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On Symmetry Breaking for the Navier–Stokes Equations

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Abstract

Inspired by an open question by Chemin, Zhang and Zhang about the regularity of the 3D Navier–Stokes equations with one initially small component, we investigate symmetry breaking and symmetry preservation. Our results fall in three classes. First we prove strong symmetry breaking. Specifically, we demonstrate third component norm inflation (3rdNI) and Isotropic Norm Inflation (INI) starting from zero third component. Second we prove symmetry breaking for initially zero third component, even in the presence of a favorable initial pressure gradient. Third we study certain symmetry preserving solutions with a shear flow structure. Specifically, we give applications to the inviscid limit and exhibit explicit solutions that inviscidly damp to the Kolmogorov flow.

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Notes

  1. Currently one component regularity criteria in terms of norms preserved with respect to the Navier–Stokes scaling symmetry, involve spatial norms with some differentiability or Lorentz time norms. It remains a long standing open problem if a solution to the Navier–Stokes equations u, with third component \(u_{3}\in L^{q}(0,T; L^{p}({\mathbb {R}}^3))\) \((\frac{3}{p}+\frac{2}{q}=1,\,p\in [3,\infty ])\) is smooth on \((0,T]\times {\mathbb {R}}^3\).

  2. This data has the structure given by (1.8). Our result shows that the solution map is not continuous at \({{\bar{u}}}_{\textrm{in}}\) in the critical space \({\dot{B}}^{-1}_{\infty , \infty }\).

  3. Note that a regularity criterion involving the velocity field along a time-varying direction was established in [35].

  4. This data has the structure given by (2.21).

  5. The terminology unfavorable refers here to the fact that the pressure is unfavorable to symmetry preservation.

  6. The terminology favorable refers here to the fact that the pressure is favorable to symmetry preservation. We demonstrate, see Theorem B that favorable pressure is still not enough to preserve the vanishing of the third component of the velocity, if it is zero initially.

  7. We thank Hao Jia for this observation.

  8. Let us give a short proof of this embedding. For a mean-free function v in \(L^3({{\mathbb {T}}}^3)\), for \(s>1\),

    $$\begin{aligned} \Big \Vert \sum _{\xi \in {{\mathbb {Z}}}^3\setminus \{0\}}e^{-s|\xi |^2}e^{ix\cdot \xi }{{\hat{v}}}(\xi )\Big \Vert _{L^\infty ({{\mathbb {T}}}^3)} =&\Big \Vert \sum _{\xi \in {{\mathbb {Z}}}^3\setminus \{0\}}s|\xi |^2e^{-s|\xi |^2}e^{ix\cdot \xi }\frac{{{\hat{v}}}(\xi )}{s|\xi |^2}\Big \Vert _{L^\infty ({{\mathbb {T}}}^3)}\\ \le&\frac{1}{s}\Big (\sum _{\xi \in {{\mathbb {Z}}}^3\setminus \{0\}}\frac{1}{|\xi |^4}\Big )^\frac{1}{2}\Big (\sum _{\xi \in {{\mathbb {Z}}}^3\setminus \{0\}}|{{\hat{v}}}(\xi )|^2\Big )^\frac{1}{2}\\ \le&\frac{C}{s}\Vert v\Vert _{L^2({{\mathbb {T}}}^3)}\le \frac{C}{s}\Vert v\Vert _{L^3({{\mathbb {T}}}^3)}, \end{aligned}$$

    where \(C\in (0,\infty )\) is a universal constant. Notice that we used that the function \(xe^{-x}\) is bounded on \({{\mathbb {R}}}\). For \(s\in (0,1]\), we rely on the result of Maekawa and Terasawa [36] for instance.

  9. We emphasize that \(k_j\) is a scalar. Comparing the data to (1.13), we see that here \(\kappa (r):=\frac{1}{\Gamma _2(r)}\), \(A_j=\frac{k_j}{\sqrt{j}}\), \(\mathbf {k_j}=(1,1,k_j)\) and \(\mathbf {k_j'}=(0,-1,k_j+1)\).

