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BY 4.0 license Open Access Published by De Gruyter March 28, 2022

Regularity estimates for fractional orthotropic p-Laplacians of mixed order

  • Jamil Chaker and Minhyun Kim EMAIL logo

Abstract

We study robust regularity estimates for a class of nonlinear integro-differential operators with anisotropic and singular kernels. In this paper, we prove a Sobolev-type inequality, a weak Harnack inequality, and a local Hölder estimate.

MSC 2010: 35B65; 47G20; 31B05; 42B25

1 Introduction

In this paper, we investigate regularity estimates for weak solutions to nonlocal equations

(1.1) Lu = f in Q = ( 1 , 1 ) n ,

where L is a nonlinear integro-differential operator of the form

(1.2) Lu ( x ) = PV R n u ( y ) u ( x ) p 2 ( u ( y ) u ( x ) ) μ ( x , d y )

for p > 1 and f L q ( Q ) for some sufficiently large q . The operator L is clearly determined by the family of measures ( μ ( x , d y ) ) x R n . In the special case, when L is the generator of a Lévy process, μ ( x , A ) measures the number of expected jumps from x into the set A within the unit time interval. However, the class of operators that we consider in this paper is more involved, and for that reason, we first take a look at an important example. Let n N . For s 1 , , s n ( 0 , 1 ) , we define

μ axes ( x , d y ) = k = 1 n s k ( 1 s k ) x k y k 1 s k p d y k i k δ x i ( d y i ) .

This family plays a central role in our paper since admissible operators resp. families of measures will be defined on the basis of μ axes . Given x R n , the measure μ axes ( x , ) only charges differences that occur along the axes

{ x + t e k t R } for k { 1 , , n } .

Hence, we can think of the operator Lu for μ ( x , ) = μ axes ( x , ) as the sum of one-dimensional fractional p-Laplacian in R n with orders of differentiability s 1 , , s n ( 0 , 1 ) depending on the respective direction. In particular, μ axes ( x , ) does not possess a density with respect to the Lebesgue measure. An interesting phenomenon for the case p = 2 and s = s 1 = = s n is that on the one hand the corresponding energies for the fractional Laplacian and L are comparable. On the other hand (for sufficiently good functions), both operators converge to the Laplace operator as s 1 . It is known that the fractional p-Laplacian converges to the p-Laplacian (see [11, Theorem 2.8] or [20, Lemma 5.1] for details), which is defined by

Δ p u ( x ) = div ( u ( x ) p 2 u ( x ) ) .

However, the operator L for μ ( x , ) = μ axes ( x , ) converges for any p > 1 and s = s 1 = = s n to the following local operator (up to a constant depending on p only)

(1.3) A loc p u ( x ) = i = 1 n x i u ( x ) x i p 2 u ( x ) x i = div ( a ( u ( x ) ) )

as s 1 , where a : R n R n with a ( z ) = ( z i p 2 z i ) i { 1 , , n } . This convergence is a direct consequence of the convergence for the one-dimensional fractional p-Laplacian and the summation structure of the operator for μ axes . For details, we refer the reader to Proposition D.1. The operator A loc p is known as orthotropic p-Laplacian and is a well-known operator in the analysis (see, for instance, [41, Chapter 1, Section 8]). This operator is sometimes also called pseudo p-Laplacian. Minimizers for the corresponding energies have been studied in [6], where the authors prove Hölder continuity of minimizers. In [9], local Lipschitz regularity for weak solutions to orthotropic p-Laplace equations for p 2 and every dimension is proved. The case, when p is allowed to be different in each direction, is also studied in several papers. For instance, in [3], the authors introduce anisotropic De Giorgi classes and study related problems. Another interesting paper studying such operators with nonstandard growth condition is [8], where the authors show that bounded local minimizers are locally Lipschitz continuous. For further results, we refer the reader to the references given in the previously mentioned papers.

The two local operators Δ p and A loc p are substantially different, as Δ p is invariant under orthogonal transformation, while A loc p is not. One strength of our results is that they are robust, and we can recover results for the orthotropic p-Laplacian by taking the limit.

One way to deal with the anisotropy of μ axes is to consider for given s 1 , , s n ( 0 , 1 ) a class of suitable rectangles instead of cubes or balls. Hence, we define s max = max { s 1 , , s n } .

Definition 1.1

For r > 0 and x R n , we define

M r ( x ) = × k = 1 n x k r s max s k , x k + r s max s k and M r = M r ( 0 ) .

The advantage of taking these cubes is that they take the anisotropy of the measures resp. operators into account and the underlying metric measure space is a doubling space. The choice of s max in the definition of M r ( x ) is not important. It can be replaced by any positive number ς s max . We only need to ensure that M r ( x ) are balls in a metric measure space with radius r > 0 and center x R n . This allows us to use known results on doubling spaces like the John-Nirenberg inequality or results on the Hardy-Littlewood maximal function.

In the spirit of [15], for each k { 1 , , n } , we define E r k ( x ) = { y R n : x k y k < r s max / s k } . Note, that

(1.4) M r ( x ) = k = 1 n E r k ( x ) .

We consider families of measures μ ( x , d y ) , which are given through certain properties regarding the reference family μ axes ( x , d y ) . Let us introduce and briefly discuss our assumptions on the families ( μ ( x , ) ) x R n .

Assumption 1

We assume

sup x R n R n ( x y p 1 ) μ ( x , d y ) < ,

and for all sets A , B ( R n ) :

A B μ ( x , d y ) d x = B A μ ( x , d y ) d x .

Assumption 1 provides integrability and symmetry of the family of measures. Furthermore, we assume the following tail behavior of ( μ ( x , ) ) x R n .

Assumption 2

There is Λ 1 such that for every x 0 R n , k { 1 , , n } and all r > 0

μ ( x 0 , R n E r k ( x 0 ) ) Λ ( 1 s k ) r p s max .

Note that Assumption 2 is a stronger assumption than an assumption on the volume on the complement of every M r ( x 0 ) . It gives an appropriate tail behavior for the family of measures in each direction separately and allows us to control the appearing constants in our tail estimate in all directions. This is necessary to prove robust estimates for the corresponding operators.

Note that by Assumption 2 and (1.4), we have

(1.5) μ ( x 0 , R n M ρ ( x 0 ) ) k = 1 n μ ( x 0 , R n E ρ k ( x 0 ) ) Λ k = 1 n ( 1 s k ) ρ p s max Λ n ρ p s max .

Hence, (1.5) shows that Assumption 2 implies μ ( x 0 , R n M ρ ( x 0 ) ) c μ axes ( x 0 , R n M ρ ( x 0 ) ) for all x 0 R n .

Finally, we assume the local comparability of corresponding functionals. Hence, we define for any open and bounded Ω R n

Ω μ ( u , v ) = Ω Ω u ( y ) u ( x ) p 2 ( u ( y ) u ( x ) ) ( v ( y ) v ( x ) ) μ ( x , d y ) d x

and μ ( u , v ) = R n μ ( u , v ) whenever these quantities are finite.

Assumption 3

There is Λ 1 such that for every x 0 R n , ρ ( 0 , 3 ) and every u L p ( M ρ ( x 0 ) ) :

(1.6) Λ 1 M ρ ( x 0 ) μ ( u , u ) M ρ ( x 0 ) μ axes ( u , u ) Λ M ρ ( x 0 ) μ ( u , u ) .

Local comparability of the functionals is an essential assumption on the family of measures. It tells us that our family of measures can vary from our reference family in the given sense of local functionals without losing crucial information on ( μ ( x , ) ) x R n like functional inequalities, which we deduce for the explicitly known family ( μ axes ( x , ) ) x R n . This assumption allows us, for instance, to study operators of the form (1.2) for μ axes in the general framework of bounded and measurable coefficients. We emphasize that further examples of families of measures satisfying (1.6) can be constructed similarly to the case p = 2 (see [15, Section 9]). In this paper, we study nonlocal operators of the form (1.2) for families of measures that satisfy the previously given assumptions.

Definition 1.2

Let p > 1 , Λ 1 , and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . We call a family of measures ( μ ( x , ) ) x R n admissible with regard to ( μ axes ( x , ) ) x R n , if it satisfies Assumptions 13. We denote the class of such measures by K ( p , s 0 , Λ ) .

It is not hard to see that the family ( μ axes ( x , ) ) x R n is admissible in the aforementioned sense. Note that Assumptions 1 and 3 are clearly satisfied. Furthermore, for every x 0 R n , k { 1 , , n } and all r > 0 ,

μ axes ( x 0 , R n E r k ( x 0 ) ) = 2 s k ( 1 s k ) r s max / s k h 1 s k p = 2 ( 1 s k ) p r s max p ,

which shows Assumption 2 for Λ = 2 p .

