1. Introduction
The magneto-hydrodynamic (MHD) equations have a wide range of applications in geophysics, astrophysics, and plasma physics [1,2,3,4,5,6,7,8,9,10]. Herein we consider the existence and uniqueness of the local smooth solution of the Cauchy problem to the following 3-dimensional (3D) stochastic MHD equations without diffusion,
(1)
where , and denote, respectively, the pressure, velocity, and magnetic field. Assume that and are independent standard Brownian motions; they are defined in the filtered space , which satisfy the natural assumption. The white noise driven terms in the system are natural for solving practical and theoretical problems. The symbol for stochastic quantities will be understood throughout, but will be written explicitly hereafter.If and , Equation (1) will be reduced to the stochastic Euler equation. There are numerous references on the mathematical theory for stochastic Euler equation [11,12]. Bessaih [13] established the existence of martingale solution on bounded domain in by a compactness method. Brzezniak and Peszat [14] established the existence of martingale solution in by a viscosity vanishing method. Bessaih and Flandoli [15] studied 2D Euler equation perturbed by noise. Menaldi and Sritharan [16] considered 2D stochastic Navier–Stokes equation. Kim [17] discussed the 2D random Euler equations in a simply-connected bounded domain. Kim [18] established the existence of local smooth solution to 3D stochastic Euler equation forced by additive noise. Kim [19] considered the strong solutions of stochastic 3D Navier–Stokes equations. Glatt-Holtz and Vicol [20] established the local existence of smooth solution to 2D stochastic Euler equation driven by multiplicative noise with slip boundary conditions, and obtained the global existence of smooth solution forced by additive noise. The stochastic MHD equations were considered by many authors. Barbu and Da Prato [21] proved the existence of strong solution to 2D stochastic MHD equations in bounded domains, and the existence and uniqueness of an invariant measure were also obtained by the coupling method. The study on stochastic MHD equations, see also in [22,23,24,25] and references therein. Kim [26] established the existence and uniqueness of a local smooth solution to the stochastic initial value problem with initial data for .
If and , Equation (1) is reduced to the deterministic MHD equations without diffusion which is a special kind of quasi-linear symmetric hyperbolic system, as we known that it only has the local existence of smooth solution, see [27].
No one has addressed the existence of the local smooth solution to the stochastic MHD equations without diffusion driven by additive noise when the initial data belongs to , . Therefore, we will extend the well-known result for the deterministic MHD equations to the corresponding stochastic case. For the stochastic case, the main difficulty comes from the nonlinear coupling terms as in deterministic case. To overcome this difficulty, we add a cut-off function depending on the size of in front of the nonlinear convection term in the spirit of [18]. However, this cut-off function brings us an additional obstacle for uniqueness of the local smooth solution. Furthermore, we introduce a stopping time to overcome this new difficulty. Unlike the deterministic case, we need to show the measurability of solution obtained via a classical change of variable. To obtain suitable estimates, we need more elaborate and complicated estimates with respect to stochastic Euler equation due to the coupled construction of this system.
Our contributions are two-fold. First, we consider the stochastic MHD equations for initial data with spatial regularity actually only in , , in contrast to Kim [26] with initial data for . Then, the system (1) does not contain any diffusion terms.
We begin by reviewing some preliminaries associated with Equation (1) and then describe our main result. , we define the usual Sobolev space
(2)
where is the Fourier transform of f, and are the inner product and the norm of , respectively. The Sobolev space is defined as follows,(3)
which is a closed subspace of . The projection can be expressed by means of the Fourier transform: for each , we define , For , we write andDefine the trilinear form by
for all , where b is a continuous trilinear form given by(4)
satisfying the relations(5)
Now we can define as a continuous bilinear operator such that
where the denotes the dual of . The existence of such an operator is guaranteed by the Riesz representation theorem. The notation means the duality.Denote the operators
by the divergence free condition, system (1) can be rewritten as, in the sense of distributions in(6)
where , , ⊤ denotes the transpose. Assume that are -valued progressively measurable processes for some such that for each ,(7)
Now, we state the definition of a local smooth solution to the problem (1).
A pair is called a local smooth solution of (1) if the following conditions are satisfied. (1) is an -valued right continuous stochastic process adapted to , for some ; (2) τ is a stopping time with respect to , such that
(8)
where(9)
(3) satisfies for all
(10)
This is analogous to Definition 5.1 in [28]. By (8) and (9), we have for almost all ω.
We now describe our main result.