  10. In the computation follows, we drop the Helmholtz-Leray projector \({\mathcal {P}}\) since its contribution is harmless.

  11. As above, the existence time \(0<T<1\) is to be determined in terms of r.

  12. By weak-strong uniqueness, 2.75D shear flows (1.9) with \(f\in L^p\), \(p\ge 3\), and \(g\in C^\infty \) are unique amongst the general class of weak Leray-Hopf solutions.

  13. We refer to [40, page 104] where a similar argument is used.

  14. All subsequent estimates can be rigorously justified by approximating \(f\in H^{\ell }\) by smooth \(f_{k}\rightarrow f\) in \(H^{\ell }\).

  15. The fact that this is a weak solution to the 3D Euler equations uses the same arguments as in [4, Theorem 2].

  16. Once we get a solution for system (A.1), then it also satisfies the so-called primitive equations, see for example the works of Cao and Titi [9] and Hieber and Kashiwabara [25] on primitive equations.

  17. A byproduct of Theorem B is that system (A.1) is ill-posed for generic data in \(H^1\). The proof is by contradiction. In fact, if for any initial data \(u_{\textrm{in}}^{\textrm{h}}\) satisfying condition (1.5), there always exists a solution \( u^{\textrm{h}}\) to the problem (A.1) on some time interval [0, T], then one can extend \(u^{\textrm{h}}\) to a solution \(( u^{\textrm{h}}, 0)\) for the 3D Navier–Stokes problem (1.1). By local well-posedness theory for (1.1), regularity results in [38] and weak-strong uniqueness, one confirms that \(u=(u^{\textrm{h}}, 0)\) is the unique solution on [0, T] supplemented with initial data \((u^{\textrm{h}}_{\textrm{in}}, 0)\). In particular, it implies that \(u^3 \equiv 0\) will be preserved.

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Acknowledgements

The authors thank Hao Jia for stimulating discussions concerning the inviscid damping for the 2.75D shear flows, as well as Jean-Yves Chemin for a discussion relating to Theorem A. We also thank Pierre Gilles Lemarié-Rieusset and Helena J. Nussenzveig Lopes for their comments on an earlier version of this paper. CP and JT are partially supported by the Agence Nationale de la Recherche, project BORDS, grant ANR-16-CE40-0027-01. CP is also partially supported by the Agence Nationale de la Recherche, project SINGFLOWS, grant ANR- 18-CE40-0027-01, project CRISIS, grant ANR-20-CE40-0020-01, by the CY Initiative of Excellence, project CYNA (CY Nonlinear Analysis) and project CYFI (CYngular Fluids and Interfaces). JT is also supported by the Labex MME-DII. TB and CP thank the Institute of Advanced Studies of Cergy Paris University for their hospitality.

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Appendix A. Heuristics for the Structure of 2.75D Shear Flows

Appendix A. Heuristics for the Structure of 2.75D Shear Flows

In this appendix we give some heuristics about the derivation of 2.75D shear flows. As mentioned earlier, they are rotated versions of the parallel flows introduced by Wang [45]. Here we outline another derivation based on the analysis of the following reduced Navier–Stokes system

$$\begin{aligned} \left\{ \begin{aligned} \partial _t{ u^{\textrm{h}}}+u^{\textrm{h}}\cdot \nabla _{\textrm{h}} u^{\textrm{h}}+\nabla _{\textrm{h}} P&=\Delta u ^{\textrm{h}},\\ \partial _3 P&=0,\\ \textrm{div}_{\textrm{h}} u ^{\textrm{h}}&=0,\\ u^{\textrm{h}}|_{t=0}&=u^{\textrm{h}}_{\textrm{in}}. \end{aligned}\right. . \end{aligned}$$
(A.1)

We dub that system the ‘2.75D Navier–Stokes equations’.Footnote 16 It is well-known that solutions to this system with \(H^1\) data are smooth.Footnote 17