The purpose of this paper is to study weak solutions to nonlocal equations governed by the class of operators L as in (1.2). In order to study weak solutions, we need appropriate Sobolev-type function spaces that guarantee regularity and integrability with respect to μ .

Definition 1.3

Let Ω R n open and p > 1 . We define the function spaces

V p , μ ( Ω R n ) = { u : R n R meas. u Ω L p ( Ω ) , ( u , u ) V p , μ ( Ω R n ) < } , H Ω p , μ ( R n ) = { u : R n R meas. u 0 on R n Ω , u H Ω p , μ ( R n ) < } ,

where

( u , v ) V p , μ ( Ω R n ) = Ω R n u ( y ) u ( x ) p 2 ( u ( y ) u ( x ) ) ( v ( y ) v ( x ) ) μ ( x , d y ) d x , u H Ω p , μ ( R n ) p = u L p ( Ω ) p + R n R n u ( y ) u ( x ) p μ ( x , d y ) d x .

The space V p , μ ( Ω R n ) can be seen as a nonlocal analog of the space H 1 , p ( Ω ) . It provides fractional regularity (measured in terms of μ ) inside of Ω and integrability on R n Ω . The space V p , μ ( Ω R n ) will serve as solution space. On the other hand, the space H Ω p , μ ( R n ) can be seen as a nonlocal analog of H 0 1 , p ( Ω ) . See [28] and [24] for further studies of these spaces in the case p = 2 .

We are interested in finding robust regularity estimates for weak solutions to a class of nonlocal equations. This means that the constants in the regularity estimates do not depend on the orders of differentiability of the integro-differential operator itself but only on a lower bound of the orders. Let us formulate the main results of this paper. For this purpose, we define s ¯ to be the harmonic mean of the orders s 1 , , s n , that is,

s ¯ = 1 n k = 1 n 1 s k 1 .

It is well known that the Harnack inequality fails for weak solutions to singular equations of the type (1.1). Even in the case p = 2 and s 1 = = s n , the Harnack inequality does not hold (see, for instance, [4,7]). Our first main result is a weak Harnack inequality for weak supersolutions to equations of the type (1.1). Throughout the paper, we denote by p = n p / ( n p s ¯ ) the Sobolev exponent, which will appear in Theorem 2.7.

Theorem 1.4

(Weak Harnack inequality) Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p < n / s ¯ and f L q / ( p s ¯ ) ( M 1 ) for some q > n . There are p 0 = p 0 ( n , p , p , s 0 , q , Λ ) ( 0 , 1 ) and C = C ( n , p , p , s 0 , q , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every u V p , μ ( M 1 R n ) satisfying u 0 in M 1 and

μ ( u , φ ) ( f , φ ) for every non - negative φ H M 1 p , μ ( R n ) ,

the following holds:

(1.7) inf M 1 / 4 u C M 1 / 2 u p 0 ( x ) d x 1 / p 0 sup x M 15 / 16 2 R n M 1 u ( z ) p 1 μ ( x , d z ) 1 / ( p 1 ) f L q / ( p s ¯ ) ( M 15 / 16 ) .

Although the weak Harnack inequality provides an estimate on the infimum only, it is sufficient to prove a decay of oscillation for bounded weak solutions and therefore a local Hölder estimate.

Theorem 1.5

(Local Hölder estimate) Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p < n / s ¯ and f L q / ( p s ¯ ) ( M 1 ) for some q > n . There are α = α ( n , p , p , s 0 , q , Λ ) ( 0 , 1 ) and C = C ( n , p , p , s 0 , q , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every u V p , μ ( M 1 R n ) L ( R n ) satisfying

μ ( u , φ ) = ( f , φ ) for every φ H M 1 p , μ ( R n ) ,

the following holds: u C α ( M ¯ 1 / 2 ) and

u C α ( M ¯ 1 / 2 ) C ( u L ( R n ) + f L q / ( p s ¯ ) ( M 15 / 16 ) ) .

Note that the result needs global boundedness of weak solutions. The same assumption is also needed in the previous works [14,15,25]. Global and local boundedness of weak solutions to anisotropic nonlocal equations are nontrivial open questions.

Furthermore, note that the general case, replacing M 1 4 , M 1 2 , M 15 16 , M 1 by M r 4 ( x 0 ) , M r 2 ( x 0 ) , M 15 r 16 ( x 0 ) , M r ( x 0 ) , for x 0 R n and r ( 0 , 1 ] follows by a translation and anisotropic scaling argument introduced in Section 4. See also [14].

Let us comment on related results in the literature. The underlying ideas in developing regularity results for uniformly elliptic operators in divergence form with bounded and measurable coefficients go back to the influential contributions by De Giorgi, Nash, and Moser (see [19,45,46]). These works led to many further results in various directions. Similar results for nonlocal operators in divergence form have been obtained by several authors including these works: [1, 2,5,12,16,17,18,22,24,26,27, 33,34,38,42,43,44,54,55]. See also the references therein. For further regularity results concerning nonlocal equations governed by fractional p-Laplacians, we refer the reader to [10,38,39,48,49,50,51].

In [22], the authors extend the De Giorgi-Nash-Moser theory to a class of fractional p-Laplace equations. They provide the existence of a unique minimizer to homogenous equations and prove local regularity estimates for weak solutions. Moreover, in [21], the same authors prove a general Harnack inequality for weak solutions.

Nonlocal operators with anisotropic and singular kernels of the type μ axes are studied in various mathematical areas such as stochastic differential equations and potential theory. In [4], the authors study regularity estimates for harmonic functions for systems of stochastic differential equations d X t = A ( X t ) d Z t driven by Lévy processes Z t with Lévy measure μ axes ( 0 , d y ) , where 2 s 1 = = 2 s n = α and p = 2 . See also [13,56,52]. Sharp two-sided bounds for the heat kernels are established in [35,37]. In [36], the authors prove the existence of transition density of the process X t and establish semigroup properties of solutions. The existence of densities for solutions to stochastic differential equations with Hölder continuous coefficients driven by Lévy processes with anisotropic jumps has been proved in [30]. Such types of anisotropies also appear in the study of the anisotropic stable JCIR process, see [29].

Our approach follows mainly the ideas of [14,25] and [15]. In [25], the authors develop a local regularity theory for a class of linear nonlocal operators, which covers the case s = s 1 = = s n ( 0 , 1 ) and p = 2 . Based on the ideas of [25], the authors in [14] establish regularity estimates in the case p = 2 for weak solutions in a more general framework, which allows the orders of differentiability s 1 , , s n to be different. In [15], parabolic equations in the case p = 2 and possible different orders of differentiability are studied. That paper provides robust regularity estimates, which means the constants in the weak Harnack inequality and Hölder regularity estimate do not depend on the orders of differentiability but on their lower one, only. This allows us to recover regularity results for local operators from the theory of nonlocal operators by considering the limit.

The purpose of this paper is to provide local regularity estimates as in [14] for operators which are allowed to be nonlinear. This nonlinearity leads to several difficulties like the need for a different proof for the discrete gradient estimate (see Lemma 3.4). Since we cannot use the helpful properties of Hilbert spaces (like Plancherel’s theorem), we also need an approach different from the one in [14] to prove the Sobolev-type inequality. One strength of this paper is the robustness of all results. This allows us to recover regularity estimates for the limit operators such as for the orthotropic p-Laplacian.

Finally, we would like to point out that it is also interesting to study such operators in nondivergence form. We refer the reader to [53] for regularity results concerning the fractional Laplacian and to [40] for the fractional p-Laplacian. See also [23] for the anisotropic case.

Even in the most simple case, that is, p = 2 and s = s 1 = s 2 = = s n , regularity estimates for operators in nondivergence form of the type (1.2) with μ = μ axes lead to various open problems such as an Alexandrov-Bakelmann-Pucci estimate.

The authors wish to express their thanks to Lorenzo Brasco for helpful comments.

Outline: This paper is organized as follows. In Section 2, we introduce appropriate cut-off functions and prove auxiliary results concerning functionals for admissible families of measures. One main result of that section is the Sobolev-type inequality (see Theorem 2.7). In Section 3, we prove the weak Harnack inequality, and Section 4 presents the proof of the local Hölder estimate. In Appendix A, we prove some auxiliary algebraic inequalities, and in Appendix B, we briefly sketch the construction of appropriate anisotropic “dyadic” rectangles. In Appendix C, we use the anisotropic dyadic rectangles to sketch the proof of a suitable sharp maximal function theorem.

2 Auxiliary results

This section is devoted to providing some general properties for the class of nonlocal operators that we study in the scope of this paper. The main auxiliary result is a robust Sobolev-type inequality.

Let us first introduce a class of suitable cut-off functions that will be useful for appropriate localization.