Let be -measurable random variable and satisfy (7). Thus, there exists a unique local smooth solution of (1) in the sense of Definition 1. Then, we obtain the estimate of τ:
(11)
where is a constant independent of U and δ. The solution is unique in the following sense; Suppose that and are local smooth solutions to (1), respectively, if almost surely, thenThe paper is organized as follows. In Section 2, we construct the pathwise approximate smooth solution by introducing a cut-off function and controlling the nonlinear convection term in Equation (6) and regularizing the initial function and the noise with respect to the space variables. Equation (6) can be rewritten to a deterministic problem via a classical change of variable, then we apply the Kato method to get a smooth global solution for each fixed random element . To obtain the measurability of the solution, the continuous dependence on the initial data and the noise is established. In Section 3, by energy estimates and stopping time for fixed and we first prove the existence of local smooth solution to the stochastic modified equations driven by an additive noise, then extend the existence interval by passing and where N ia a parameter in the cut-off function such that makes the cut-off function become an identity map. The limit function will be the solution. Finally, by the Chebyshev inequality and energy estimates, the probability of existence can be made arbitrarily close to one.
2. Construction of Approximate Solution
Let be the standard mollifier, and define
(12)
where the convolution be taken with respect to the space variable. Then, is an -valued continuous square integral martingale for every . For each integer , we define as follows,Fix and , let and . Let and , then we define a nonlinear operator and a function as follows,
Therefore, Equation (1) can be rewritten as an abstract Cauchy problem
(13)
Let and be the Laplacian operator in . To apply the Kato method to (13), we need to verify the properties of appearing in Theorem 6 in [27].
(1) is an isomorphism of into .
(2) with , and each , is quasi-m-accretive in , see [29].
(3) and , there is a bounded linear operator on , such that
for all with and all , where denotes the operator norm of bounded linear operators on .(4) and , is a bounded linear operator from into , such that
for all with and all , where denotes the operator norm of bounded linear operator from into .(5) with and , is -valued and and the map is continuous from into . Also, for all with ,
The above and are certain non-negative functions defined for and , which are nondecreasing in r and T.
Property (1) follows from the fact that commutes with . Property (3) was established in [27] when and . Note that is independent of space variable and . At the same time, is a given function and it plays the same role as Y. Therefore, the method in [30] can be applicable to property (3). Property (4) holds due to the following inequality,
for some positive constant C independent of .By the fact that and similar estimates, we can obtain property (5).
With these properties in hand, we apply Theorem 6 in [27] to obtain a local existence to the Cauchy problem (13). In order to extend the local solution to a global solution in time, we will need the following lemmas.
[31] Let w be a Lipschitz continuous function in and . Then,
for some constant c independent of , and , the left-hand side tends to zero as .
[30] Let , for some . Then
for a constant independent of .
If and , then for any fixed , there is a unique solution of (13) for and .
Firstly, using Lemma 1 and Lemma 2, , we have the estimates
(14)
(15)
(16)
Due to the work in [27], there is a local solution for some . Therefore, , the solution Y satisfies
(17)
(18)
By virtue of Equations (5) and (14)–(16), we have
(19)
for some constant C independent of , and .On the other hand, we can estimate directly
(20)
(21)
for some constants C independent of , and . Applying on (17), (18) and multiplying by and , respectively; then, using (19)–(21) and passing , we obtain(22)
for all and some positive constant C independent of T. By the Grönwall inequality, (22) yields that is bounded on each bounded time interval. Therefore, we can extend the solution Y to a global one. □We prove the measurability of Y as a function of .
, the map from Ω into is -measurable.
Because of the fact that the map from into is -measurable, we only need to show the continuous dependence of Y on and . Suppose that as ,
(23)
for each . Therefore, is uniformly bounded in .Define the nonlinear operators and functions as follows,
Denote such that
(24)
Then, for each and we have
uniformly in n.Let be the solution of the problem
(25)
Due to Theorem 7 of [27], there is some such that in . , is uniformly bounded in by Equation (23). We can partition into a number of smaller subintervals to get the continuous dependence of Y on and on . □
3. Existence and Uniqueness of the Local Smooth Solution
We now construct the pathwise smooth solution by means of approximate solutions obtained in Section 2.
Step 1. Construct the local smooth solution for any fixed and .
