# Symmetry and monotonicity of least energy solutions

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1 Symmetry and monotonicity of least energy solutions Jaeyoung BYEO, Louis JEAJEA and Mihai MARIŞ Abstract We give a simple proof of the fact that for a large class of quasilinear elliptic equations and systems the solutions that minimize the corresponding energy in the set of all solutions are radially symmetric. We require just continuous nonlinearities and no cooperative conditions for systems. Thus, in particular, our results cannot be obtained by using the moving planes method. In the case of scalar equations, we also prove that any least energy solution has a constant sign and is monotone with respect to the radial variable. Our proofs rely on results in [15, 6] and answer questions from [3, 12]. 1 Introduction We consider the system of partial differential equations div( u i p 2 u i ) = g i (u), i = 1,..., m, (1) where u = (u 1,..., u m ) : R R m, 1 < p, (y 1,..., y ) p = ( j=1 y 2 j ) p 2, g i (0) = 0 and there exists G C 1 (R m \ {0}, R) C(R m, R) such that g i (u) = G u i (u) for u 0. Formally, solutions of (1) are critical points of the following energy functional S(u) = 1 p m R i=1 u i p dx G(u) dx. R The aim of this note is to prove, under general assumptions, that those solutions of (1) which minimize the energy S in the set of all solutions are radially symmetric (up to a translation in R ). In the scalar case we also study the sign and monotonicity of these solutions. We do not consider here the problem of existence of solutions (respectively of least energy solutions) for (1). We believe that our results cover all situations where the existence of a least energy solution is already known in the literature. We begin with some definitions. Let Π be an affine hyperplane in R, let Π and Π be the two closed half-spaces determined by Π and s Π the symmetry with respect Department of Mathematics and PMI, Pohang University of Science and Technology, Pohang, Kyungbuk , Republic of Korea, Département de Mathématiques UMR 6623, Université de Franche-Comté, 16, Route de Gray, Besançon, France, Département de Mathématiques UMR 6623, Université de Franche-Comté, 16, Route de Gray, Besançon, France, 1

2 to Π (i.e. s Π (x) = 2p Π (x) x, where p Π is the orthogonal projection onto Π). Given a function f defined on R, we define f Π (x) = { { f(x) if x Π f(x) if x Π f(s Π (x)) if x Π, f Π (x) = f(s Π (x)) if x Π. (2) For σ > 0, we denote f σ (x) = f( x σ ). We say that a space X of functions defined on R is admissible if X is nonempty and (i) X L 1 loc (R, R m ) and measure({x u(x) > α}) < for any u X and α > 0; (ii) g i (u) L 1 loc (R ) for any u X and i = 1,..., m; (iii) m i=1 u i p and G(u) belong to L 1 (R ) if u X ; (iv) u σ X for any u X and σ > 0; (v) u Π, u Π X whenever u X and Π is an affine hyperplane in R. Let X be an admissible function space. We note that from (i) and (iii), G(0) = 0. A function u X is a solution of (1) if it satisfies (1) in D (R ). If (1) admits solutions in X, we say that u is a least energy solution if u is a nontrivial solution of (1) and S(u) = inf{s(u) u X \ {0}, u is a solution of (1)}. We introduce the functionals J(u) = 1 p R i=1 m u i p dx and V (u) = G(u) dx. R Clearly, these functionals are well-defined on any admissible function space. As we will see, the least energy solutions of (1) come from the following minimization problem: minimize J(u) in the set { u X V (u) = λ}. (P λ ) We shall prove that under some general conditions (see (C1)-(C3) or (D1)-(D3) below), all least energy solutions of (1) in the set X are radially symmetric, up to a translation in R. It is easy to see that J(u σ ) = σ p J(u) and V (u σ ) = σ V (u). If V (u) > 0 for some u X, we have V (u σ ) = 1 for σ = V (u) 1. Then, denoting we see that T = inf {J(u) u X and V (u) = 1}, J(v) T (V (v)) p for any v X satisfying V (v) > 0. (3) It is clear that u is a minimizer for problem (P λ ) above (λ > 0) if and only if u σ1 minimizer for (P 1 ), where σ 1 = λ 1. We assume first that 1 < p < and the following conditions are satisfied. is a (C1) T > 0 and problem (P 1 ) has a minimizer u X ; 2