Definition 2.1

We say that ( τ x 0 , r , λ ) x 0 , r , λ C 0 , 1 ( R n ) is an admissible family of cut-off functions if there is c 1 such that for all x 0 R n , r ( 0 , 1 ] and λ ( 1 , 2 ] , it holds that

supp ( τ ) M λ r ( x 0 ) , τ 1 , τ 1 on M r ( x 0 ) , k τ c ( λ s max / s k 1 ) 1 r s max / s k for every k { 1 n } .

For brevity, we simply write τ for any such function from ( τ x 0 , r , λ ) x 0 , r , λ , if the respective choice of x 0 , r and λ is clear. The existence of such functions is standard.

Recall the definition of admissible families of measures K ( p , s 0 , Λ ) from Definition 1.2.

Lemma 2.2

Let p > 1 , Λ 1 , and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . There is C = C ( n , p , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) , every x 0 R n , r ( 0 , 1 ] , λ ( 1 , 2 ] and every admissible cut-off function τ , the following is true:

sup x R n R n τ ( y ) τ ( x ) p μ ( x , d y ) C k = 1 n ( λ s max / s k 1 ) p s k r p s max .

Proof

We skip the proof. One can follow the lines of the proof from [15, Lemma 3.1] and will get the same result with the factor n p 1 instead of n .□

For future purposes, we deduce the following observation. It is an immediate consequence of the foregoing lemma.

Corollary 2.3

Let p > 1 , Λ 1 , and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . There is a constant C = C ( n , p , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every x 0 R n , r ( 0 , 1 ] , λ ( 1 , 2 ] and every admissible cut-off function τ and every u L p ( M λ r ( x 0 ) ) , it holds true that

M λ r ( x 0 ) R n M λ r ( x 0 ) u ( x ) p τ ( x ) p μ ( x , d y ) d x C k = 1 n ( λ s max / s k 1 ) p s k r p s max u L p ( M λ r ( x 0 ) ) p .

Note that the constants in Lemma 2.2 and Corollary 2.3 do not depend on s 0 . Therefore, the lower bound s 0 s k for all k { 1 , , n } can be dropped here.

2.1 Functional inequalities

This section is devoted to the proofs of a Sobolev and a Poincaré-type inequality. We start our analysis by first proving a technical lemma, see also [15, Lemma 4.1].

Lemma 2.4

Let p > 1 , a ( 0 , 1 ] , b 1 , N N , k { 1 , , n } , and s k ( 0 , 1 ) . For any u L p ( R n )

R n sup ρ > 0 1 ρ ( 1 + p s k ) b R u ( x ) u ( x + h e k ) p 1 [ a ρ b , 2 a ρ b ) ( h ) d h d x ( 2 a ) 1 + p s k N p ( 1 s k ) R n R u ( x ) u ( x + h e k ) p h 1 + p s k 1 a N ρ b , 2 a N ρ b ( h ) d h d x .

Proof

Let I a = [ a ρ b , 2 a ρ b ) . By the triangle inequality and a simple change of variables, we have

R u ( x ) u ( x + h e k ) p 1 I a ( h ) d h N p 1 j = 1 N R u x + j 1 N h e k u x + j N h e k p 1 I a ( h ) d h = N p j = 1 N R u ( x + ( j 1 ) h e k ) u ( x + j h e k ) p 1 I a / N ( h ) d h .

Since h < 2 a N ρ b , we obtain

R n sup ρ > 0 1 ρ ( 1 + p s k ) b R u ( x ) u ( x + h e k ) p 1 I a ( h ) d h d x N p 2 a N 1 + p s k j = 1 N R n R u ( x + ( j 1 ) h e k ) u ( x + j h e k ) p h 1 + p s k 1 I a / N ( h ) d h d x .

We change the order of integration by Fubini’s theorem and then use the change of variables y = x + ( j 1 ) h e k to conclude that

j = 1 N R n R u ( x + ( j 1 ) h e k ) u ( x + j h e k ) p h 1 + p s k 1 I a / N ( h ) d h d x = j = 1 N R R n u ( x + ( j 1 ) h e k ) u ( x + j h e k ) p h 1 + p s k 1 I a / N ( h ) d x d h = j = 1 N R R n u ( y ) u ( y + h e k ) p h 1 + p s k 1 I a / N ( h ) d y d h = N R n R u ( y ) u ( y + h e k ) p h 1 + p s k 1 I a / N ( h ) d h d y .

Using the foregoing result for b = s max / s k allows us to prove a robust Sobolev-type inequality. Robust in this context means that the appearing constant in the Sobolev-type inequality is independent of s 1 , , s n and depends on the lower bound s 0 only.

Before we prove a robust Sobolev-type inequality, we recall the definition of the Hardy–Littlewood maximal function and sharp maximal function. For u L loc 1 ( R n ) ,

M u ( x ) = sup ρ > 0 M ρ ( x ) u ( y ) d y and M u ( x ) = sup ρ > 0 M ρ ( x ) u ( y ) ( u ) M ρ ( x ) d y ,

where ( u ) Ω = Ω u ( z ) d z . We will use the maximal function theorem and the sharp maximal function theorem. Note that R n is equipped with the metric induced by rectangles of the form M r ( x ) and the standard Lebesgue measure. Since M 2 r = 2 n ( 2 r ) n s max / s ¯ 2 n / s 0 M r , this space is a doubling space with the doubling constant 2 n / s 0 .

Theorem 2.5

[32, Theorem 2.2] Let s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Then, there is a constant C 1 = C 1 ( n , s 0 ) > 0 such that

{ x R n : M u ( x ) > t } C 1 t u L 1 ( R n )

for all t > 0 and u L 1 ( R n ) . For p > 0 , there is a constant C p = C p ( n , p , s 0 ) > 0 such that

M u ( x ) L p ( R n ) C p u L p ( R n )

for all u L p ( R n ) .

We were not able to find a reference for the sharp maximal function theorem for sets of the type M ρ . Actually, we are not sure whether such a result is available in the literature. However, one can follow the ideas of [31, Section 3.4], where the L p bound is established for the sharp maximal function with cubes (instead of anisotropic rectangles). In order to prove the same result for the sharp maximal function with anisotropic rectangles, dyadic cubes have to be replaced by appropriate anisotropic “dyadic” rectangles. We construct the anisotropic dyadic rectangles in Appendix B and prove the following theorem in Appendix C. See also Appendix C for the definition of the dyadic maximal function M d u .

Theorem 2.6

Let s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) and let 0 < p 0 p < . Then, there is a constant C = C ( n , p , s 0 ) > 0 such that for all u L loc 1 ( R n ) with M d u L p 0 ( R n ) ,

u L p ( R n ) C M u L p ( R n ) .

We are now in a position to prove a robust Sobolev-type inequality by using Lemma 2.4 and Theorems 2.5 and 2.6.

Theorem 2.7

Let s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Suppose that 1 < p < n / s ¯ and let p = n p / ( n p s ¯ ) . Then, there is a constant C = C ( n , p , p , s 0 ) > 0 such that for every u V p , μ axes ( R n R n )

(2.1) u L p ( R n ) p C R n R n u ( x ) u ( y ) p μ axes ( x , d y ) d x .

Proof

This proof is based on the technique of [47], which uses the maximal and sharp maximal inequalities. Note that by definition of V p , μ axes ( R n R n ) and Hölder’s inequality, V p , μ axes ( R n R n ) L p ( R n ) L loc p ( R n ) L loc 1 ( R n ) . Hence, the maximal and sharp maximal functions are well defined for every function u V p , μ axes ( R n R n ) . For x R n and ρ > 0 , we have

(2.2) M ρ ( x ) u ( y ) ( u ) M ρ ( x ) d y M ρ ( x ) M ρ ( x ) u ( y ) u ( z ) d z d y .

Let us consider as in [14, Lemma 2.1] a polygonal chain = ( 0 ( y , z ) , , n ( y , z ) ) R n ( n + 1 ) connecting y and z with

k ( y , z ) = ( l 1 k , , l n k ) , where l j k = z j , if j k , y j , if j > k ,

then y = 0 ( y , z ) , z = n ( y , z ) , and k 1 ( y , z ) k ( y , z ) = y k z k for all k = 1 , , n . By the triangle inequality, we have

(2.3) M ρ ( x ) M ρ ( x ) u ( y ) u ( z ) d z d y k = 1 n M ρ ( x ) M ρ ( x ) u ( k 1 ( y , z ) ) u ( k ( y , z ) ) d z d y .

For a fixed k , we set w = k 1 ( y , z ) = ( z 1 , , z k 1 , y k , , y n ) and v = y + z w = ( y 1 , , y k 1 , z k , , z n ) , then k ( y , z ) = w + e k ( v k w k ) . By Fubini’s theorem, we obtain

(2.4) M ρ ( x ) M ρ ( x ) u ( k 1 ( y , z ) ) u ( k ( y , z ) ) d z d y M ρ ( x ) x k ρ s max / s k x k + ρ s max / s k u ( w ) u ( w + e k ( v k w k ) ) d v k d w .

Moreover, using the inequality v k w k v k x k + w k x k < 2 ρ s max / s k , we make the inner integral on the right-hand side of (2.4) independent of x . Namely, we have

(2.5) x k ρ s max / s k x k + ρ s max / s k u ( w ) u ( w + e k ( v k w k ) ) d v k 2 w k 2 ρ s max / s k w k + 2 ρ s max / s k u ( w ) u ( w + e k ( v k w k ) ) d v k = 2 2 ρ s max / s k 2 ρ s max / s k u ( w ) u ( w + h e k ) d h .

Combining (2.2)–(2.5), we arrive at

(2.6) M ρ ( x ) u ( y ) ( u ) M ρ ( x ) d y k = 1 n ρ s max M ρ ( x ) F k ( w ) d w ,

where the function F k is defined by

F k ( w ) sup ρ > 0 2 ρ s max 2 ρ s max / s k 2 ρ s max / s k u ( w ) u ( w + h e k ) d h .

By Hölder’s inequality,

(2.7) M ρ ( x ) F k ( w ) d w p M ρ ( x ) F k p ( w ) d w p p p M ρ ( x ) F k ( w ) d w p M ρ p p p F k L p ( R n ) p p M ρ ( x ) F k ( w ) d w p .

Thus, it follows from (2.6) and (2.7) that

M ρ ( x ) u ( y ) ( u ) M ρ ( x ) d y p n p 1 k = 1 n ρ p s max M ρ ( x ) F k ( w ) d w p n p 1 k = 1 n ρ p s max M ρ p p p F k L p ( R n ) p p M ρ ( x ) F k ( w ) d w p n p 1 2 n p p p k = 1 n F k L p ( R n ) p p M ρ ( x ) F k ( w ) d w p .

Taking the supremum over ρ > 0 , we obtain

(2.8) ( M u ( x ) ) p n p 1 2 n p p p k = 1 n F k L p ( R n ) p p ( M F k ( x ) ) p .

We now use Theorems 2.5 and 2.6. By (C.1) and Theorem 2.5, we know that M d u L p ( R n ) . Thus, Theorem 2.6 yields that

u L p ( R n ) p C M u L p ( R n ) p

for some C = C ( n , p , s 0 ) > 0 . Moreover, assuming F k L p ( R n ) , we have by Theorem 2.5 and (2.8)

M u L p ( R n ) p C k = 1 n F k L p ( R n ) p p M F k p p C k = 1 n F k L p ( R n ) p

for some C = C ( n , p , p , s 0 ) > 0 . Therefore, it only remains to show that

(2.9) F k L p ( R n ) p C s k ( 1 s k ) R n R u ( x ) u ( x + h e k ) p h 1 + p s k d h d x

for each k = 1 , , n .

Let us fix k . By using Hölder’s inequality, we have

F k L p ( R n ) p R n sup ρ > 0 2 p ρ p s max 2 ρ s max / s k 2 ρ s max / s k u ( x ) u ( x + h e k ) p d h d x = i = 0 R n sup ρ > 0 2 p 2 ρ ( 1 + p s k ) s max / s k R u ( x ) u ( x + h e k ) p 1 I i ( h ) d h d x ,

where I i = [ 2 i ρ s max / s k , 2 i + 1 ρ s max / s k ) . For each i , let { β j , i } j = 0 be a sequence such that j β j , i 1 , which will be chosen later. Then,

F k L p ( R n ) p i , j = 0 β j , i R n sup ρ > 0 2 p 2 ρ ( 1 + p s k ) s max / s k R u ( x ) u ( x + h e k ) p 1 I i ( h ) d h d x .

By Lemma 2.4 for N = 2 j , a = 2 i ( 0 , 1 ] and b = s max / s k , we obtain

F k L p ( R n ) p i , j = 0 2 p 2 + ( 1 + p s k ) ( 1 i ) + p ( 1 s k ) j β j , i R n R u ( x ) u ( x + h e k ) p h 1 + p s k 1 I i + j ( h ) d h d x .

We rearrange the double sums to have

F k L p ( R n ) p i = 0 j = 0 i 2 p 2 + ( 1 + p s k ) ( 1 i + j ) + p ( 1 s k ) j β j , i j R n R u ( x ) u ( x + h e k ) p h 1 + p s k 1 I i ( h ) d h d x .

Let β j , i = p ( log 2 ) ( 1 s k ) 2 p ( 1 s k ) j , then

1 j = 0 β j , i = p ( log 2 ) ( 1 s k ) 1 2 p ( 1 s k ) 2 p < + .

Since

j = 0 i 2 p 2 + ( 1 + p s k ) ( 1 i + j ) + p ( 1 s k ) j β j , i j = p ( log 2 ) ( 1 s k ) 2 p 2 + ( 1 + p s k ) ( 1 i ) j = 0 i 2 ( 1 + p s k ) j = p ( log 2 ) ( 1 s k ) 2 p 2 + ( 1 + p s k ) ( 1 i ) 2 ( 1 + p s k ) ( i + 1 ) 2 1 + p s k 1 p ( 1 s k ) 2 p ( 1 + s k ) ,

we arrive at

F k L p ( R n ) p i = 0 p ( 1 s k ) 2 p ( 1 + s k ) R n R u ( x ) u ( x + h e k ) p h 1 + p s k 1 I i ( h ) d h d x p 2 2 p s k s 0 ( 1 s k ) R n R u ( x ) u ( x + h e k ) p h 1 + p s k d h d x ,

which proves (2.9).□

Next, we can make use of appropriate cut-off functions to prove a localized version of the foregoing Sobolev-type inequality.

Corollary 2.8

Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Suppose that 1 < p < n / s ¯ . There is C = C ( n , p , p , s 0 , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every x 0 R n , r ( 0 , 1 ] , λ ( 1 , 2 ] and u H M λ r ( x 0 ) p , μ ( R n ) it holds

u L p ( M r ( x 0 ) ) p C M λ r ( x 0 ) M λ r ( x 0 ) u ( x ) u ( y ) p μ ( x , d y ) d x + C k = 1 n ( λ s max / s k 1 ) s k p r p s max u L p ( M λ r ( x 0 ) ) p ,

where p is defined as in Theorem 2.7.

Proof

Let τ : R n R be an admissible cut-off function in the sense of Definition 2.1. For simplicity of notation, we write M r = M r ( x 0 ) .

By Theorem 2.7, there is a constant c 1 = c 1 ( n , p , p , s 0 ) > 0 such that

u τ L p ( R n ) p c 1 M λ r M λ r u ( x ) τ ( x ) u ( x ) τ ( y ) p μ axes ( x , d y ) d x + 2 M λ r ( M λ r ) c u ( x ) τ ( x ) u ( x ) τ ( y ) p μ axes ( x , d y ) d x c 1 ( I 1 + 2 I 2 ) .

We have

I 1 1 2 p M λ r M λ r 2 p 1 ( u ( y ) u ( x ) ) ( τ ( x ) + τ ( y ) ) p μ axes ( x , d y ) d x + M λ r M λ r 2 p 1 ( u ( x ) + u ( y ) ) ( τ ( x ) τ ( y ) ) p μ axes ( x , d y ) d x = 1 2 ( J 1 + J 2 ) .

Since ( τ ( x ) + τ ( y ) ) 2 for all x , y M λ r , we get

J 1 2 p M λ r M λ r u ( y ) u ( x ) p μ axes ( x , d y ) d x Λ 2 p M λ r M λ r u ( y ) u ( x ) p μ ( x , d y ) d x ,

where we used Assumption 3 in the second inequality.

Moreover, since u ( x ) + u ( y ) p τ ( x ) τ ( x ) p 2 p 1 u ( x ) p τ ( x ) τ ( x ) p + 2 p 1 u ( y ) p τ ( y ) τ ( x ) p , we can again apply Assumption 3, and by Lemma 2.2, we get

J 2 2 p sup x R n R n τ ( y ) τ ( x ) p μ ( x , d y ) u L p ( M λ r ) p c 2 k = 1 n λ s max s k 1 p s k r p s max u L p ( M λ r ) p

for some c 2 > 0 , depending on n , p , s 0 , and Λ . Moreover, by Corollary 2.3, there is c 3 = c 3 ( n , p , Λ ) > 0 such that

I 2 c 3 k = 1 n λ s max s k 1 p s k r p s max u L p ( M λ r ) p .

Combining these estimates, we find a constant C = C ( n , p , p , s 0 , Λ ) > 0 such that

u L p ( M r ) p u τ L p ( R n ) p C M λ r M λ r u ( x ) u ( y ) p μ axes ( x , d y ) d x + k = 1 n λ s max s k 1 p s k r p s max u L p ( M λ r ) p .

Applying the same method as in the proof of the Sobolev-type inequality Theorem 2.7, we can deduce a Poincaré inequality.

Theorem 2.9

Let p > 1 , Λ 1 , and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . There is C = C ( n , p , s 0 , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every x 0 R n , r ( 0 , 1 ] and u L p ( M r ( x 0 ) ) ,

u ( u ) M r ( x 0 ) L p ( M r ( x 0 ) ) p C r p s max M r ( x 0 ) μ ( u , u ) .

The proof is analog to the proof of the Poincaré inequality for the case p = 2 , see [15, Theorem 4.2].

3 Weak Harnack inequality

In this section, we prove Theorem 1.4. The proof is based on Moser’s iteration technique. We first need to verify a few properties for weak supersolutions to (1.1).

Lemma 3.1

Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p n / s ¯ , x 0 R n , r ( 0 , 1 ] , and λ ( 1 , 2 ] . Set M r = M r ( x 0 ) and assume f L q / ( p s ¯ ) ( M λ r ) for some q > n . There is C = C ( n , p , s 0 , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every u V p , μ ( M λ r R n ) that satisfies

μ ( u , φ ) ( f , φ ) for any nonnegative φ H M λ r p , μ ( R n ) , u ( x ) ε a.e. in M λ r for some ε > 0 ,

the following holds:

M r M r log u ( y ) log u ( x ) p μ ( x , d y ) d x C k = 1 n ( λ s max / s k 1 ) p s k r p s max M λ r + ε 1 p f L q / ( p s ¯ ) ( M λ r ) M λ r q p s ¯ q + 2 ε 1 p M λ r sup x M ( λ + 1 ) r / 2 R n M λ r u p 1 ( y ) μ ( x , d y ) .

Proof

Let τ be an admissible cut-off function in the sense of Definition 2.1, and let φ ( x ) = τ p ( x ) u 1 p ( x ) , which is well defined since supp ( τ ) M λ r . Then, we have

(3.1) ( f , φ ) M λ r M λ r u ( x ) u ( y ) p 2 ( u ( x ) u ( y ) ) τ p ( x ) u p 1 ( x ) τ p ( y ) u p 1 ( y ) μ ( x , d y ) d x + 2 M λ r R n M λ r u ( x ) u ( y ) p 2 ( u ( x ) u ( y ) ) τ p ( x ) u p 1 ( x ) μ ( x , d y ) d x I 1 + I 2 .

Similar to the proof of [22, Lemma 1.3], we get the inequality

(3.2) u ( x ) u ( y ) p 2 ( u ( x ) u ( y ) ) τ p ( x ) u p 1 ( x ) τ p ( y ) u p 1 ( y ) c 1 log u ( x ) log u ( y ) p τ p ( y ) + c 2 τ ( x ) τ ( y ) p ,

where c 1 , c 2 > 0 are constants depending only on p . Hence, by (3.2) and Lemma 2.2,

(3.3) I 1 c 1 M r M r log u ( x ) log u ( y ) p μ ( x , d y ) d x + C k = 1 n ( λ s max / s k 1 ) p s k r p s max M λ r .

For I 2 , again by Lemma 2.2,

(3.4) I 2 2 M λ r R n M λ r ( u ( x ) u ( y ) ) p 1 τ p ( x ) u p 1 ( x ) 1 { u ( x ) u ( y ) } μ ( x , d y ) d x 2 M λ r R n M λ r τ ( x ) τ ( y ) p μ ( x , d y ) d x + 2 M λ r R n M λ r u p 1 ( y ) τ p ( x ) ε p 1 μ ( x , d y ) d x C k = 1 n ( λ s max / s k 1 ) p s k r p s max M λ r + 2 M λ r ε p 1 sup x M ( λ + 1 ) r / 2 R n M λ r u p 1 ( y ) μ ( x , d y ) ,

where we assumed that supp ( τ ) M ( λ + 1 ) r / 2 . Combining (3.1), (3.3), and (3.4), and using Hölder’s inequality, we conclude that

M r M r log u ( y ) log u ( x ) p μ ( x , d y ) d x C k = 1 n ( λ s max / s k 1 ) p s k r p s max M λ r + ε 1 p f L q / ( p s ¯ ) ( M λ r ) M λ r q p s ¯ q + 2 ε 1 p M λ r sup x M ( λ + 1 ) / 2 R n M λ r u p 1 ( y ) μ ( x , d y ) .

The next theorem is an essential result to prove the weak Harnack inequality.

Theorem 3.2

Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p < n / s ¯ , x 0 R n , and r ( 0 , 1 ] . Set M r = M r ( x 0 ) and assume f L q / ( p s ¯ ) ( M 5 r / 4 ) for some q > n . There are C = C ( n , p , s 0 , q , Λ ) > 0 and p ¯ = p ¯ ( n , p , s 0 , q , Λ ) ( 0 , 1 ) such that for each μ K ( p , s 0 , Λ ) and every u V p , μ ( M 5 r / 4 R n ) that satisfies

μ ( u , φ ) ( f , φ ) for any nonnegative φ H M 5 r / 4 p , μ ( R n ) , u ( x ) ε a.e. in M 5 r / 4 ,

for

ε > r δ f L q / ( p s ¯ ) ( M 5 r / 4 ) 1 p 1 + r p s max sup x M 9 r / 8 R n M 5 r / 4 u p 1 ( y ) μ ( x , d y ) 1 p 1 ,

where δ = p s max p 1 q n q , the following holds:

M r u p ¯ ( x ) d x 1 / p ¯ C M r u p ¯ ( x ) d x 1 / p ¯ .

Proof

We only need to prove that log u BMO ( M r ) . The rest of the proof is standard. The Poincaré inequality (see Theorem 2.9) and Lemma 3.1 imply

log u ( log u ) M r L p ( M r ) p C r p s max M r μ ( log u , log u ) C k = 1 n 5 4 s max s k 1 s k p M 5 r / 4 + C ε 1 p f L q / ( p s ¯ ) ( M 5 r / 4 ) r p s max M 5 r / 4 q p s ¯ q + C ε 1 p r p s max M 5 r / 4 sup x M 9 r / 8 R n M 5 r / 4 u p 1 ( y ) μ ( x , d y ) C M r ,

where we used the bound on ε in the last inequality. Finally, by Hölder’s inequality, we obtain

log u BMO ( M r ) M r log u ( log u ) M r p d x 1 / p C ,

which shows that log u BMO ( B r ) .□

In order to apply Moser’s iteration for negative exponents, we prove the following lemma.

Lemma 3.3

Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p < n / s ¯ , x 0 R n , r ( 0 , 1 ] , and λ ( 1 , 2 ] . Set M r = M r ( x 0 ) and assume f L q / ( p s ¯ ) ( M λ r ) for some q > n . For each μ K ( p , s 0 , Λ ) and every u V p , μ ( M λ r R n ) that satisfies

μ ( u , φ ) ( f , φ ) for any nonnegative φ H M λ r p , μ ( R n ) , u ( x ) ε a.e. in M λ r ,

for

ε > r δ f L q / ( p s ¯ ) ( M λ r / 4 ) 1 p 1 + r p s max sup x M ( λ + 1 ) r / 2 R n M λ r u p 1 ( y ) μ ( x , d y ) 1 p 1 ,

the following is true for any t > p 1 ,

u 1 L ( t p + 1 ) γ ( M r ) t p + 1 C k = 1 n ( λ s max / s k 1 ) s k p r s max p u 1 L t p + 1 ( M λ r ) t p + 1 ,

where δ = p s max p 1 q n q , γ = n / ( n p s ¯ ) , and C = C ( n , p , p , q , t , s 0 , Λ ) > 0 is a constant that is bounded when t is bounded away from p 1 .

To prove Lemma 3.3, we need the following algebraic inequality.

Lemma 3.4

Let a , b > 0 , τ 1 , τ 2 [ 0 , 1 ] , and t > p 1 > 0 . Then,

b a p 2 ( b a ) ( τ 1 p a t τ 2 p b t ) c 1 τ 1 a t + p 1 p τ 2 b t + p 1 p p c 2 τ 1 τ 2 p ( a t + p 1 + b t + p 1 ) ,

where c i = c i ( p , t ) > 0 , i = 1 , 2 , is bounded when t is bounded away from p 1 .

Note that Lemma 3.4 is a discrete version of

v p 2 v ( v t τ p ) c 1 v t + p 1 p τ p c 2 τ p v t + p 1 .

The proof of Lemma 3.4 is provided in Appendix A.