Recalling (12) and (13), we choose a sequence of decreasing positive numbers such that
(26)
as for almost all , whereSet , , where is a solution to (13) with . Then, we have , for almost all and it is -valued progressively measurable. It holds that
(27)
in the sense of distributions over , for almost all .We next define a stopping time for by
The Itô formula implies that
(28)
(29)
for all and almost all . Using Equations (5) and (14), we can estimate the coupling terms(30)
for some constant independent of l. The Burkholder–Davis–Gundy inequality implies that(31)
where is a constant independent of and t. Combining (28)–(31), we have(32)
where the constant is independent of l and K. By the Fatou Lemma and passing , we get(33)
thus we have , i.e., , there exists such that Therefore, we consider the following setLet be the set of all for which, as ,
and (27) holds in the sense of distributions over . Next, we define . Then, .Now, fixed any . Then, there exists some and a subsequence denoted by such that
(34)
for all . The choice of such a subsequence may depend on .As satisfies
(35)
in the sense of distributions over , thus(36)
where is a constant independent of and . We choose a constant such that . Combining (34) and (36), we extract a subsequence still denoted by such that(37)
(38)
for every bounded open ball G in , as . Equation (38) uses the Corollary 8 in [32].Next, we will prove that
(39)
It is enough to prove that
(40)
where such that for and for . We define , for . Then, (39) follows from (38) and (40).[18] Let . For all , it holds that
(41)
for some constants independent of h and .
As the interaction of with the projection operator is difficult to handle for our purpose, we remove by introducing the vorticity. Let and . By Equation (27) and the equalities
(42)
(43)
where the vector function(44)
we have(45)
(46)
Combining Equations (4), (5), (34); Lemma 3; and the Young inequality, we can estimate the coupling terms as follows,
(47)
where denotes constant independent of . By Equations (45)–(47), we obtain(48)
for all , where is a constant independent of but depends on T. As and uniformly in and . It follows that as . We also have as due to the definition of and (34). Due to Grönwall inequality, it follows from (48) that(49)
On the other hand, by Lemma 3 and (34), there is a constant independent of and such that
(50)
By Equations (45) and (46) as well as the interpolation inequality , for some constant C and we have
(51)
Applying (51), Lemma 3 and the identity , we obtain
(52)
Due to the facts
(53)
(54)
for , we have(55)
The Riesz transform is continuous from into itself for any s and Equations (52)–(55), we have
(56)
By (39), we also have
(57)
Then, combining (37) and (57), we obtain
(58)
in the sense of distributions over , at . We claim that(59)
Due to (37) and (58), we have Because of the fact that and , we obtain
(60)
As , Equations (39) and (60) imply Equation (59).
Due to the occurrence of the cut-off function which plays a key role to obtain the uniformly boundedness and also brings the difficulty of uniqueness, we need to introduce a function as follows
(61)
for the same fixed . Assume that . Let and be two functions satisfying (58), (59), and . It holds that in the sense of distributions over . By (4), (5) and the Young inequality, we haveIt follows that
(62)
for all and some constant C, which yields(63)
Thus, . If , then is obvious.
Now for each , associated with a limit function U of a certain subsequence is uniquely determined, and U is unique on the interval .
Next, we need to show that is a stopping time and is -valued progressively measurable.
is a stopping time.
We need to show that the set is -measurable for . We first claim that
(64)
Let . Then, according to the above procedure, there exists a subsequence such that (34), (37)–(39) hold for some function U. Then, can be defined in terms of the limit function U. As , it holds , for some . Therefore, we have for all sufficiently large . Then, belongs to the right-hand set.
Next, belongs to the right-hand set. As , there exists a subsequence such that Equations (34) and (37)–(39) hold for some function U and can be defined in terms of this limit function U. Simultaneously, there exists another subsequence , such that for some and
for all . Applying the above procedure on the interval , we can further extract a subsequence still denoted by which satisfies (35), (37)–(39) hold for some function , which satisfies that(65)
Since , and repeating the above procedure on the uniqueness, we obtain
Therefore, follows from (65). Thus, . As the left-hand set is -measurable for . For , the left-hand set is empty, so it is -measurable. Thus, is a stopping time. □
is -valued progressively measurable.
For each , . Thus, . Meanwhile, every Borel subset of is also a Borel subset of ; therefore, every Borel subset of is also a Borel subset of . Using , we define , for all x. Then, for all , we have
as , for every . As the continuity of time of U, it is enough to show the measurability of for each R in . Fixed any and let be the closure of an open ball with radius and center p in . We first claim that(66)
Let . Then, according to the above procedure, there exists a subsequence such that Equations (34) and (37)–(39) hold. By Equation (37), for any , , for all sufficiently large . Thus, belongs to the right-hand set.