3 (C2) Any minimizer u X of (P 1 ) is a C 1 function and satisfies the Euler-Lagrange system of equations for i = 1,..., m and some α R; div( u i p 2 u i ) = αg i (u) in D (R ) (4) (C3) Any solution u X of (4) (and not only any minimizer!) satisfies the Pohozaev identity ( p)j(u) = αv (u). (5) A few comments are in order. Clearly, the most important of the conditions above is (C1). To our knowledge, the existence of a minimizer for (P 1 ), under sufficiently general assumptions on the functions g i and for arbitrary m and p (1, ), is still an open problem. However, several particular cases have been extensively studied in the literature. A series of papers has been devoted to the case p = 2 and fairly optimal conditions on g i that guarantee (C1) have been found by Berestycki-Lions [1] for m = 1 and by Brezis-Lieb [3] for m 1. In the case m = 1 and 1 < p < the existence of a minimizer for (P 1 ) has also been proved in [9] under general assumptions on g = g 1 (similar to the assumptions in [1]). Under the conditions considered in [1] and [2], the functionals J and V are well defined on H 1 (R ) and this is clearly an admissible function space. The settings in [3] and [9] also correspond to our assumptions. If T > 0 and (P 1 ) admits minimizers, in most applications it is quite standard to prove that (C2) and (C3) hold. This is indeed the case under the assumptions in [1, 3, 9]. ext we consider the case p =. ote that in this case the Pohozaev identity (5) becomes αv (u) = 0; hence any reasonable solution u of (1) should satisfy V (u) = 0. Since we are interested in nontrivial solutions, we consider the minimization problem minimize J(u) in the set { u X \ {0} V (u) = 0}. (P 0 ) We assume that the following conditions are satisfied. (D1) T 0 := inf{j(u) u X, u 0, V (u) = 0} > 0 and (P 0 ) admits a minimizer u 0; (D2) Any minimizer u X of (P 0 ) is C1 and satisfies the Euler-Lagrange equations (4) for some α > 0; (D3) Any solution u X of (4) (with α > 0) satisfies the Pohozaev identity V (u) = 0. For p = = 2, fairly optimal conditions on g i that guarantee (D1)-(D3) have been found by Berestycki-Gallouët-Kavian [2] for m = 1 and by Brezis-Lieb [3] for m 1. In the next section we show that least energy solutions are minimizers of (P λ ) for some particular choice of λ if 1 < p <, respectively minimizers of (P 0 ) if p =. Then we obtain the radial symmetry of such solutions as a direct consequence of the general results in [15] (in the case = p, we need some extra-argument in addition to the results in [15]). In the third section we consider the scalar case m = 1 and we prove that least energy solutions have constant sign and, if they tend to zero at infinity, then they are monotone with respect to the radial variable. In the final section we make some connections with related results of symmetry and monotonicity in the literature. Let us just mention that, especially in the scalar case, the symmetry and monotonicity of solutions of (1) have been studied by many authors, see 3

4 e.g. [11, 16, 8, 7] and references therein. In most of these works it is assumed that the solutions are nonnegative and some further assumptions on the nonlinearity g are made. They require, at least, g to be Lipschitz continuous and to satisfy a cooperative condition in the case of systems. In the present work, we do not make any additional assumptions on g, except those that guarantee the existence of least energy solutions (basically, we need g to be merely continuous and to satisfy some growth conditions near zero and infinity, but we do not need any sign or monotonicity assumption; see [3] and [9]). We prove that our solutions have constant sign and our results are valid as well for compactly supported solutions and for solutions that do not vanish. Of course, there is a price we have to pay: our method works only for least energy solutions, not for any nonnegative solution of (1). 2 Variational characterization and symmetry We begin with the case 1 < p <. Lemma 1 Assume that 1 < p < and the conditions (C1)-(C3) hold. (i) Let u be a minimizer for (P 1 ). Then u σ0 is a least action solution of (1), where ( ) 1 σ 0 = p T p, and S(u σ0 ) = p( p) p 1 p T p. (ii) Let v be a least energy solution for (1). Then v is a minimizer for (P λ ), where ( ) λ = p T p. Proof. (i) By (C2) we know that u C 1 and u satisfies (4) for some α R. Then (5) implies ( p)j(u) = αv (u), which gives α = p T > 0. It is easy to see that u σ0 satisfies (1) for σ 0 = α 1 p and S(u σ0 ) = σ p 0 J(u) σ 0 V (u) = σ p 0 T σ 0 = p( p) p 1 p T p. Let w X, w 0, be a solution of (1). By (C3) we have ( p)j(w) = V (w). If J(w) = 0, we have w = 0 a.e. on R, hence w must be constant. Since measure{x R w(x) > α} < for any α > 0, we infer that w = 0, a contradiction. Thus J(w) > 0 and V (w) = p p J(w) > 0. On the other hand, by (3) we get J(w) T (V (w)), i.e. ) p J(w) T J(w), which gives ( p ( p J(w) Combined with Pohozaev identity, this implies ) p p T p. (6) S(w) = J(w) V (w) = p J(w) p( p) p 1 p T p = S(u σ0 ) (7) and we infer that u σ0 is a least energy solution for (1). (ii) Conversely, let v be a least energy solution for (1). Then ( p)j(v) = V (v) by (C3), hence S(v) = p J(v). It is obvious that the inequalities (6) and (7) above are satisfied with w = v. On the other hand, S(v) = S(u σ0 ) and we infer that v must satisfy (7) with equality sign, that is, ( p J(v) = ) p p T p and V (v) = p ( ) p J(v) = p T p. 4