Consider initial data \(u^{\textrm{h}}_{\textrm{in}}\) of the form

$$\begin{aligned} u^{\textrm{h}}_{\textrm{in}}=\Bigl (\partial _2\phi (x), \,-\partial _1\phi (x)\Bigr ). \end{aligned}$$
(A.2)

Let us look for solutions of system (A.1) under the form

$$\begin{aligned} u^{\textrm{h}}=\Bigl (\partial _2\Phi (t, x), \,-\partial _1\Phi (t, x)\Bigr )=\nabla _{\textrm{h}}^{\perp } \Phi , \end{aligned}$$
(A.3)

where \(\nabla _{\textrm{h}}^{\perp }:=(\partial _2, -\partial _1)\). Notice that the pressure is now given by

$$\begin{aligned} \left\{ \begin{aligned}&\Delta _{\textrm{h}} P =-\textrm{div}_{\textrm{h}}(u^{\textrm{h}}\cdot \nabla _h u^{\textrm{h}})=2 \det \bigl (\textrm{Hessian}_{\textrm{h}}~~\Phi \bigr )\\&\partial _3 P=0, \end{aligned}\right. \end{aligned}$$

where we used the vector identities

$$\begin{aligned} \textrm{div}_{\textrm{h}} \Bigl ((\nabla _{\textrm{h}}^{\perp } \Phi )\cdot \nabla _{\textrm{h}} (\nabla _{\textrm{h}}^\perp \Phi )\Bigr )&= \textrm{div}_{\textrm{h}}\textrm{div}_{\textrm{h}}\Bigl ((\nabla _{\textrm{h}}^{\perp } \Phi ) \otimes (\nabla _{\textrm{h}}^{\perp } \Phi ) \Bigr ) \\&= (\nabla _{\textrm{h}}\nabla _{\textrm{h}}^\perp \Phi ): (\nabla _{\textrm{h}}\nabla _{\textrm{h}}^\perp \Phi )^{\textrm{T}}=-2 \det \bigl (\textrm{Hessian}_{\textrm{h}}~~\Phi \bigr ), \end{aligned}$$

where

$$\begin{aligned} \textrm{Hessian}_{\textrm{h}}{:=}\left( \begin{array}{cc} \partial _{1}^2 &{} \partial _{1}\partial _{2}\\ \partial _{1}\partial _{2} &{} \partial _{2}^2 \end{array} \right) . \end{aligned}$$

In order to have \(\partial _3 P=0\), one has to satisfy

$$\begin{aligned} \partial _3\det \bigl (\textrm{Hessian}_{\textrm{h}}~~\Phi \bigr )=0. \end{aligned}$$

If there exist a function \(\Psi : {{\mathbb {T}}}\times {{\mathbb {R}}}_+\rightarrow {{\mathbb {R}}}\) and a constant \(\lambda \in {\mathbb {Z}}\) such that

$$\begin{aligned} {\mathcal {L}}_\lambda \Phi (t, x)=\Psi (t, x_3) \quad \textrm{with}\quad {\mathcal {L}}_\lambda := \partial _1-\lambda \partial _2, \end{aligned}$$
(A.4)

then we have

$$\begin{aligned} \partial _1 {\mathcal {L}}_\lambda \Phi = \partial _2 {\mathcal {L}}_\lambda \Phi =0 \quad \mathrm{i.e.}\quad \left( \begin{array}{c} \partial _{1}^2 \Phi \\ \partial _{1}\partial _{2} \Phi \end{array} \right) =\lambda \left( \begin{array}{c} \partial _{1}\partial _{2} \Phi \\ \partial _{2}^2 \Phi \end{array}\right) , \end{aligned}$$

and thus

$$\begin{aligned} \det \bigl (\textrm{Hessian}_{\textrm{h}}~~\Phi \bigr )=0. \end{aligned}$$
(A.5)

