*}|\tilde{g}_{\kappa}\bar{g}_{\kappa}(\lambda t)|\sum\nolimits_{j}\sigma^{-1}\Big{(}\|\Phi_{j}^{\mu}\|_{L^{p}}\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}+1\Big{)}.

By Proposition 3.5, we have ΦjμLp𝑾jμLp1\|\Phi_{j}^{\mu}\|_{L^{p}}\|\boldsymbol{W}_{j}^{\mu}\|_{L^{p^{\prime}}}\lesssim 1. Hence by (3.6), we finally obtain

𝑹osc,xLt,x1Cσ1g~κg¯κLt1Cσ1.\|\boldsymbol{R}_{{\rm osc},x}\|_{L^{1}_{t,x}}\leq C_{*}\sigma^{-1}\|\tilde{g}_{\kappa}\bar{g}_{\kappa}\|_{L^{1}_{t}}\leq C_{*}\sigma^{-1}.

Lemma 4.12 (Estimate on 𝑹osc,t\boldsymbol{R}_{{\rm osc},t}).

For μ\mu large enough, we have

𝑹osc,tLt,x1δ10.\|\boldsymbol{R}_{{\rm osc},t}\|_{L^{1}_{t,x}}\leq\frac{\delta}{10}.
Proof.

We control t(χj2Rj)Lt,x\|\partial_{t}(\chi_{j}^{2}R_{j})\|_{L^{\infty}_{t,x}} simply by a constant CC_{*}, then by Lemma 3.1 we obtain

𝑹osc,tLt,x1\displaystyle\|\boldsymbol{R}_{{\rm osc},t}\|_{L^{1}_{t,x}} λ1hκ(λt)jt(χj2Rj)Lt,x1\displaystyle\leq\lambda^{-1}\|h_{\kappa}(\lambda t)\sum\nolimits_{j}\partial_{t}(\chi_{j}^{2}R_{j})\|_{L^{1}_{t,x}}
Cλ1hκLt1jt(χj2Rj)Lt,x\displaystyle\leq C\lambda^{-1}\|h_{\kappa}\|_{L^{1}_{t}}\sum\nolimits_{j}\|\partial_{t}(\chi_{j}^{2}R_{j})\|_{L^{\infty}_{t,x}}
by (3.7) Cλ1.\displaystyle\leq C_{*}\lambda^{-1}.

Lemma 4.13 (Estimate on 𝑹rem\boldsymbol{R}_{\rm rem}).
𝑹remLt,x1δ2.\|\boldsymbol{R}_{\rm rem}\|_{L^{1}_{t,x}}\leq\frac{\delta}{2}.
Proof.

According to the definition (3.8) of χj\chi_{j} and the choice (3.9) of rr, we have

𝑹remLt,x1\displaystyle\|\boldsymbol{R}_{\rm rem}\|_{L^{1}_{t,x}} j(1χj2)Rj𝒆jLt,x1\displaystyle\leq\sum\nolimits_{j}\|(1-\chi_{j}^{2})R_{j}\boldsymbol{e}_{j}\|_{L^{1}_{t,x}}
j|Rj|δ4d(1χj2)|Rj|𝑑x𝑑t+tIrc(1χj2)|Rj|𝑑x𝑑t\displaystyle\leq\sum\nolimits_{j}\int_{|R_{j}|\leq\frac{\delta}{4d}}(1-\chi_{j}^{2})|R_{j}|\,dxdt+\int_{t\in I^{c}_{r}}(1-\chi_{j}^{2})|R_{j}|\,dxdt
d×(δ4d+2r𝑹Lt,x)=δ2.\displaystyle\leq d\times(\frac{\delta}{4d}+2r\|\boldsymbol{R}\|_{L^{\infty}_{t,x}})=\frac{\delta}{2}.

4.6 Conclusion

Proof of Proposition 2.1. Combine Lemma 4.1-4.13, there exists μ08d\mu_{0}\geq 8d large enough depending on the old solution (ρ,𝒖,𝑹)(\rho,\boldsymbol{u},\boldsymbol{R}) and N,ν,δN,\nu,\delta given in Proposition 2.1, such that for μμ0\mu\geq\mu_{0}, we have

θLtsLxp\displaystyle\|\theta\|_{L^{s}_{t}L^{p}_{x}} ν𝑹Lt,x11/p,\displaystyle\lesssim\nu\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p},
𝒘LtsLxp\displaystyle\|\boldsymbol{w}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}} ν1𝑹Lt,x11/p,\displaystyle\lesssim\nu^{-1}\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p^{\prime}},
𝒘Lts~Wx1,q\displaystyle\|\boldsymbol{w}\|_{L^{\tilde{s}}_{t}W^{1,q}_{x}} δ,𝑹1Lt,x1δ.\displaystyle\leq\delta,\quad\|\boldsymbol{R}^{1}\|_{L^{1}_{t,x}}\leq\delta.

The inessential constants in the estimates can be taken as a universal constant MM, that is

θLtsLxpνM𝑹Lt,x11/p,𝒘LtsLxpν1M𝑹Lt,x11/p.\|\theta\|_{L^{s}_{t}L^{p}_{x}}\leq\nu M\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p},\quad\|\boldsymbol{w}\|_{L^{s^{\prime}}_{t}L^{p^{\prime}}_{x}}\leq\nu^{-1}M\|\boldsymbol{R}\|_{L^{1}_{t,x}}^{1/p^{\prime}}.

Notice (2.2) follows from Lemma 4.7, meanwhile (2.3) follows from the definition (4.1) of θ\theta and the fact suppχjIr/2\operatorname{supp}\chi_{j}\subset I_{r/2}. Proposition 2.1 follows. ∎

Acknowledgments

This work is supported by the National Natural Science Foundation of China (Grant No.11871024).

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