Proof of Lemma 3.3

Let τ be an admissible cut-off function in the sense of Definition 2.1. Since τ = 0 outside M λ r , the function φ = τ p u t is well defined. By using Lemma 3.4, we have

( f , τ p u t ) ( u , τ p u t ) = M λ r M λ r u ( y ) u ( x ) p 2 ( u ( y ) u ( x ) ) ( τ p ( x ) u t ( x ) τ p ( y ) u t ( y ) ) μ ( x , d y ) d x + 2 M λ r R n M λ r u ( y ) u ( x ) p 2 ( u ( y ) u ( x ) ) τ p ( x ) u t ( x ) μ ( x , d y ) d x

c 1 M λ r M λ r τ ( x ) u t + p 1 p ( x ) τ ( y ) u t + p 1 p ( y ) p μ ( x , d y ) d x c 2 M λ r M λ r τ ( x ) τ ( y ) p ( u t + p 1 ( x ) + u t + p 1 ( y ) ) μ ( x , d y ) d x 2 M λ r R n M λ r ( u ( x ) u ( y ) ) p 1 τ p ( x ) u t ( x ) 1 { u ( y ) u ( x ) } μ ( x , d y ) d x c 1 I 1 c 2 I 2 I 3 ,

where c 1 and c 2 are constants given in Lemma 3.4. By Theorem 2.8, we obtain

I 1 = M λ r M λ r τ ( x ) u t + p 1 p ( x ) τ ( y ) u t + p 1 p ( y ) p μ ( x , d y ) d x C τ u t + p 1 p L p ( M r ) p C r p s max k = 1 n ( λ s max / s k 1 ) s k p τ u t + p 1 p L p ( M λ r ) p ,

where p = n p n p s ¯ .

For I 2 , we use Lemma 2.2 again to have

I 2 = 2 M λ r M λ r τ ( x ) τ ( y ) p u t + p 1 ( x ) μ ( x , d y ) d x C r p s max k = 1 n ( λ s max / s k 1 ) s k p u t + p 1 L 1 ( M λ r ) .

For I 3 , assuming that supp ( τ ) M ( λ + 1 ) r / 2 and using Lemma 2.2, we deduce

I 3 C M λ r R n M λ r ( u p 1 ( x ) + u p 1 ( y ) ) τ p ( x ) u t ( x ) μ ( x , d y ) d x C r p s max k = 1 n ( λ s max / s k 1 ) s k p u t + p 1 L 1 ( M λ r ) + C ε 1 p sup x M ( λ + 1 ) r / 2 R n M λ r u p 1 ( y ) μ ( x , d y ) u t + p 1 L 1 ( M λ r ) .

Moreover, we estimate

( f , τ p u t ) ε 1 p R n f τ p u t + p 1 d x ε 1 p f L q / ( p s ¯ ) ( M λ r ) τ p u t + p 1 L q / ( q p s ¯ ) ( M λ r ) = ε 1 p f L q / ( p s ¯ ) ( M λ r ) τ u t + p 1 p L p q / ( q p s ¯ ) ( M λ r ) p .

By using Lyapunov’s inequality and Young’s inequality, we have

v p q / ( q p s ¯ ) p v p n p / q v p ( q p n p ) / q n q ω v p p + q n q ω n / ( q n ) v p p

for any v L p L p and any ω > 0 . This yields that

( f , τ p u t ) ε 1 p f L q / ( p s ¯ ) ( M λ r ) n q ω τ u t + p 1 p L p p + q n q ω n / ( q n ) τ u t + p 1 p L p p r p s max q n q n q ω τ p u t + p 1 L γ + q n q ω n / ( q n ) τ p u t + p 1 L 1 .

Combining all the estimates, we have

τ p u t + p 1 L γ ( M λ r ) C r p s max 1 + k = 1 n ( λ s max / s k 1 ) s k p u t + p 1 L 1 ( M λ r ) + C r p s max q n q n q ω τ p u t + p 1 L γ ( M λ r ) + q n q ω n / ( q n ) τ p u t + p 1 L 1 ( M λ r ) .

Taking ω = ε 0 r p s max q n q with ε 0 > 0 small enough, we arrive at

u 1 L ( t p + 1 ) γ ( M r ) t p + 1 τ p u t + p 1 L γ ( M λ r ) C 1 + k = 1 n ( λ s max / s k 1 ) s k p r p s max u 1 L t p + 1 ( M λ r ) t p + 1 ,

where C depends on n , p , p , t , s 0 , q , and Λ and is bounded when t is bounded away from p 1 . Since λ 2 , we obtain

k = 1 n ( λ s max / s k 1 ) s k p k = 1 n ( λ 1 / s k 1 ) s k p k = 1 n 2 p = n 2 p ,

from which the desired result follows.□

The standard iteration technique proves the following lemma, see [25,14].

Lemma 3.5

Under the same assumptions as in Lemma 3.3, for any p 0 > 0 , there is a constant C = C ( n , p , p , q , p 0 , s 0 , Λ ) > 0 such that

(3.5) inf M r u C M 2 r u ( x ) p 0 d x 1 / p 0 .

The proof of Theorem 1.4 follows from Theorem 3.2, Lemma 3.5, and the triangle inequality.

4 Hölder estimates

This section is devoted to the proof of Theorem 1.5. The general scheme for the derivation of a priori interior Hölder estimates from the weak Harnack inequality in the nonlocal setting has been developed in [25] and applied successfully to the anisotropic setting [14] when p = 2 . We extend the result presented in [14] to the general case p > 1 .

Recall that the rectangles in Definition 1.1 satisfy the following property. For λ > 0 and Ω R n open, we have

Ω μ axes ( u Ψ , v Ψ ) = λ ( n s ¯ p ) s max / s ¯ Ψ ( Ω ) μ axes ( u , v ) for every u , v V p , μ axes ( Ω R n )

and

( f Ψ , φ Ψ ) = λ n s max / s ¯ ( f , φ ) for every f L q / ( p s ¯ ) ( Ω ) , φ H Ω p , μ axes ( R n ) ,

where Ψ : R n R n is a diffeomorphism given by

(4.1) Ψ ( x ) = λ s max / s 1 0 0 λ s max / s n x .

The rectangles from Definition 1.1 are balls in a metric space ( R n , d ) , where the metric d : R n × R n [ 0 , ) is defined as follows:

d ( x , y ) = sup k { 1 , , n } x k y k s k / s max .

By the scaling property and covering arguments provided in [14], it is enough to show the following theorem.

Theorem 4.1

Let Λ 1 and s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . Let 1 < p < n / s ¯ . Assume f L q / ( p s ¯ ) ( M 1 ) for some q > n . There are α = α ( n , p , p , q , s 0 , Λ ) ( 0 , 1 ) and C = C ( n , p , p , q , s 0 , Λ ) > 0 such that for each μ K ( p , s 0 , Λ ) and every u V p , μ ( M 1 R n ) satisfying

μ ( u , φ ) = ( f , φ ) for any φ H M 1 p , μ ( R n ) ,

we have u C α at 0 and

u ( x ) u ( 0 ) C ( u L ( R n ) + f L q / ( p s ¯ ) ( M 15 / 16 ) ) d ( x , 0 ) α

for all x M 1 .

Proof

We assume that 2 u L ( R n ) + κ 1 f L q / ( p s ¯ ) ( M 15 / 16 ) 1 for some κ > 0 , which will be chosen later. It is enough to construct sequences { a k } k = 0 and { b k } k = 0 such that a k u b k in M 1 / 4 k and b k a k = 4 α k for some α > 0 . For k = 0 , we set a 0 = 1 / 2 and b 0 = 1 / 2 . Assume that we have constructed such sequences up to k and let us choose a k + 1 and b k + 1 .

We assume

(4.2) { u ( b k + a k ) / 2 } M 1 2 4 k M 1 2 4 k / 2 ,

and then prove that we can choose a k + 1 and b k + 1 . If (4.2) does not hold, then we can consider u instead of u . Let Ψ be the diffeomorphism given by (4.1) with λ = 4 k and define

v ( x ) = u ( Ψ ( x ) ) a k ( b k a k ) / 2 and g ( x ) = λ p s max f ( Ψ ( x ) ) ( b k a k ) / 2 .

Then, v 0 in M 1 and M 1 μ ( v , φ ) = ( g , φ ) for every φ H M 1 μ ( R n ) . Moreover, it is easy to see that v 2 ( 1 4 α j ) in M 4 j for every j 0 by induction hypothesis. By applying Theorem 1.4, we obtain

(4.3) M 1 / 2 v p 0 ( x ) d x 1 / p 0 C inf M 1 / 4 v + C sup x M 15 / 16 R n M 1 v ( y ) p 1 μ ( x , d y ) 1 / ( p 1 ) + g L q / ( p s ¯ ) ( M 15 / 16 ) .

By taking α < p s 0 q n q , we have

(4.4) g L q / ( p s ¯ ) ( M 15 / 16 ) = 2 4 ( α p s max q n q ) k f L q / ( p s ¯ ) ( M 4 k 15 / 16 ) 2 κ .

For x M 15 / 16 and for each j 1 , we have M 4 j M 4 j + 1 R n M 4 j ( x ) . Hence, by (1.5),

(4.5) R n M 1 v ( y ) p 1 μ ( x , d y ) j = 1 M 4 j M 4 j + 1 ( 2 ( 4 α j 1 ) ) p 1 μ ( x , d y ) j = 1 ( 2 ( 4 α j 1 ) ) p 1 μ ( x , R n M 4 j ( x ) ) j = 1 l Λ ( 2 ( 4 α j 1 ) ) p 1 4 p s 0 j + 2 p 1 Λ j = l + 1 4 ( α ( p 1 ) p s 0 ) j .

If we assume that α < p s 0 2 ( p 1 ) , then we can make the last term in (4.5) as small as we want by taking l = l ( p , s 0 ) sufficiently large. Since the first term in (4.5) converges to 0 as α 0 , we have

(4.6) C sup x M 15 / 16 R n M 1 v ( y ) p 1 μ ( x , d y ) 1 / ( p 1 ) κ

by assuming further that α = α ( n , p , p , q , s 0 , Λ ) is sufficiently small.

On the other hand, it follows from (4.2) that

(4.7) M 1 / 2 v p 0 ( x ) d x 1 / p 0 1 M 1 / 2 M 1 / 2 { v 1 } v p 0 ( x ) d x 1 / p 0 2 1 / p 0 .

Combining (4.3), (4.4), (4.6), and (4.7), and choosing κ > 0 sufficiently small, we arrive at inf M 1 / 4 v κ 0 for some κ 0 . We take a k + 1 = a k + κ 0 ( b k a k ) / 2 and b k + 1 = b k , and make α and κ 0 small so that 1 κ 0 / 2 = 4 α . Then, a k + 1 u b k + 1 in M 4 ( k + 1 ) and b k + 1 a k 1 = 4 α ( k + 1 ) , which finishes the proof.□

  1. Funding information: Jamil Chaker gratefully acknowledges support by the Deutsche Forschungsgemeinschaft (SFB 1283/2 2021 – 317210226). Minhyun Kim gratefully acknowledges funding by the Deutsche Forschungsgemeinschaft (GRK 2235/2 2021 - 282638148).

  2. Conflict of interest: The authors state no conflict of interest.

Appendix A Algebraic inequalities

In this section, we prove Lemma 3.4 using the series of following lemmas.

Lemma A.1

Let a , b > 0 and t > p 1 > 0 . Then,

b a p 2 ( b a ) ( a t b t ) t p t p + 1 p a t + p 1 p b t + p 1 p p .

Proof

We may assume that b > a . Let f ( x ) = x t + p 1 p and g ( x ) = x t , and then by using Jensen’s inequality, we have

f ( b ) f ( a ) b a p = a b f ( x ) d x p a b ( f ( x ) ) p d x = 1 t t p + 1 p p a b g ( x ) d x = 1 t t p + 1 p p g ( b ) g ( a ) b a ,

which proves the lemma.□

Lemma A.2

Let a , b > 0 and t > p 1 > 0 . Then,

b a p 1 min { a t , b t } p t p + 1 p 1 a t + p 1 p b t + p 1 p p 1 min a t + p 1 p , b t + p 1 p .

Proof

We may assume that b > a . Let f ( x ) = x t + p 1 p , then

f ( b ) f ( a ) b a p 1 = a b f ( x ) d x p 1 = t p + 1 p p 1 a b x t 1 p d x p 1 t p + 1 p p 1 a b b t 1 p d x p 1 = t p + 1 p p 1 b t b t + p 1 p ,

which proves the lemma.□

Lemma A.3

Let τ 1 , τ 2 [ 0 , 1 ] and p > 1 . Then,

τ 1 p τ 2 p p τ 1 τ 2 max { τ 1 p 1 , τ 2 p 1 } .

Proof

The desired inequality follows from the convexity of the function f ( τ ) = τ p .□

Lemma A.4

Let a , b > 0 , τ 1 , τ 2 [ 0 , 1 ] , and t > p 1 > 0 . Then,

(A.1) min { τ 1 p , τ 2 p } a t + p 1 p b t + p 1 p p 2 1 p τ 1 a t + p 1 p τ 2 b t + p 1 p p τ 1 τ 2 p max { a t + p 1 , b t + p 1 }

and

(A.2) max { τ 1 p , τ 2 p } a t + p 1 p b t + p 1 p p 2 p 1 τ 1 a t + p 1 p τ 2 b t + p 1 p p + 2 p 1 τ 1 τ 2 p max { a t + p 1 , b t + p 1 } .

Proof

For (A.1), we assume that τ 1 τ 2 . Then, we obtain from

τ 1 a t + p 1 p τ 2 b t + p 1 p = τ 2 a t + p 1 p b t + p 1 p + ( τ 1 τ 2 ) a t + p 1 p

that

2 1 p τ 1 a t + p 1 p τ 2 b t + p 1 p p τ 2 p a t + p 1 p b t + p 1 p p + τ 1 τ 2 p a t + p 1 τ 2 p a t + p 1 p b t + p 1 p p + τ 1 τ 2 p max { a t + p 1 , b t + p 1 } ,

from which (A.1) follows. The other case τ 1 < τ 2 can be proved in the same way.

For (A.2), we assume that τ 1 τ 2 . Then,

max { τ 1 p , τ 2 p } a t + p 1 p b t + p 1 p p = τ 1 a t + p 1 p τ 2 b t + p 1 p + ( τ 2 τ 1 ) b t + p 1 p p 2 p 1 τ 1 a t + p 1 p τ 2 b t + p 1 p p + 2 p 1 τ 2 τ 1 p b t + p 1 .

The proof for the case τ 1 < τ 2 is the same.□

Proof of Lemma 3.4

We may assume that b > a . We begin with the equality

(A.3) b a p 2 ( b a ) ( τ 1 p a t τ 2 p b t ) = ( b a ) p 1 ( a t b t ) τ 1 p + ( b a ) p 1 b t ( τ 1 p τ 2 p ) A + B .

By Lemma A.1 and (A.1), we have

(A.4) A t p t p + 1 p a t + p 1 p b t + p 1 p p min { τ 1 p , τ 2 p } t p t p + 1 p 2 1 p τ 1 a t + p 1 p τ 2 b t + p 1 p p τ 1 τ 2 p max { a t + p 1 , b t + p 1 } .

For B , we use Lemmas A.2, A.3, and Young’s inequality to obtain

B p p t p + 1 p 1 a t + p 1 p b t + p 1 p p 1 b t + p 1 p τ 1 τ 2 max { τ 1 p 1 , τ 2 p 1 } ( p 1 ) p t p + 1 p ε p / ( p 1 ) a t + p 1 p b t + p 1 p p max { τ 1 p , τ 2 p } 1 ε p b t + p 1 τ 1 τ 2 p

for any ε > 0 . By using (A.2), we have

(A.5) B 2 p 1 ( p 1 ) p t p + 1 p ε p / ( p 1 ) τ 1 a t + p 1 p τ 2 b t + p 1 p p 2 p 1 ( p 1 ) p t p + 1 p ε p / ( p 1 ) + 1 ε p τ 1 τ 2 p max { a t + p 1 , b t + p 1 } .

Combining (A.3)–(A.5), and then taking ε so that 2 p 1 ε p / ( p 1 ) = 2 1 p , we arrive at

b a p 2 ( b a ) ( τ 1 p a t τ 2 p b t ) c 1 τ 1 a t + p 1 p τ 2 b t + p 1 p p c 2 τ 1 τ 2 p ( a t + p 1 + b t + p 1 ) ,

where

c 1 = 2 1 p p p ( t p + 1 ) p 1 and c 2 = ( t + 2 1 p ( p 1 ) ) p t p + 1 p + 2 2 ( p 1 ) 2 .

Note that c 1 and c 2 are bounded when t is bounded away from p 1 .□

B Anisotropic dyadic rectangles

Let us briefly sketch the construction of anisotropic “dyadic” rectangles. These objects can be used to prove the lower bound in L p for the sharp maximal function M u .

We construct anisotropic dyadic rectangles having the following properties:

  1. For each integer k Z , a countable collection { Q k , α } α covers the whole space R n .

  2. Each Q k ( = Q k , α for some α ) has an interior of the form Int ( Q k ) = M 2 k ( x ) . We call Q k an anisotropic dyadic rectangle of generation k.

  3. Every Q k , α is contained in Q k 1 , β for some β . We call Q k 1 , β a predecessor of Q k , α .

  4. If Q k , 0 , , Q k , 2 n are 2 n + 1 different anisotropic dyadic rectangles of generation k , then i = 0 2 n Q k , i = .