Next, belongs to the right-hand set. Since , is well-defined. At the same time, for some such that for each , there exists a certain subsequence such that (34), (37)–(39) hold for some function with T replaced by . Let
Suppose . Then, U and satisfy
in the sense of distributions over . It follows that on ; therefore, . Then on . As in ; therefore, . Thus, holds for all . Then, belongs to the left-hand set, and Equation (66) is valid.As is a stopping time, the right-hand set belongs to . Consequently, the map from into defined by is -measurable. □
To improve the time regularity of , we need the next lemma which will be used in Proposition 5.
It holds that
(67)
where is the same constant as in (34).Choosing any constant . We first claim that for each ,
(68)
For any fixed . If the right-hand side is equal to K, then (68) holds. Suppose
Then, there exists a subsequence such that . By repetition of the above procedure, we can further extract a subsequence still denoted by such that
(69)
(70)
(71)
for some function . Combining Equations (69) and (71), we haveTherefore, we obtain (68). Next, by applying the Fatou Lemma and (34), which yields
for all . By passing , we obtain (67). □Next, we improve the time regularity of .
It holds that , for almost all ω.
Let be the Friedrichs mollifier with respect to the space variable. It holds that
for all and , for each . By applying the Itô formula to the functions and , we have for all , for each with .By Equations (14)–(16), we have
(72)
(73)
for all and some constant . By the Burkholder–Davis–Gundy inequality, the identity and Lemma 4, we haveThen, there is a subsequence of still denoted by and a set such that and
(74)
in , as . By the similar estimate, we also have(75)
in , as .Combining Equations (72)–(75) and , for all and let , we obtain
(76)
for all and . Since for each , we obtain the continuity of the time following (76). □Up to now, we obtain the existence of local smooth of (1) for any fixed and , i.e., there exist a stopping time and a function U with the following properties.
(1) for almost all and it is -valued progressively measurable.
(2) It holds that
for all and almost all .(3) For almost all ,
Step 2. Extend the existence interval by passing the limit for any fixed .
Let be the solution obtained with . is a stopping time defined by
There exists some subset such that and satisfies the above properties (1)–(3) and . It is easy to check that for and each ,
then, we obtainIf not, assume that there exists , such that and , for all . By the definition of and , we have , it contradicts with .
Thus, we can define
If , then there is some such that and ,
Thus
If , it holds that ,
Therefore, (defined above) can be written as follows,
(77)
We also have for each and satisfies
(78)
Step 3. Establish the maximal time of existence of local smooth solution.
Next, we pass to obtain the maximal time of existence of the local smooth solution. For each , let be the solution obtained in step 2 and be the stopping time associated with by (78). Let , where be the same as in step 2 for each N.
For any , it is easy to check that for all and each ,
then, we haveIf not, assume that such that , if , then for all , it follows that . By the definition of and , we have , and , this contradicts with .
Then, we can define
If , for some , at some , we infer that
for all and(79)
On the other hand, if , at ,
(80)
We also have , for each .
We set , if . Then, is right continuous on and -measurable for each . Therefore, it is -valued progressively measurable. By Equations (78) and (79), we define
Then, we have and satisfies
(81)
for all and each .Thus, is a local smooth solution in the sense of Definition 1. We can show the uniqueness easily as in step 1.
Step 4. Estimate of the stopping time.
We now establish the estimate (11) of the stopping time. For the solution obtained in Step 3, fix any , we have
where ia a constant defined bySince for almost all , we can define a stopping time
Applying (14)–(16) with replaced by and the Itô formula, we have
(82)
for all , where is a constant independent of . By the Burkholder–Davis–Gundy inequality,(83)
for all , where is a constant independent of . By (82), (83) and the Grönwall inequality, we haveAs , then we have
by passing . Choosing an integer N such that , we have where C is a positive constant independent of . The proof of Theorem 1 is complete.Author Contributions
Z.Q. carried out the well-posedness of stochastic partial differential equations, and Y.T. carried out the perturbation of noise. Z.Q. and Y.T. carried out the proofs and conceived the study as well as read and agreed to the published version of the manuscript.
Funding
The project is supported by NSFC grants 11971188, 11471129. Z.Q. is supported by the CSC under grant No. 201806160015.
Acknowledgments
The authors would like to thank the referees for their valuable comments and suggestions which improved the original manuscript.
Conflicts of Interest
The authors declare no conflict of interest.
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© 2019 by the authors.
Abstract
In this paper, we consider the existence of local smooth solution to stochastic magneto-hydrodynamic equations without diffusion forced by additive noise in
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer