Flexibility for the Three-Dimensional Navier–Stokes Equations via Moving Hill Vortices
Abstract
We construct weak solutions of the three-dimensional incompressible Navier–Stokes equations on the torus. The convex-integration scheme is based on the moving-dipole construction of Bruè, Colombo, and Kumar [14]. For the explicit exponent
and for any two mean-zero, divergence-free vector fields in , we construct a weak solution whose traces at times and approximate the prescribed fields arbitrarily well and which satisfies
Exploiting the time-locality of the iteration, we also obtain exact nonuniqueness for a dense set of initial data in . The principal perturbations are localized, rescaled copies of Hill’s spherical vortex. The Hill scaling preserves both the kinetic-energy scale and the -scale of the velocity gradient. The construction uses localization of the potential exterior flow, long-orbit averaging of moving vortex cores, an auxiliary source correction, and a temporal corrector compatible with uniform-in-time Sobolev control.
1 Introduction
1.1 The problem and the main result
We consider the incompressible Navier–Stokes equations on the three-dimensional torus:
| (1.1) |
where is the velocity, is the pressure, and is fixed. We take with normalized Lebesgue measure . Throughout the paper, all velocity fields have zero spatial mean.
We write
A finite-energy weak solution of (1.1) is a vector field
such that
| (1.2) |
for every satisfying . The pressure can then be recovered as a distribution. No energy inequality is included in this definition.
Our main result is the following.
Theorem 1.1 (Flexibility).
The numerical value of is not claimed to be optimal. It is an explicit exponent for which all inequalities in the parameter selection are strict. The threshold comes from the Hill scaling used in the present construction. Also, Theorem 1.1 is not a statement in the Leray–Hopf class: the regularity , with close to , does not imply , and the solutions constructed here are not asserted to satisfy the energy inequality.
1.2 Interpretation and consequences of the theorem
Theorem 1.1 can be restated as a density result for pairs of endpoint traces. Let denote the set of all weak solutions of (1.1) satisfying and .
Then
| (1.3) |
Thus weak trajectories in this class connect arbitrarily small neighborhoods of any two prescribed states. No compatibility condition is imposed on the endpoint targets.
This is an approximate, rather than exact, controllability statement. Theorem 1.1 does not assert that both prescribed traces are attained exactly. The density relation (1.3) states only that the set of endpoint pairs of weak solutions is dense in the product energy topology. Nevertheless, the construction contains additional information that is not visible in this density statement: the iteration is local in time. Starting from two Reynolds flows that agree near , the successive perturbations can be chosen so that their limits continue to agree on a nontrivial initial time interval. Choosing two distinct terminal targets then gives the following exact same-data consequence.
Theorem 1.2 (Nonuniqueness).
There exists a dense set such that every is the initial datum of at least two distinct weak solutions . More precisely, the two solutions may be chosen so that
for some , while .
Thus the same scheme yields exact nonuniqueness on a dense subset of the finite-energy data. The theorem does not claim nonuniqueness for every prescribed element of , and the resulting solutions are not asserted to satisfy the energy inequality.
The flexibility is incompatible with the Leray–Hopf energy inequality for suitable target pairs. Indeed, take , , and . The solution supplied by the theorem satisfies
and therefore cannot obey a nonincreasing kinetic-energy inequality. Hence the solution does not belong to the Leray–Hopf class.
The theorem gives the following small improvement over . Since
Poincaré’s inequality and Sobolev embedding give
This is a fixed-time spatial gain, rather than an estimate obtained by integrating a stronger norm in time. The class nevertheless remains far below the classical uniqueness range.
1.3 Background and related work
Leray’s classical construction [76] on , and Hopf’s construction [61] in the periodic and bounded-domain settings, give global weak solutions in
satisfying the energy inequality. Uniqueness holds under the Ladyzhenskaya–Prodi–Serrin conditions
with the usual endpoint refinements; see [88, 94, 72], and [46] for the endpoint . Quantitative refinements are discussed in [97]. The global regularity problem for smooth finite-energy data remains open [47]. For an introduction to the mathematical analysis of the Euler and Navier–Stokes equations, including the classical well-posedness theory and the Leray–Hopf framework, we refer to the book of Bedrossian and Vicol [8]. Further treatments of weak, mild, and local-energy solutions can be found in [74, 75, 99]. Our result concerns flexibility in a distributional class with finite kinetic energy and a uniform spatial-gradient bound below the energy-dissipation level; the energy inequality is not imposed.
For comparison, we recall the Cauchy theory in critical spaces. Kato [69] proved local well-posedness in and global existence for small data, while Koch and Tataru [70] extended the small-data theory to . Bourgain and Pavlović [10] proved norm inflation in , and Germain [52] studied the associated second-iterate instability. Jia and Šverák constructed forward self-similar solutions from large -homogeneous data and formulated spectral conditions for same-data nonuniqueness [67, 68]; Guillod and Šverák [59] investigated this bifurcation scenario numerically.
Convex integration originates in the geometric flexibility of Nash and Kuiper [83, 71] and Gromov [57, 58]. For incompressible Euler, the modern theory developed from the early constructions of Scheffer and Shnirelman [93, 95, 96] and the differential-inclusion framework of De Lellis and Székelyhidi [40, 42]; see also [39]. After a series of partial results, including [20, 22], Isett [64] proved the flexible part of Onsager’s conjecture [86] by constructing non-energy-conserving Euler solutions in for every . Together with the energy-conservation result of Constantin, E, and Titi [37] above the exponent , this resolved Onsager’s conjecture. Buckmaster, De Lellis, Székelyhidi, and Vicol [23] subsequently gave a considerably shorter proof of the flexible part. They also constructed solutions with any prescribed smooth positive energy profile and established an -principle in for every . Intermittent and localized variants were developed in [24, 85, 53, 54]; related developments include the two-dimensional Newton–Nash scheme [56] and the construction with prescribed generalized helicity [55]. For surveys, see [98, 28]. The relation between convex integration, intermittency, and phenomenological models of turbulence is discussed by Buckmaster and Vicol in [27]. At the level of the Euler–Reynolds system, these schemes successively replace a coarse stress by the quadratic self-interaction of a rapidly oscillating perturbation. Intermittency adds spatial concentration to this mechanism and gives estimates in Lebesgue spaces below , which are used to control the viscous error.
For the viscous problem, spatial concentration makes high-frequency errors small in spaces below . Buckmaster and Vicol [26] constructed finite-energy weak solutions on with arbitrary prescribed smooth nonnegative energy profiles. For some , these solutions satisfy
In particular, their construction implies nonuniqueness in the class of finite-energy weak solutions. Their building blocks are intermittent Beltrami waves: stationary high-frequency flows modulated by concentrated Dirichlet kernels. The resulting sub- estimates make both the Reynolds and viscous errors perturbative, while introducing several separated spatial and temporal scales.
Buckmaster, Colombo, and Vicol [21] combined convex integration with gluing. Starting from two strong Navier–Stokes solutions, they produced a weak solution agreeing with the first near the initial time and with the second near the terminal time, with the same type of uniform-in-time regularity and smoothness outside a fractal set of singular times. Their result also concerns time-uniform regularity. In our setting, however, the endpoint states are arbitrary finite-energy targets and are approximated rather than joined through prescribed strong trajectories. For comparison, Leray–Hopf solutions have a singular time set of Hausdorff dimension at most [76, 92], while the space–time partial-regularity theorem of Caffarelli, Kohn, and Nirenberg [29] controls the parabolic Hausdorff measure of the singular set for suitable weak solutions. The solutions in [21] are not suitable weak solutions, so these partial-regularity results do not apply directly. Buckmaster, Colombo, and Vicol instead proved that the singular set of times has Hausdorff dimension strictly less than (1).
Cheskidov and Luo [31] proved nonuniqueness in for every . More precisely, for every and , they constructed non-Leray–Hopf weak solutions in
Their construction combines gluing, temporal concentration, spatially intermittent Mikado flows, and a temporally oscillating corrector. The required smallness is obtained in time-integrated norms. Theorem 1.1, by contrast, requires estimates that are uniform at each time, so the principal perturbations must also provide sufficient spatial concentration.
In two dimensions, the same authors proved an -critical nonuniqueness result [32]. Their solutions are uniformly continuous in for every . This conclusion is uniform in time, as is ours, but their construction uses space–time intermittent accelerating jets, whereas the present construction uses moving Hill vortices.
Related results concern Navier–Stokes equations with fractional dissipation. Luo and Titi [77] proved nonuniqueness for the hyperviscous equation with dissipation whenever , showing the sharpness of the J.-L. Lions exponent. Nonuniqueness results in the hypodissipative regime were obtained in [35, 43]. In these works the dissipation exponent is varied. Here the standard Laplacian is fixed, and the aim is to obtain time-uniform Sobolev regularity while retaining enough spatial concentration to control the viscous error.
An inviscid result with a related endpoint statement is due to Novack and Vicol [85]. For every , their Euler solutions connect arbitrary divergence-free states up to a small endpoint error while remaining in
Their construction uses a scheme with higher-order Reynolds stresses, which are corrected through a combinatorial placement of intermittent pipe flows with optimal relative intermittency. Although the endpoint statement is close to Theorem 1.1, their equation is inviscid. In the present setting, the Laplacian of a concentrated perturbation creates an additional principal constraint and requires a different choice of scales.
A distinct route to nonuniqueness is based on spectral instability. Albritton, Bruè, and Colombo constructed two suitable Leray–Hopf solutions on with the same force and zero initial data [2]. Their argument starts from an unstable self-similar vortex-ring profile and constructs a second trajectory on its unstable manifold. Thus it gives exact nonuniqueness for a forced Cauchy problem, rather than endpoint flexibility for the unforced equation. An inner–outer gluing argument later extended the construction to the torus and smooth bounded domains [3]. This instability mechanism is based on Vishik’s construction for the forced two-dimensional Euler equations [100, 101]; see also [4] for a detailed presentation. In a different direction, Bruè and De Lellis [16] constructed forced classical Navier–Stokes solutions exhibiting anomalous dissipation in the vanishing-viscosity limit. For a different mechanism producing anomalous diffusion through fractal homogenization, see Armstrong and Vicol [7].
At critical regularity, Coiculescu and Palasek [34] proved exact nonuniqueness for the unforced equation from a particular datum in . Their nested-Mikado cascade builds on the dyadic scenario of [87] and is not a convex-integration scheme. It branches from one particular infinite-energy datum and shows that smallness is essential in the Koch–Tataru theory; this is complementary to the finite-energy endpoint flexibility obtained here. A recent preprint by Hou, Wang, and Yang [62] presents what the authors describe as a computer-assisted proof of nonuniqueness for Leray–Hopf solutions of the unforced three-dimensional Navier–Stokes equations on . This result is not used in the present paper. Ionescu, Jia, and Palasek [63] obtain a conditional result based on a candidate axisymmetric profile whose required existence remains open. For an overview of instability and convex integration, see Colombo [36]. These results concern three different forms of nonuniqueness. Instability arguments branch from a specially constructed coherent profile; critical-space cascades branch from a particular rough datum; convex integration prescribes a sequence of stresses at each stage. The resulting convex-integration solutions generally lie below the Leray–Hopf class. Theorem 1.1 should be read in this sense: it gives density of attainable endpoint traces in the finite-energy space, while the nonuniqueness statement deduced later concerns a dense set of initial data, not every datum and not the Leray–Hopf class.
The two-dimensional Euler equation provides relevant background for the moving-profile construction. Yudovich’s theorem [103] gives global well-posedness for bounded vorticity, while uniqueness for unforced solutions with vorticity merely in , , remains open. At the borderline of integrability, Bruè and Colombo [12] first constructed nonunique weak Euler solutions with uniformly bounded kinetic energy and vorticity in the Lorentz space . Buck and Modena [18, 19] subsequently extended this line to the real Hardy spaces , first for , and later, with compact spatial support, for the full range . Related results for transport equations appear in [81, 82, 80, 13, 15]; their sharpness is measured against the renormalization and well-posedness theories of DiPerna and Lions [44] and Ambrosio [5].
The present construction is based most directly on the work of Bruè, Colombo, and Kumar [14]. For
they construct a dense set of initial data in giving rise to infinitely many nonconservative weak Euler solutions in with vorticity in . Their principal perturbation is a Lamb–Chaplygin dipole concentrated in a moving ball; see [73, §165] and [79] for classical accounts of this structure. The Reynolds stress is decomposed into rank-one directions, with only one direction activated on each short time interval. The radius and speed of the dipole are coupled to the coefficient of that stress component, while its motion along a long rational trajectory converts a localized source into the directional flux required for cancellation. This dynamical use of a traveling coherent structure is also used in the present paper. The passage from that construction to three-dimensional Navier–Stokes is not formal. A planar dipole carries scalar vorticity and travels in a preferred direction, whereas Hill’s vortex is an axisymmetric three-dimensional velocity field whose gradient must be estimated in all directions. Moreover, rescaling the core simultaneously changes its energy, its gradient, its transport speed, and the size of the viscous defect. Balancing these effects is what produces the exponent near and distinguishes the present iteration from its Euler precursor.
For SQG, the weak existence theory was developed in [90, 78]. Buckmaster, Shkoller, and Vicol [25] constructed the first nonunique weak solutions of the unforced equation, and Isett and Ma [66] later gave a direct scalar-level construction. In related work, Bruè, Jin, and Nguyen [17] develop a moving-profile convex-integration scheme for the inviscid SQG equation on . For the explicit, nonoptimized exponent , their construction approximately connects any two prescribed mean-zero states in by a momentum weak solution in . It also gives nonuniqueness for a dense subset of the mean-zero space . The scheme uses localized traveling SQG profiles whose centers move along rational directions, and a bilinear null-form estimate controls the derivative loss caused by the nonlocal relation .
The present paper follows the moving-profile strategy introduced by Bruè, Colombo, and Kumar [14] for the two-dimensional Euler equations. In passing to the three-dimensional viscous setting, the Lamb–Chaplygin dipoles used there are replaced by Hill’s spherical vortex, control of the scalar vorticity is replaced by control of the full velocity gradient, and viscosity introduces an additional error at every stage of the iteration. The related SQG work is a separate adaptation of the same general strategy and is not used in the proof of the present paper.
1.4 Moving Hill vortices and the critical scaling
Our construction uses a dynamical cancellation. Hill’s vortex is an exact traveling Euler flow, so transport and self-interaction cancel before antidivergence. After localization, motion along a rational orbit converts the remaining source into a directional stress after time averaging. The Hill scaling preserves the -norm and the -gradient norm, and disjoint time scheduling removes interactions between principal directions.
The Hill profile.
Hill’s spherical vortex [60, 73] is an axisymmetric, no-swirl traveling Euler flow whose azimuthal vorticity is supported in a ball. Its orbital and linear stability under axisymmetric perturbations were studied in [33, 89]; these results are not used below.
After rotation and normalization, the profile satisfies
Its exterior potential-doublet form permits localization without changing the core; see Figure 2.
For , define
The core radius is , the velocity amplitude is , and
Here and . Hence the energy and the -gradient norm are invariant, in agreement with . For , however,
so concentration creates a loss that must be offset by the amplitude and averaging parameters.