  5. If 2 n + 1 different anisotropic dyadic rectangles Q k 0 , , Q k 2 n , k 0 k 2 n , have a nonempty intersection, then Q j Q i for some 0 i < j 2 n .

Remark B.1

  1. A predecessor may not be unique.

  2. 2 n different anisotropic dyadic rectangles from the same generation may have a nonempty intersection.

Such a family of anisotropic dyadic rectangles can be easily constructed. Since the sets are rectangles, it is sufficient to exemplify the construction in one dimension. Let Q 0 = [ 0 , 1 ) . Then, a countable collection { Q 0 + z } z Z constitutes the zeroth generation. Let N = 2 s max / s 1 . In order to construct the first generation, we take a disjoint family of (left-closed and right-opened) N intervals in Q 0 starting from 0 with length 2 s max / s 1 such that the following interval starts at the endpoint of the previous interval. If the right-endpoint of the last interval is 1, then these intervals constitute the first generation, and there is nothing to do. Thus, we assume from now on that 2 s max / s 1 Z . In this case, we add an interval [ 1 2 s max / s i , 1 ) so that

Q 0 = i = 0 N 1 Q 1 , i Q 1 , N ,

where

Q 1 , i = [ i 2 s max / s 1 , ( i + 1 ) 2 s max / s 1 ) for i = 0 , , N 1 , Q 1 , N = [ 1 2 s max / s i , 1 ) ,

and N = 2 s max / s 1 . Then, the collection { Q 1 , i + z } 0 i N , z Z forms the first generation of intervals satisfying (i)–(iv) (Figure A1).

Figure A1 
                  This figure shows the construction of the family 
                        
                           
                           
                              
                                 
                                    Q
                                 
                                 
                                    1
                                    ,
                                    i
                                 
                              
                           
                           {Q}_{1,i}
                        
                     .
Figure A1

This figure shows the construction of the family Q 1 , i .

We continue to construct the intervals of generation 2 that fill in Q 1 , i for each 0 i N 2 . However, we have to be careful in filling in Q 1 , N 1 and Q 1 , N since Q 1 , N 1 Q 1 , N . Suppose that we filled in Q 1 , N 1 and Q 1 , N as above, i.e.,

Q 1 , N 1 = i = 0 N 1 Q 2 , i Q 2 , N and Q 1 , N = i = 0 N 1 Q ˜ 2 , i Q ˜ 2 , N

for some intervals Q 2 , i and Q ˜ 2 , i , 0 i N , of length 4 s max / s 1 . Let K be the smallest integer such that Q 2 , K ¯ Q 1 , N . Then, we have

Q 1 , N 1 Q 1 , N = i = 0 K Q 2 , i i = 0 N 1 Q ˜ 2 , i Q ˜ 2 , N

and at most two different intervals among { Q 2 , 0 , , Q 2 , K , Q ˜ 2 , 0 , , Q ˜ 2 , N } can intersect. Therefore, these intervals constitute the second generation satisfying (i)–(iv) (Figure A2).

Figure A2 
                  This figure shows the construction of generation 2.
Figure A2

This figure shows the construction of generation 2.

In this way, we construct intervals of generation k for all k 0 .

Let us now construct intervals of generation k < 0 . It is easy to observe that a collection { Q 1 + N z } z Z of intervals of generation 1 satisfies (i)–(iv), where

Q 1 = [ 0 , 2 s max / s 1 ) .

For the generation of 2 , let K be the largest integer such that Q 1 + N K Q 2 , where Q 2 = [ 0 , 4 s max / s 1 ) . Then, the intervals Q 2 + N ( K + 1 ) z , z Z , form the generation of 2 , which satisfying (i)–(iv). We continue this process to construct intervals of all generations k < 0 .

We show that the intervals constructed in this way satisfy the property (v) as well. Suppose that three different intervals Q k 0 , Q k 1 , and Q k 2 , k 0 k 1 k 2 , have a nonempty intersection. If k 1 = k 2 , then Q k 1 Q k 0 or Q k 2 Q k 0 . If k 1 < k 2 , then either Q k 2 Q k 1 or not. In the former case, we are done. In the latter case, Q k 2 Q ˜ k 1 for some Q ˜ k 1 Q k 1 , which reduces to the case k 1 = k 2 .

C Sharp maximal function theorem

In this section, we prove Theorem 2.6 by using the anisotropic dyadic rectangles. For u L loc 1 ( R n ) , we define a dyadic maximal function M d u by

M d u ( x ) = sup x Q Q u ( y ) d y ,

where the supremum is taken over all anisotropic dyadic rectangles Q . Since

(C.1) M d u M u ,

Theorem 2.5 also holds for the dyadic maximal function M d u . We first prove a good-lambda estimate using the dyadic maximal function. See [31, Theorem 3.4.4].

Theorem C.1

Let s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) . There exists a constant C = C ( n , s 0 ) > 0 such that

{ x R n : M d u ( x ) > 2 λ , M u ( x ) γ λ } C γ { x R n : M d u ( x ) > λ }

for all γ > 0 , λ > 0 , and u L loc 1 ( R n ) .

Proof

Let Ω λ = { x R n : M d ( f ) ( x ) > λ } . We may assume that Ω λ < + since otherwise there is nothing to prove. For each x Ω λ , we find a maximal anisotropic dyadic rectangle Q x such that

(C.2) x Q x Ω λ and Q x f > λ .

There are at most 2 n different maximal anisotropic dyadic rectangles of the same generation satisfying (C.2), but we can still choose anyone of them. Let Q j be the collection of all such rectangles Q x for all x Ω λ . Then, we have Ω λ = j Q j . Note that different rectangles Q j may have an intersection, but the intersection is contained in at most 2 n different maximal rectangles of the same generation. This is a consequence of the properties (iv) and (v) of anisotropic dyadic rectangles. Hence,

j Q j 2 n Ω λ .

Therefore, the desired result follows once we have

(C.3) { x Q j : M d u ( x ) > 2 λ , M u ( x ) γ λ } C γ Q j

for some C = C ( n , s 0 ) . Indeed, one can prove (C.3) by following the second paragraph of the proof of [31, Theorem 3.4.4], using Theorem 2.5 for M d , and replacing [31, equation (3.4.8)] by

1 λ Q j u ( y ) ( u ) Q j d y 2 n s max / s ¯ λ Q j Q j Q j u ( y ) ( u ) Q j d y 2 n / s 0 λ Q j M u ( ξ j )

for all ξ j Q j , where Q j is anyone of predecessors of Q j .□

Theorem C.2

Let s 1 , , s n [ s 0 , 1 ) be given for some s 0 ( 0 , 1 ) , and let 0 < p 0 p < . Then, there is a constant C = C ( n , p , s 0 ) > 0 such that for all functions u L loc 1 ( R n ) with M d u L p 0 ( R n ) , we have

M d u L p ( R n ) C M u L p ( R n ) .

Theorem C.2 can be proved in the same way as in the proof of [31, Theorem 3.4.5] except that we use Theorem C.1 instead of [31, Theorem 3.4.4]. Finally, we combine the inequality

u L p ( R n ) M d u L p ( R n ) ,

which comes from the Lebesgue differentiation theorem and Theorem C.2 to conclude Theorem 2.6. See [31, Corollary 3.4.6].

D Pointwise convergence of the fractional orthotropic p-Laplacian

This section provides the proof of pointwise convergence of the fractional orthotropic p-Laplacian as s 1 .

Proposition D.1

Let u C 2 ( R n ) L ( R n ) and x R n be such that i u ( x ) 0 for all i = 1 , , n . Let s i = s for all i = 1 , , n . Let L be the operator in (1.2) with μ = μ axes and A loc p be as in (1.3). Then, Lu ( x ) A loc p u ( x ) as s 1 up to a constant.

Proof

Let us fix a point x R n with i u ( x ) 0 . For each i = 1 , , n , let us define u i : R R by u i ( x i ) = u ( x 1 , , x i , , x n ) as a function of one variable. Then, u i C 2 ( R ) L ( R ) and u ( x i ) 0 . We write

Lu ( x ) = i = 1 n s ( 1 s ) R u i ( y i ) u ( x i ) p 2 ( u i ( y i ) u i ( x i ) ) x i y i 1 + s p d y i = i = 1 n ( 2 ) p s u i ( x i ) ,

which is the sum of one-dimensional fractional p-Laplacians. By [11, Theorem 2.8], we have

( 2 ) p s u i ( x i ) d d x i d u i d x i ( x i ) p 2 d u i d x i ( x i )

as s 1 , for each i = 1 , , n , up to a constant depending on p only. Consequently, by summing up, Lu ( x ) A loc p u ( x ) as s 1 .□

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Received: 2021-04-27
Revised: 2021-11-18
Accepted: 2022-02-04
Published Online: 2022-03-28

© 2022 Jamil Chaker and Minhyun Kim, published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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