In the following, we will focus on the case (A.4) for the Cauchy problem (A.1). Concerning the initial data, we also need to look for a function \(\psi : {{\mathbb {T}}}\rightarrow {{\mathbb {R}}}\) such that

$$\begin{aligned} {\mathcal {L}}_{\lambda }\phi (x) -\psi (x_3)=0. \end{aligned}$$
(A.6)

Recalling that the velocity \(u^{\textrm{h}}=\nabla ^\perp _{\textrm{h}} \Phi \) and taking into consideration (A.4), one has

$$\begin{aligned} u^{\textrm{h}}\cdot \nabla _{\textrm{h}} u^{\textrm{h}}=(-1, \lambda )\,\Psi \partial _{2}^2\Phi \end{aligned}$$

and P is a constant. Finally, we are lead to considering the following system

$$\begin{aligned} \left\{ \begin{aligned}&\partial _t{\partial _2 \Phi }-\Psi (t, x_3)\, \partial _{2}^2\Phi = \Delta \partial _2 \Phi \quad&\hbox {in}\ ~~{{\mathbb {R}}}_+\times {{\mathbb {T}}}^3,\\&\partial _t{(\lambda \partial _2 \Phi +\Psi (t, x_3))}-\lambda \Psi (t, x_3)\, \partial _{2}^2\Phi = \Delta (\lambda \partial _2 \Phi +\Psi (t, x_3)) \quad&\hbox {in}\ ~~{{\mathbb {R}}}_+\times {{\mathbb {T}}}^3,\\&(\Phi , \Psi )|_{t=0}= (\phi , \psi ) \quad \textrm{with}\quad {\mathcal {L}}_{\lambda }\phi -\psi (x_3)=0, \end{aligned}\right. \end{aligned}$$

which can be simplified as

$$\begin{aligned} \left\{ \begin{aligned}&\partial _t{\partial _2 \Phi }-\Psi (t, x_3)\, \partial _{2}^2\Phi = \Delta \partial _2 \Phi \quad&\hbox {in}\ ~~{{\mathbb {R}}}_+\times {{\mathbb {T}}}^3,\\&\partial _t\Psi (t, x_3) = \partial _{3}^2\Psi (t, x_3)\quad&\hbox {in}\ ~~{{\mathbb {R}}}_+\times {{\mathbb {T}}},\\&(\Phi , \Psi )|_{t=0}= (\phi , \psi ) \quad \textrm{with}\quad {\mathcal {L}}_{\lambda }\phi -\psi (x_3)=0. \end{aligned}\right. \end{aligned}$$
(A.7)

In conclusion, \(\Psi (t, x_3)= ({\mathcal {K}}\star \psi ) (t, x_3)\), where \({\mathcal {K}}\) is the one-dimensional heat kernel see (1.20), and \(\partial _2 \Phi \) satisfies the linear transport-heat equation

$$\begin{aligned} \left\{ \begin{aligned}&\partial _t v + V\cdot \nabla v = \Delta v\quad \textrm{in} ~~{{\mathbb {R}}}_+\times {{\mathbb {T}}}^3 \quad \textrm{with}\quad V=(0, -\Psi (t, x_3), 0),\\&v_{\textrm{in}}=\partial _2 \phi . \end{aligned}\right. \end{aligned}$$
(A.8)

Take \(\psi (x_3)=g(x_3)\) and

$$\begin{aligned} \phi (x)=\phi (\lambda x_1+ x_2, x_3)=\int \limits _0^{\lambda x_1+x_2} f(y_1, x_3)\,d y_1+ x_1 \psi (x_3). \end{aligned}$$

Obviously, \(\phi (x)\) and \(\psi (x_3)\) satisfy (A.6), so the associated solution \(\partial _2 \Phi (t, x)\) of (A.8) for which \(u^{\textrm{h}}\) given by (A.3) solves problem (A.1).

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Barker, T., Prange, C. & Tan, J. On Symmetry Breaking for the Navier–Stokes Equations. Commun. Math. Phys. 405, 25 (2024). https://doi.org/10.1007/s00220-023-04897-1

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