This Hill threshold differs from the Navier–Stokes scaling threshold. Under
one has
Thus the scale-invariant exponent is . Our theorem crosses the Hill threshold but remains supercritical for Navier–Stokes.
On , cutoff and mollification give a smooth compactly supported profile . For
we introduce the Helmholtz correction
Then is divergence free. Choosing the intrinsic trajectory
cancels the leading transport and Euler terms. With
The block then satisfies schematically
| (1.4) |
where contains the remaining block errors.
The viscous contribution is written as the symmetric stress
It is estimated at an auxiliary exponent , where ; the limiting gradient is instead measured at .
1.5 Strategy of the construction
A smooth Reynolds flow encodes the endpoint data, and an iteration removes its defect with localized Hill vortices moving along rational trajectories. At each stage, the stress is frozen on short time cells and decomposed into finitely many rank-one tensors. A moving Hill block treats each tensor, while a temporal corrector converts the resulting time-averaged cancellation into a pointwise identity.
The zeroth Reynolds flow and the iteration
The iteration is formulated for the Navier–Stokes–Reynolds system
After mollifying , we add the Hill blocks and a temporal corrector. The principal blocks cancel the frozen part of ; all remaining terms, including mollification, modulation, viscosity, and interactions with the coarse velocity, are placed in . The estimates give in , summable increments, and a common gradient bound. Hence
The endpoint fields enter only at the initial stage. Given , we mollify them at a common scale and choose a smooth cutoff that equals one near and zero near . We then set
Its defect is placed in a symmetric Reynolds stress using .
The blocks and corrector vanish at cell interfaces, including . Thus
These errors are summable. Suitable choices of and then give the endpoint approximation.
Stress decomposition and moving Hill blocks
The geometric lemma decomposes the mollified stress, up to pressure, into nine positive rank-one pieces:
The positivity of the coefficients permits them to be encoded in the radius and residence time of a Hill vortex. Each time cell is divided into nine disjoint subintervals, one for each direction, and the corresponding coefficient is frozen in time as . This scheduling also removes the leading quadratic interactions between different directions.
Let
be the base concentration parameter at stage ; the complete parameter hierarchy is stated in (1.6) below. For one coefficient and direction , set
We orient the profile by and define
The center follows
Thus couples the stress coefficient to the Hill scale, whose physical core radius is , and the trajectory preserves the exact Hill cancellation. The normalization of compensates for the fact that the direction is active only during one ninth of the cell. Moreover, the speed is inversely proportional to : the vortex spends more time in regions where the coefficient is larger, which is the basis of the stress reconstruction below.
Reconstruction of the stress by time averages
The source in (1.4) is first replaced by a smooth auxiliary density of mass . The difference has zero spatial mean and can therefore be written as a divergence with an inverse-frequency gain. Integration by parts along the trajectory converts the auxiliary source into a directional tensor flux. Since the speed is proportional to , the residence time recovers the coefficient , giving
| (1.5) |
A rational trajectory closes on the torus and can be repeated many times during one active interval. The freezing error is , while the factor controls incomplete periods and spatial variation; see Figure 3.
The temporal corrector and the new stress
The orbit identity cancels the stress only after averaging over a time cell. To restore the equation pointwise in time, sum the nine sources into and define
where is the Leray projection. Since the integrand has zero cell average, vanishes at both endpoints and gains the short factor . Its time derivative cancels the zero-average source, while the cell average cancels the frozen stress through (1.5). The factor makes smaller than the principal blocks in both the energy and gradient estimates.
The new stress contains the coarse-flow, corrector, freezing, source-replacement, localization, viscous, and intrinsic block errors. They are estimated separately because they use different features of the construction: concentration, inverse frequency, or the short time-cell factor. Their bounds make the stress decay and the increments summable, while endpoint vanishing preserves the prescribed traces.
1.6 Crossing the Hill threshold and analytical difficulties
Competing effects of concentration
The main difficulty is that concentration has opposite effects on the estimates. For an energy-sized Hill block,
Thus small improves the intrinsic and viscous errors below , but increases the gradient norm above . We use for the block errors, close to one for source replacement, and for the limiting gradient. Short time cells reduce the freezing and corrector errors, but must still contain enough complete rational orbits to average the stress.
The main parameters are
| (1.6) |
Here is the stress level, the concentration parameter, and the cell length. The rapid growth of separates consecutive stages, whereas the small exponent makes the stress decrease slowly enough to absorb the loss above the Hill threshold.
We take , for which . Together with the intrinsic block choices and , this gives a positive power of the Hill scale in the intrinsic and viscous estimates. The source-replacement error is treated at close to one. The difference between the Hill source and the auxiliary source has zero mean, so a localized antidivergence produces an inverse-frequency gain; choosing near one keeps the associated concentration loss small.
The balance above
For the final exponent, set
A principal block has amplitude , while its smallest Hill parameter is and its smallest physical core radius is . Therefore
Its summability requires
The factor must compensate for the concentration loss. This explains why increasing either or makes the argument harder.
There is also a restriction from time averaging. Short cells improve the freezing error and the temporal primitive, but a cell must be long enough for the vortex to complete the required orbit periods. The orbit and temporal-corrector estimates impose the following sufficient conditions, respectively,
These restrictions are compatible for
and . This small gain above reflects the limited margin between the concentration loss and the orbit and corrector constraints. Temporal concentration cannot replace this balance: it improves time-integrated norms but does not reduce the required norm.
Localization, background interaction, and time continuity
Several further errors must be controlled. Localization and mollification create commutators, while the Helmholtz correction restores incompressibility after cutting off the exterior potential. The intrinsic Hill motion also produces an interaction with the coarse velocity. For a principal increment , concentration gives schematically
This must be smaller than the next stress level. The disjoint time scheduling removes the leading interactions between different principal directions, while orbit averaging, freezing, and the short temporal primitive control the remaining terms.
Finally, for some , the iteration provides estimates of the form
The first estimate gives strong convergence in ; the second provides a common time modulus for the gradients. Together they yield and . A uniform fixed-time gradient bound alone would not give this time continuity.
1.7 Organization of the paper
The remainder of the paper is organized as follows. Section 2 recalls the normalized Hill vortex and establishes estimates for its rescaled, localized, and mollified forms. Section 3 introduces the moving Hill block and derives the associated Euler and Navier–Stokes defect identities. Section 4 states the iteration step and constructs the next Reynolds flow, including the decomposition of the Reynolds stress, the time partition, the space-dependent scales, the vortex trajectories, the auxiliary source, and the temporal corrector. Section 5 proves the estimates required for the iteration and verifies the parameter restrictions. Section 6 constructs the initial Reynolds flow, passes to the limit, and proves Theorems 1.1 and 1.2. Section 7 discusses the limitations of the method and possible modifications. Section 8 presents further directions and open problems.
2 Hill’s spherical vortex
Hill’s spherical vortex is an axisymmetric, no-swirl solution of the three-dimensional Euler equations whose vorticity is supported in a ball and which translates without changing shape. It was introduced by Hill [60]; see also Lamb [73, §165] for the classical formulas and Choi [33] for a modern treatment of its orbital stability in the axisymmetric no-swirl class. Only the explicit traveling-wave structure is used below.
We record the profile carefully because three features enter the convex-integration scheme with their precise normalization: the translation speed, the directional integral of the localized velocity, and the potential character of the exterior field. We first write the classical vortex in a frame in which the spherical core is stationary, then remove the constant velocity at infinity to obtain a decaying traveling profile. The following subsection rescales and rotates this unit profile and truncates its exterior potential without changing the vorticity core. Here denotes a rank-one stress direction. Also, denotes a rotation, whereas is the temporal corrector introduced in Section 4.
Let be spherical coordinates with the axis of propagation along the -axis. In this preliminary description, denotes the spherical radius; it should not be confused with the concentration parameters introduced later. Thus
where is the cylindrical radius. The flow is axisymmetric and has no swirl; hence
An axisymmetric no-swirl incompressible velocity is represented by its Stokes stream function , with
For a Hill vortex of radius and translation speed , we use the sign convention
These formulas agree, up to the choice of propagation direction, with the classical formulas in [60]; see also [73, §165] for the normalization used here.
The corresponding velocity components are
The vorticity is purely azimuthal:
with
In particular, in the normalization used here, the relative vorticity is
Thus the vorticity is compactly supported even though the induced velocity has a noncompact potential tail.
These formulas describe a stationary field in the co-moving frame. In that frame the velocity is an exact steady solution of the incompressible Euler equations,
For , the co-moving velocity tends to at infinity. Subtracting this constant far-field velocity gives the decaying laboratory-frame profile
Since , the steady Euler equation becomes, in the sense of distributions,
Thus travels in the direction .
In spherical coordinates, let , , and denote the radial, polar, and azimuthal unit vectors, respectively. Since has no azimuthal component, it is determined by
For , the profile coincides with the three-dimensional potential doublet , where .
Remark 2.1.
In Cartesian coordinates, is given by
Thus and is smooth on .
We shall use four consequences of these formulas. The field is a finite-energy divergence-free traveling Euler profile; its vorticity is confined to ; its exterior velocity is the gradient ; and its only loss of smoothness occurs across . The potential representation permits us to remove the long-range tail by a cutoff. Since the profile is only Lipschitz across the spherical interface, we subsequently mollify it to obtain the required higher-derivative estimates.
2.1 Scaled Hill vortex profile
We first introduce the spatial and amplitude scalings used in the construction. The spatial scale of the vorticity core is , whereas the amplitude is . This preserves the -size of the profile and changes its traveling speed from one to . We then cut off the irrotational exterior field at the larger scale . Since , this localization does not alter the vorticity core.
For , define the rescaled Hill profile by
Then
| (2.1) |
More generally, for , choose with , and define
The definition is independent of the particular choice of , because the Hill profile is axisymmetric about . The field is oriented along , travels intrinsically in the direction , and satisfies
Equivalently,
is a traveling Euler solution whose center moves with velocity .
Fix and . Let be radial, with on , on , and . Set
Since , the transition annulus
lies strictly outside the spherical vorticity core. For , the rescaled profile is a gradient. Indeed, the -homogeneity of gives
The scalar potential and the localized Hill profile are therefore defined by
| (2.2) |
Although is singular at the origin, is smooth because vanishes in a neighborhood of the origin. Thus on , while on . In particular, the gradient correction preserves the vorticity exactly:
It introduces only a divergence error in the annulus . Since on ,
2.2 Estimates for the building block
We collect the estimates for the localized profile. The first lemma records its support, Lebesgue norms, derivative bounds, and directional integral. We then derive the approximate traveling equation and the identity obtained by differentiating in , and finally mollify the spherical interface.
Lemma 2.3.
The fields and , defined in (2.2), satisfy the following properties, with constants independent of . The constants may depend on , , and the cutoff , and also on the displayed Lebesgue exponent.
- 1.
The localization identities are
Consequently, and .
- 2.
and for every .
- 3.
For every , ,
- 4.
(2.3)
Proof.
The identities in Part 1 follow from the definition of the cutoff and the exterior formula .
For the norm estimates, the explicit formulas for and give, for ,
| (2.4) |
where the estimate for is understood away from the interface. Moreover, on the support of a derivative of one has . Hence, for ,
| (2.5) |
Combining (2.4) and (2.5), we obtain
| (2.6) |
again with understood away from . Integrating (2.6) in polar coordinates proves the -bounds in Parts 2 and 3. At , the exterior contribution to is , which accounts for the factor .
It remains to estimate the divergence. On , , while and . Thus
which gives . The warning concerning the second derivative is essential: is Lipschitz across the spherical interface, but it need not have a classical second derivative there. The mollification below removes this singularity.
Finally, compact support of and integration by parts give, componentwise,
Write . Since and , the last line equals
The radial integral is one. The first two angular components vanish, and the third is
This proves (2.3). ∎
The next proposition shows that the truncated block satisfies the traveling Euler-profile equation up to error terms. We also compute , because the scale varies along the moving trajectory. We use the following Bogovskiĭ notation; see [9, 51] and, for the scaling-invariant bound used below, [1]. If is a vector field supported in a ball and for each , we define the componentwise Bogovskiĭ tensor by
It is extended by zero outside and satisfies
This componentwise tensor is not required to be symmetric; symmetry is restored later by the symmetric inverse-divergence operator on the torus.
Proposition 2.4.
Let . Then the truncated block satisfies the following identities in the sense of distributions on .
| (2.7) |
| (2.8) |
where the error and pressure terms have the following properties:
- 1.
After fixing the additive constant in ,
- 2.
For every , and .
- 3.
and, away from the spherical interface,
Proof.
The calculation follows the localization mechanism in [14, Proposition 2.1]. Since and satisfies (2.1), we have
We use the identity
The vector field is supported in . To apply , we verify that it has zero mean. The identity
and the exterior decay show, by integration over and passage to the limit , that
Indeed, the boundary flux is . Thus every component of satisfies the compatibility condition for the componentwise Bogovskiĭ operator.
On the exterior of , we have and . The potential-flow form of (2.1) therefore implies there. We fix the additive constant so that in the exterior. The stated support properties of and now follow from the support-preserving property of .
The support of lies in by Lemma 2.3. On this annulus,
Since , it follows that
The scale- Bogovskiĭ estimate then yields
Combining the preceding estimates with (2.9) proves the bound for .
Corollary 2.5 (Mollified Hill block).
Fix and a radial function such that and . Set
Then , and there exist such that
| (2.11) | ||||
| (2.12) |
Moreover,
and
| (2.13) |
For every , the mollified profile also satisfies
and
At , the corresponding endpoint estimates are
The fields , , , , and are supported in , and
Proof.
Mollifying (2.7) in space gives (2.11) with
and
Young’s convolution inequality gives . Set
Then
Here we used precisely the stated choice of . Since and ,
This proves the estimate for .
We next compute the derivative with respect to . Since the mollification scale depends on ,
Mollifying (2.8) gives
For vector fields , define the second-order tensor by , and set
A direct differentiation of the rescaled kernel gives
Consequently,
Thus (2.12) holds with
The kernel satisfies and . Hence
We used in the last inequality. Similarly,
Since and ,
Thus this term satisfies the bound asserted in (2.13). Because is only Lipschitz, two derivatives cannot be taken uniformly across the spherical interface before mollification. Instead, we place one derivative on the mollifier:
Together with the preceding estimates and Young’s inequality, this proves all asserted bounds for and .
The estimates for follow from Lemma 2.3; for the second derivative, use
Convolution preserves the integral. Finally, implies , so convolution enlarges each support by at most ; this yields the stated support in . ∎
3 The moving Hill block
We now modulate the amplitude and scale of the localized Hill profile and translate its center along a time-dependent trajectory. The velocity of the center is chosen to match the intrinsic traveling speed of the profile; this cancels the leading transport term against the quadratic Euler term. Scale and amplitude modulation leave a distinguished vector source whose spatial mean is prescribed by (2.3). All remaining terms are placed in a symmetric stress. A Helmholtz correction restores incompressibility, and the final corollary incorporates viscosity.
Proposition 3.1 (Moving Hill block).
Let be an interval, fix and , and choose
as in Corollary 2.5. Shrinking if necessary, assume
Let
Choose and , and let solve
| (3.1) |
Set .
Define the principal block
| (3.2) |
We suppress the parameters and on the pressure and error terms when no confusion can arise. The profile identities are
The support condition on allows the compactly supported Euclidean profiles to be periodized on without overlap between distinct copies.
Since is periodic,
so the periodic inverse Laplacian below is well defined on . To restore incompressibility on , define
Then
for every , and
| (3.3) |
where is a symmetric matrix field. The following estimates hold:
- 1.
The stress satisfies
where
- 2.
For every , the displayed spatial estimates below are understood uniformly in ; all powers of the variable are taken in , and all unlabelled norms of are over :
- 3.
For every , , and
In particular,
Thus the block is not itself mean zero; the distinguished vector source in (3.3) is exactly the time derivative of its spatial mean.
Proof.
Write . Differentiating (3.2) gives
| (3.4) |
Moreover,
By Corollary 2.5,
The scale derivative satisfies
Combining these identities with the trajectory equation (3.1), the transport term cancels and we obtain
| (3.5) |
where all profiles on the right are evaluated at , and
Since , this term can be absorbed into the pressure. Let denote the symmetric inverse-divergence operator on introduced in [42]; we use its and order- bounds in the form established in [23, 26]. The vector field has zero spatial mean, and hence
Define
| (3.6) |
The tensor is symmetric. Adding the equation for to (3.5) now proves (3.3).
It remains to establish the estimates. The chain rule and (3.1) give
| (3.7) |
We use two complementary bounds for the Helmholtz correction. For every , Calderón–Zygmund boundedness gives
while Poincaré’s inequality and the definition of give
In particular, at ,
The first of the two correction bounds also implies . Therefore,
| (3.9) |
For the remaining estimates, fix . The profile estimates in Corollary 2.5 give
The Calderón–Zygmund bounds for the Helmholtz projection give
It remains to estimate the two time derivatives of . Equation (3.4) and Corollary 2.5 yield, at each fixed ,
and
In the last two estimates we used and to dominate the pressure terms by the displayed powers of . Using (3.7) in the form
together with , gives the asserted time-derivative bounds. The -estimates follow from the -bounds because .
The final assertion follows from Corollary 2.5 and is unchanged by periodization. ∎
Corollary 3.2 (Navier–Stokes moving Hill block).
Under the assumptions of Proposition 3.1, the divergence-free block satisfies
| (3.10) |
where is symmetric and satisfies
4 The iteration step
We carry out one stage of the Navier–Stokes–Reynolds iteration. Starting from an admissible triple , we regularize the background flow, decompose the mollified stress into rank-one components, and assign each component to a moving Hill block on a short time interval. An auxiliary source and a temporal corrector then convert the orbit-averaged cancellation into a pointwise-in-time equation. Here admissible means that the velocity is continuous in time and the triple is smooth in the interior of each time cell, with bounded one-sided derivatives at the cell interfaces; the Navier–Stokes–Reynolds system is understood distributionally. This class is preserved by the construction below and becomes smooth after the mollification at the beginning of the next stage.
To avoid boundary artifacts in the space–time convolution, all triples are constructed on a fixed open interval , and the iteration is restricted to only after mollification. All time-dependent estimates below are understood on ; this harmless convention will not be repeated.
We begin by fixing the parameter hierarchy. At the th stage, controls the density of the rational orbits, measures the Reynolds stress, is the base concentration scale, and is the length of a time cell. For , set
The constants are positive, while depends on the initial data and will be chosen sufficiently large. We also take , , and to be integers. For the intrinsic moving-block estimates we fix, throughout this section,
| (4.1) |
The numerical choices of the remaining parameters, and the verification of all exponent inequalities, are given in the parameter-selection subsection 5.3 below.
Suppose that the Navier–Stokes–Reynolds system at the th stage is
| (4.2) | ||||
The triple is admissible on , and the induction assumptions are
| (4.3) |
Here is fixed in the parameter selection below.
Proposition 4.1.
4.1 Mollification step
We regularize the background flow and Reynolds stress at a space–time scale . This provides the derivative bounds needed to define the space-dependent radii and trajectories of the vortex cores. The commutator generated by mollifying the nonlinear term is included in the new Reynolds stress. Fix a sufficiently small absolute constant and set
Let be a smooth space–time mollifier on , where is supported in the unit space–time ball, and set
| (4.4) |
Then solves (4.2) and satisfies
Here the last inequality follows from and the definition of . This verifies that the smaller scale still controls the mollification commutator.
We also check the inverse powers of . At the initial triple is fixed and smooth before is chosen, so the following bounds hold after increasing . For , we use and to obtain
In the last inequalities we used . Thus all subsequent bounds involving powers of retain the exponents used below.
4.2 Error decomposition
The decomposition of a symmetric matrix into nine positive rank-one components is the geometric lemma of [83, 42, 23]. The refinement producing directions with rational component ratios and orbit periods comparable to follows [14]; the perturbation matrix and the density argument in item (i) below are specific to the present three-dimensional setting.
We resolve the mollified Reynolds stress, up to a scalar pressure, into finitely many positive rank-one components. The directions are chosen to have rational components, periods comparable to , and -dense trajectories; they will later determine the trajectories of the moving vortex cores. The positive coefficients determine both the amplitudes and the spatial scales of the corresponding perturbations.
Lemma 4.2 (Error Decomposition).
Given and , there exist unit vectors , , such that, for every , the following statements hold.
- (i)
The curve on has minimal period for some , and its image is -dense in , where is independent of and .
- (ii)
The following decomposition holds:
(4.5) - (iii)
The functions are smooth and satisfy
(4.6)
Proof.
Define the following nine unit vectors:
For a symmetric matrix , use the decomposition
| (4.7) |
where are smooth functions given by
If , then , and .
Put , and let denote the matrix
Define vectors , whose component ratios are rational, by
To verify item (i), write
so that , and set
where
Then is parallel to , and hence . For example,
The vectors need not themselves be primitive. If denotes the greatest common divisor of their components, a direct calculation gives
Thus , and has relatively prime components. In particular,
Since is orthogonal, , and , the columns of and the reverse triangle inequality give, for ,
Since is primitive, the minimal period is
As and , we have
This proves the period assertion in item (i) without any parity assumption on .
It remains to verify the density assertion. Notice first that and have the same annihilator lattice. A direct computation gives
so span for every . If satisfies , then
The three scalar products are integers. If and , then
a contradiction. Hence . If , then , again a contradiction. Thus is orthogonal to , and hence . Consequently,
Let be the orthogonal projection onto . The dual of the two-dimensional lattice is . The standard two-dimensional transference estimate for the covering radius therefore gives
For a symmetric matrix , apply (4.7) to and multiply on the left by and on the right by . This gives
| (4.8) |
Since , the condition and the choice
ensure that
Thus the argument of every used below lies in the positivity neighborhood of the geometric decomposition.
Next, we define
It follows that
Thus item (ii) holds. The bounds , together with , give , and hence the stated lower bound. Moreover, ; using gives the claimed -estimate. Finally, differentiating the formula for , using , and applying (4.8) gives
∎
4.3 Time partition and cutoff functions
The nine directions from Lemma 4.2 are activated successively, thereby avoiding interactions between distinct directional families. We partition time into cells and divide each cell into nine subintervals, one for each direction. On every cell the coefficients are frozen at their temporal averages; the resulting discrepancy will later be included in the temporal error. Smooth cutoffs make the perturbations vanish near the endpoints of their active intervals.
Because , set and partition the time axis into cells
Only the finitely many cells meeting enter the construction on that interval. The integrality assumption makes both and cell interfaces.
Each interval is further divided into nine subintervals of equal length:
Thus . For the cutoff construction, we also use the slightly shorter interval
| (4.9) |
We use the coefficients from Lemma 4.2 and denote their time averages by
Equation (4.6) gives
| (4.10) |
Moreover,
Thus the freezing error is small when is sufficiently small.
For and , choose a smooth cutoff such that , on , and
| (4.11) |
4.4 Space-dependent vortex scale
We couple the radius of each core to the local size of the corresponding frozen stress coefficient. This choice produces the weighted orbit average needed to recover the tensor , while determines the overall concentration scale. The separation condition below ensures that the localized cores remain narrower than the spacing of the rational orbits. We set
| (4.12) |
Because , we choose small enough that
| (4.13) |
Thus the diameter of every principal core is at most the geometric spacing scale . In particular, the Hill source and the auxiliary source introduced below are contained, after a common translation, in a ball of radius .
4.5 Trajectory of the vortex core
We next choose the amplitude and trajectory of each core. The amplitude is normalized by the spatial mean of , while the center moves at the intrinsic Hill speed in the direction . The initial point is selected so that the average of along one rational orbit agrees with its torus average. This normalization produces the desired directional stress after time averaging.
The cutoff used in Proposition 3.1 is the scalar multiple of given by
where is chosen to produce exact cancellation:
| (4.14) |
The bounds for follow from (4.10). This value is chosen now so that the averaged rank-one tensor has the required normalization in the cancellation below.
Next, we define the trajectory of the center of the core as
| (4.15) |
For later use, set
Set and choose so that
Such a point exists: the orbit-average on the left is a continuous function on the connected quotient of by the closed -orbit, and its average over that quotient is precisely the spatial mean of . It must therefore attain that mean.
Solve the ODE (4.15) forward and backward from to obtain a trajectory on the whole interval . We impose
| (4.16) |
where is a sufficiently large absolute constant. This condition is verified uniformly, including at , in Section 5.3.
On the plateau where , the trajectory is periodic with period
| (4.17) |
Condition (4.16) is intended to guarantee that many complete periods lie inside . Let be the largest nonnegative integer such that
By the maximality of , the completed periods differ from by at most the two cutoff layers and one additional period:
| (4.18) |
4.6 Estimates of the building block
We apply Corollary 3.2 with its intrinsic exponent set equal to from (4.1). We take profile direction , amplitude , radius , and center . The sign is determined by the normalization of the Hill impulse: with this choice the resulting block moves and has impulse in the direction. It satisfies
| (4.19) |
With these choices of radius and amplitude, Proposition 3.1 and Corollary 3.2 give the following estimates. Since ,
Using the bounds for , , and , we obtain
| (4.20) |
The velocity satisfies
| (4.21) | ||||
| (4.22) |
For , the exponent is nonnegative. Using the upper bound for , we obtain
| (4.23) |
For , the exponent is negative. Using , we instead obtain
| (4.24) |
The following time-derivative bounds hold for every .
| (4.25) |
4.7 Auxiliary building block
The source generated by the moving Hill block has the correct spatial mean but remains concentrated at the core scale. To compare its time average with the prescribed rank-one stress, we replace it by an orbit-adapted auxiliary source. Its profile is normalized both in space and along the rational trajectory, so that its time average recovers up to a small error tensor. The difference between the original and auxiliary sources will be handled by a symmetric antidivergence. For each , define
| (4.27) |
Extend by zero and set the locally finite sum
Each component replaces the corresponding concentrated Hill source
The auxiliary profile is chosen so that the antidivergence of the difference between these two sources is small. In addition, has the following properties:
- (i)
The profile has mass , matching the impulse of :
(4.28) - (ii)
For every , its full-orbit average satisfies
(4.29) - (iii)
, and for every ,
(4.30)
Only these normalization, orbit-average, and localization properties are used below. For completeness, we recall the standard normalized periodization construction from [14]. The special rational geodesics chosen in Lemma 4.2 are -dense, with a uniform constant . Choose a nonnegative that is strictly positive on . We regard the rescaled bump below as a function on by -periodization and set
Define the orbit average without inserting the initial translation,
| (4.31) |
The covering property of the orbit gives and . Moreover, is invariant under translation along the -orbit. Consequently, averaging cancels the denominator in (4.31) and proves (4.29). Fubini’s theorem then yields (4.28), while the quotient rule and the support of give (4.30).
Proposition 4.3.
Let be the locally finite sum defined above. Then
| (4.32) |
Moreover, for every and , there exists a smooth symmetric tensor such that
| (4.33) |
| (4.34) |
Proof of Proposition 4.3.
The definition (4.27) of and (4.30) imply, for every ,
| (4.35) |
Using (4.12), (4.14), and (4.11), we estimate the supremum in (4.7), for every , by
| (4.36) |
For the second term we used , while (4.16) controls the first term. Combining this estimate with (4.7) proves (4.32).
Next, we write
| (4.38) |
The tensor contributes to . By (4.30),
| (4.39) |
Next, we investigate the main term . Make the change of variables , determined by and . Then
This change of variables gives
| (4.40) |
where is the main term and will be part of the error . By (4.29), we rewrite the main term as
| (4.41) |
| (4.42) |
4.8 The temporal corrector
The auxiliary source cancels the Reynolds stress only after averaging over a complete time cell. We therefore introduce a temporal corrector as the primitive of its zero-mean oscillatory part. The cellwise cancellation confines this primitive to an interval of length at most , producing the small factor needed in the estimates, while the Leray projection preserves incompressibility. Here , where is the inverse Laplacian on the periodic domain , acting on mean-zero scalar functions. Define by
| (4.44) |
The integrand in (4.44) has zero integral over every complete cell . Consequently, only the current cell contributes to the primitive, and its effective time length is at most .
| (4.45) |
In particular, and vanish at every cell interface. Their time derivatives may have bounded jumps there, so is continuous and piecewise smooth, in agreement with the admissibility convention at the beginning of this section. Since the velocity itself is continuous, these jumps create no temporal Dirac masses in the distributional equation.
These estimates hold for every and . Equation (4.44) also gives
| (4.47) |
Similarly,
| (4.48) |
4.9 Construction of the next Reynolds flow
All components of the perturbation are now available. We add the moving Hill blocks and the temporal corrector to the mollified background flow. Substitution into the equation produces the next Navier–Stokes–Reynolds system, with the remaining terms grouped into the linear interaction, corrector, temporal-freezing, source-replacement, and building-block errors.
Define the velocity field by
| (4.49) |
Here the main velocity perturbation is
The fields are the adapted building blocks, and is the temporal corrector constructed above.
Remark 4.4.
We define the new pressure field as
Here , , and are defined in (4.4), (4.5), and (4.19), respectively. The last term is the gradient part of the temporal-corrector source. The locally finite pressure sum is defined up to a function of time. The fields and satisfy the Navier–Stokes–Reynolds system distributionally with stress
| (4.51) |
Here is defined in (4.19) and in Proposition 4.3. The stress contains terms linear in the principal perturbation, whereas contains the temporal-corrector terms:
Finally, for , define as the coefficient-freezing error and as the source-replacement error:
The impulse identity for the Hill source and (4.28) give
so the standard symmetric inverse-divergence on the torus is applicable. By (4.13) and property (iii) of , both terms are supported in a common ball of radius . Poincaré’s inequality on that ball gives ; the order- estimate for therefore yields, for ,
Finally, substituting (4.19), (4.44), (4.33), and (4.5) into (4.49) gives (4.2) with the stress (4.51); the signs of and of the pressure correction are exactly those dictated by (4.5).
5 Proof of Proposition 4.1
We verify the conclusions of Proposition 4.1. We first control the velocity increment and its space–time regularity, then estimate each component of the new Reynolds stress, and finally choose the parameters so that all the resulting inequalities hold simultaneously.
5.1 Velocity estimates
We begin with the bounds for the new velocity. The estimate controls the size of the increment, the estimate propagates the target gradient regularity, and the derivative estimates preserve the inductive bound. Each estimate yields an explicit restriction on the iteration parameters. By (4.50), (4.22), and (4.8),
At each time, at most one pair is active. Hence the norm of the sum of moving blocks is controlled by the supremum over , as used below.
To obtain , it is sufficient that
| (5.1) |
Moreover,
provided that is sufficiently large.
Remark 5.1.
For , the same argument gives the following -bound:
Since has finite length, this also implies, for every time exponent ,
This formulation avoids incorrectly replacing the -norm of the sum over all time cells by the supremum of the individual cellwise -norms.
The perturbation also preserves the zero-mean condition. Indeed, Proposition 3.1 and the choice give
On the other hand, (4.28) and (4.27) show that . The cell average of this spatial mean vanishes because vanishes at the endpoints of its support. Taking the spatial mean in (4.44) therefore yields
on the active subinterval, and zero elsewhere. Thus has zero spatial mean; since mollification preserves the mean, so does .
Remark 5.2.
For an exponent slightly larger than , the power of is negative; hence one must use (4.24), rather than (4.23). Because is much smaller than , this loss restricts the attainable exponent. More precisely,
A gain by follows if
| (5.3) |
Taking instead gives
To keep the induction assumption , we need
| (5.4) |
We now justify the Hölder continuity in time without hiding any exponent loss. Set
Thus . For every Banach-valued function that is continuous and piecewise ,
This estimate applies globally here: the supports of the are disjoint in time, each vanishes at the endpoints of its support, and vanishes at the cell interfaces. Using (4.23), (4.26), (4.8), and (4.48), we obtain
Both exponents are negative when is sufficiently small, by (5.2).
For the target exponent , set and introduce the two positive margins
Their positivity is precisely (5.3). The same interpolation then gives
The displayed powers of are retained explicitly. Once the base frequency is fixed they are independent of ; the first stage is a single finite term, and the strict negative powers of control the summability of all later stages. Choose so small that all four exponents above are strictly negative. Since is a fixed multiple of , there is then a , independent of , such that the preceding bound and the already established bound yield
Here may depend on the fixed base frequency , but is independent of . This dependence is harmless because is fixed throughout the iteration.
We apply this general estimate with . The bound therefore requires
| (5.5) |
5.2 Reynolds-stress estimates
We estimate the components of the Reynolds stress defined in the preceding section. Each component will be bounded by a fixed fraction of the target level . We treat successively the linear interaction, the temporal corrector, the freezing and source-replacement errors, and the intrinsic errors of the moving blocks.
By (4.21), Poincaré’s inequality, and Hölder’s inequality,
When this and the other terms containing are compared with , we use the exact ratio
Thus the retained factor is favorable, and the displayed exponent inequalities remain sufficient. After choosing sufficiently large to absorb the fixed constant, the bound follows from the exponent inequality
| (5.6) |
For the corrector stress, we estimate
It is therefore sufficient that
| (5.7) |
For the coefficient-freezing error,
where the last inequality follows from (5.7).
Choose an exponent for the source-replacement estimate, independently of the exponent used in Proposition 3.1. From Proposition 3.1, (4.36), and (4.30),
Since , the preceding bound controls the required stress. It closes provided
| (5.8) |
Both inequalities hold by taking sufficiently close to one. It remains to use (4.20) and (4.34) for the building-block and averaging errors:
| (5.9) | ||||
At a fixed time there are four global error tensors, at most one active tensor , and nine static tensors on the current time cell. Consequently, after increasing once more to absorb all fixed constants,
5.3 Choice of parameters
We collect the restrictions obtained above and exhibit one choice for which they are all strict. We distinguish the intrinsic block exponent , the source-replacement exponent , and the final regularity exponent , since these exponents enter different estimates. The geometric condition (4.13) gives
For (4.16), the fixed prefactor in must also be retained. Indeed,
Thus the stronger first-stage condition
is sufficient uniformly for every after increasing . We next collect (5.1), (5.2),(5.4), (5.5)–(5.9). Since is a positive integer, (5.7) implies (5.1) and (5.2). The remaining restrictions reduce to
These conditions are supplemented by the two source-exponent inequalities in (5.8). We first choose , , , , and . For the intrinsic block estimates, set and . Then
and we choose . Independently, take in (5.8). The two geometric left-hand sides are approximately and . Moreover,
which verifies (4.16), also for , once is sufficiently large. The inequalities that become less favorable when is increased have the values
The two source-exponent left-hand sides in (5.8) are approximately and , both below . The bounds in (5.6), (5.7), and the -part of (5.9) have exponents , , and , respectively. The two -dependent exponents in the -part of (5.9) are and . Hence all of these exponents are strictly below , and direct substitution verifies the remaining strict inequalities as well.
For the final exponent , the gradient estimates impose the additional restrictions in (5.3), namely
For , , , , and , both inequalities are strict when : their left-hand sides are approximately and , respectively. In particular, the positive interpolation margins remain available, and the corresponding time Hölder exponent may still be chosen sufficiently small.
6 Proof of the main theorem
We first construct a smooth Reynolds solution on the fixed interval that approximates the two prescribed endpoint fields. Consider
| (6.1) |
where is symmetric.
Fix , and let be a standard spatial mollifier. Choose such that
Let be a symmetric inverse-divergence operator on the torus, normalized so that
Proposition 6.1 (Smooth initialization).
Define
| (6.2) | ||||
| (6.3) |
Then is a smooth solution of (6.1) on . Moreover, for every , there exists such that
| (6.4) |
Proof.
After and have been fixed, all relevant norms of the initial triple are finite. By increasing , we may arrange
Thus satisfies the induction hypotheses at level .
We use the following compactness statement.
Proposition 6.2 (Compactness and convergence).
Let be a sequence of admissible solutions of (4.2), with every divergence free and of zero mean. Suppose that, for some ,
| (6.5) | ||||
| (6.6) | ||||
| (6.7) | ||||
| (6.8) |
where with and with . Then there exists
such that strongly in . The field is a weak solution of the Navier–Stokes equation in the sense that
| (6.9) |
for every divergence-free . If, in addition, (6.4) holds and , then
Proof.
Since , the three series
| (6.10) |
converge. It follows from (6.6) that is Cauchy in , so
| (6.11) |
for some in that space. Divergence and spatial mean pass to the strong limit, hence for every .
Iterating (6.7) and using (6.10) gives
| (6.12) |
Fix . Since , is reflexive, and is weakly precompact in . The strong convergence implies convergence in distributions, so every weakly convergent subsequence of has the unique limit . Hence the full sequence converges weakly, and
It remains to pass to the equation. Testing the th Reynolds system against a divergence-free gives
| (6.13) |
The right-hand side tends to zero by (6.5). Moreover, (6.11) and the uniform bound imply
All the remaining terms in (6) pass to the limit directly by (6.11), including the initial trace. We obtain (6.9). A distributional pressure may then be recovered from the periodic de Rham theorem.
We now complete the proof of Theorem 1.1. Choose by Proposition 6.1, and then choose sufficiently large that the initial triple satisfies the induction hypotheses and . Repeated application of Proposition 4.1 gives a sequence satisfying the assumptions of Proposition 6.2. Its limit has the required regularity, solves (1.1) in the sense of (1.2), and satisfies the two endpoint estimates.
6.1 Time locality and proof of Theorem 1.2
The endpoint-density statement alone does not imply exact nonuniqueness. The extra ingredient is that one iteration step only uses the Reynolds flow in a short neighborhood of the current time cell. We record this feature in the form needed below. At stage , write
| (6.14) |
for the space–time mollification scale used in Section 4.
Lemma 6.3 (Time locality of the iteration).
Suppose that two Reynolds triples satisfying the hypotheses of Proposition 4.1, with the same parameters, agree on . After fixing the same normalization for the pressures, the two applications of Proposition 4.1 may be coupled so that the resulting triples agree on
provided .
Proof.
Since the two input triples agree on , their mollifications, and hence the coefficients , agree on . Every complete time cell contained in this interval therefore has the same frozen coefficients in the two constructions. On such a cell we choose the same admissible initial points for the trajectories. The amplitudes, radii, trajectories, moving Hill blocks, and auxiliary sources then agree on that cell.
The temporal corrector (4.44) is defined by integration only over the current cell. The Leray projection, the symmetric inverse-divergence operator, and all other operators used to define , , and act only in space. Consequently, the two output triples agree on the union of the complete cells contained in . In particular, they agree on , and the same left-time convention is preserved for the next stage. This proves the claim. ∎
Proof of Theorem 1.2.
Fix an arbitrary and . Choose with , set
and choose one spatial mollification scale , common to both constructions, such that
For , apply Proposition 6.1 with endpoint targets , using this common scale and the same cutoff . Denote the resulting initial Reynolds triples by . Since on , the two triples agree on .
Choose one , common to both constructions, sufficiently large that both initial triples satisfy the induction hypotheses,
The second requirement is possible because is given by (6.14), , and . Apply Proposition 4.1 to the two triples with identical choices on every time cell on which they agree. Iterating Lemma 6.3, the level- triples agree on
Proposition 6.2 now gives two limiting weak solutions . Their equality on the intervals above and their convergence in imply
In particular, they have a common initial trace, denoted by , and the endpoint estimate in Proposition 6.2 gives
| (6.15) |
At the other endpoint,
Therefore,
so the two solutions are distinct.
Let be the set of all initial data in admitting two such distinct solutions. Since and were arbitrary, (6.15) shows that is dense in . This proves the theorem. ∎
7 Limitations and possible modifications
We record the limits of the present single-core construction under the condition . These calculations are not impossibility results for other Hill-vortex schemes.
7.1 Can the present method improve the exponent?
The principal obstruction is already visible in (5.3). If
then the formal principal-gradient estimate would require
For the parameters used in the construction above, and , this gives
| (7.1) |
Thus is already close to the ceiling imposed by the principal-gradient estimate for these parameters.
This value is not claimed to be optimal. However, and have competing roles: increasing improves amplitude decay, whereas decreasing enlarges the cores. The orbit-spacing condition
keeps relatively large, while the stress estimates restrict . Reoptimization may improve the numerical margin but does not provide a route toward ; a larger gain requires a structural change in the construction.
7.2 Why temporal concentration does not improve the present theorem
Temporal concentration, as used in related convex-integration constructions such as [31, 32], gives estimates in time-integrated spaces. Concentrating a stress of size on a set of relative measure changes the perturbation amplitude to . Since here with , one obtains
For slightly above , the factor at is , which diverges as . Temporal cutoffs also worsen the transport and corrector errors. Hence this device does not improve the present uniform-in-time estimate, although it may be useful for a theorem with finite time integrability.
7.3 Anisotropic localization
This direction is motivated by intermittent Beltrami, Mikado, and pipe constructions; see [42, 26, 28, 39, 81, 24, 53]. These schemes use anisotropic spatial concentration. The solutions in [26] belong to for some , and hence to for some unspecified . The checkerboard localization of Novack and Vicol [85] gives a related Euler example. This motivated the target
with a larger velocity-integrability gain. One may test the cutoff
and set
If on , the unchanged core gives
Thus the cutoff does not change the intrinsic Hill-core loss. It could help only through better packing or a smaller divergence-correction error, neither of which follows from the present estimates.
7.4 Several parallel moving cores
Another possibility is to split one directional stress among disjoint cores moving in parallel. The cancellation normalization would then give an amplitude of order
for each core. If the cores have comparable radius and disjoint supports, their combined fixed-time gradient satisfies schematically
For , the factor grows with . Thus splitting the amplitude does not improve the fixed-time gradient estimate unless the new packing permits sufficiently larger cores. A multicore improvement therefore requires a different packing or averaging mechanism, not only more copies of the same block.
8 Further directions and open problems
We conclude with several questions that lie beyond the present single-core iteration.
Optimal uniform-in-time spatial regularity.
Determine the largest exponent for which the endpoint-trace density in (1.3) can hold with . The ceiling in (7.1) concerns only the chosen parameters. Can optimization, localization, or a different averaging mechanism give a fixed gain above ? The scale-invariant value is , for which , but the present estimates do not approach it.
Energy profiles and admissibility.
Prescribed energy profiles and admissibility criteria have been studied in Euler convex integration; see [41, 38, 65, 23]. Can the construction prescribe while retaining , or give flexibility among energy-compatible endpoints in the Leray–Hopf or suitable class? Arbitrary endpoint density is incompatible with nonincreasing energy, and the present estimates give neither control nor a local energy inequality.
Coherent vortices beyond the Hill profile.
The Hill energy–gradient scaling gives the threshold . Possible alternatives include Fraenkel’s rings of small cross-section [48], Norbury’s one-parameter family [84] interpolating between thin rings and Hill’s vortex, and the variational constructions of Fraenkel and Berger [49] and Friedman and Turkington [50]. Their aspect ratio provides an additional parameter, although the induced velocity may offset the apparent -gain. Hill’s vortex is also the unique extreme member of the family [6]. Any replacement must retain exact traveling cancellation, a controllable impulse [91, Ch. 3], localizability, and small viscous and modulation stresses. Whether a vortex-ring profile can meet these requirements and improve the exponent is open.
Numerically assisted search for new building blocks.
Numerical and computer-assisted work on Navier–Stokes nonuniqueness [62, 63] studies candidate self-similar profiles and unstable modes; related tools appear for Euler [30, 102] and in rigorous a posteriori error estimates [11]. For the present method, one would instead seek a traveling or pulsating profile with better energy–gradient scaling and a certified residual small in the required stress norms. Numerical optimization may help identify candidates, but the cited instability mechanisms do not supply the cancellation identities needed here.
Trajectory geometry and nonperiodic domains.
Extending the construction to requires a substitute for periodic recurrence and control of spatial decay; bounded domains also require boundary-compatible blocks. For three-dimensional Euler, Enciso, Peñafiel-Tomás, and Peralta-Salas [45] proved that, under explicit compatibility conditions, a smooth local solution on a bounded region can be extended to an admissible weak solution on , , with controlled support. Their result does not provide boundary-compatible Hill vortices or treat viscosity. The inner–outer gluing in [3] is another precedent. On the torus, partial transport by the coarse velocity may reduce the linear interaction, but would require averaging along deformed trajectories.
These questions ask whether the gain above extends beyond the present moving-Hill-vortex construction.
Acknowledgment
Quoc-Hung Nguyen’s research was supported by the CAS Project for Young Scientists in Basic Research (Grant No. YSBR-031) and by the National Natural Science Foundation of China under Grant Nos. 1251101538 and 12595282. He is grateful to Elia Bruè for suggesting that he consider this problem.
AI use disclosure
This paper was written by the authors and was not generated by artificial intelligence. OpenAI’s ChatGPT 5.6 was used to assist with language editing, organization, bibliographic checks, LaTeX troubleshooting, and verification of mathematical calculations. It was not used as an independent source of mathematical results. All mathematical ideas, arguments, proofs, and conclusions are those of the authors, who reviewed the AI-assisted revisions and take full responsibility for the contents of the paper.
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