5 A simple scaling argument shows that v is a minimizer for (P λ ), where λ = ( ) p 1 T p = σ0 1 ( ) p p T p ; equivalently, v σ1 is a minimizer for (P 1 ), where σ 1 =. This completes the proof of Lemma 1. The symmetry of least energy solutions will follow from Lemma 1 and a general symmetry result in [15]. For the convenience of the reader, we recall here that result. Theorem 2 ([15]) Let 2. Assume that u : R R m belongs to some function space Y and solves the minimization problem minimize F (u(x), u(x) ) dx { R } (P) in the set u Y H(u(x), u(x) ) dx = λ 0. R Suppose that the following conditions are satisfied: (A1) For any v Y and any affine hyperplane Π in R we have v Π, v Π Y. (A2) Problem (P) admits minimizers in Y and any minimizer is a C 1 function on R. Then, after a translation, u is radially symmetric. Lemma 1 implies that least energy solutions solve the minimization problem (P λ ) for some λ > 0. Conditions (C1), (C2) and property (v) in the definition of admissible spaces imply that (P λ ) satisfies the assumptions of Theorem 2. Thus we get: Proposition 3 Assume that 1 < p < and (C1)-(C3) hold. Then (1) admits a least energy solution and each least energy solution is radially symmetric (up to a translation in R ). ow we turn our attention to the case p =. Proposition 4 Assume that p = and (D1)-(D3) hold. Then (1) admits a least energy solution and any least energy solution solves (P 0 ). Moreover, if we assume that G is either negative or positive in some ball B R m(0, ε) \ {0} and u X is a least energy solution such that u(x) 0 as x, then u is radially symmetric (up to a translation in R ). Proof. Let u 0 be a minimizer for (P 0 ). By (D2) and (D3) we have V (u 0) = 0 and u 0 satisfies (4) for some α > 0. Let u 1 = (u 0 ) σ, where σ = α 1 p. It is easy to see that u 1 solves (1) and S(u 1 ) = J(u 1 ) V (u 1 ) = J(u 0 ) σ V (u 0 ) = J(u 0 ) = T 0. For any solution u X, u 0 of (1) we have V (u) = 0 by (D3) and S(u) = J(u) T 0 = J(u 1 ). Hence u 1 is a least energy solution. If v is a least energy solution, then V (v) = 0 by (D3) and J(v) = S(v) = S(u 1 ) = T 0, thus v solves (P 0 ). Although Theorem 2 does not apply directly to minimizers of problem (P 0 ) (because the value of the constraint in (P 0 ) is zero), its proof can still be adapted to those minimizers. Indeed, the only place where the assumption λ 0 is needed in Theorem 2 is to show that for any e S 1 there exists an affine hyperplane Π orthogonal to e such that H(u(x), u(x) ) dx = H(u(x), u(x) ) dx = λ Π Π 2. (8) 5

6 From (8) it follows then easily that u Π and u Π are also minimizers. (In fact, if = 2 the assumption λ 0 was also used in the proof of Theorem 2 to show that a minimizer u of (P) could not be of the form u(x) = ũ( x ) on R 2, with ũ : [0, ) R m periodic and nonconstant. In our setting it is clear that no minimizer u of (P 0 ) could be of this form because J(u) is finite.) In the present case we will use the fact that G(u) has a constant sign in a neighborhood of to find hyperplanes that split the constraint in two equal parts. A similar idea has already been used in [14]. Henceforth we assume that u is a least action solution, u(x) 0 as x and, say, G(ξ) < 0 for 0 < ξ < ε. For e S 1 and t R, we denote Π e,t = {x R x e = t}, Π e,t = {x R x e < t} and Π e,t = {x R x e > t}. We claim that for any e S 1, there exists t e R such that Π G(u(x)) dx = Π G(u(x)) dx = 0 and u Π To see this, fix e S 1 and define ϕ ± e (t) = Π ± e,t 0, u Π 0. (9) G(u(x)) dx, respectively. It follows that ϕ e and ϕ e are continuous because G(u) L 1 (R ). Since u is continuous, u 0, lim x u(x) = 0 and G < 0 on B R m(0, ε) \ {0}, it is not hard to see that there exist t, t R, t < t such that ϕ e (t ) < 0, ϕ e (t ) < 0 and u Π e,t 0, u Π e,t 0. Since ϕ e (t ) = V (u) ϕ e (t ) = ϕ e (t ), it follows that ϕ e (t ) < 0 < ϕ e (t ). From the mean value property, we see that there exists t e (t, t ) satisfying (9). It is clear that u Π, u Π X \ {0} because X is admissible and (9) implies that V (u Π ) = V (u Π is easy to see that J(u Π ) = 0, hence J(u Π ) J(u Π are also minimizers for (P 0 ) T 0, J(u Π ) T 0. On the other hand, it ) = 2J(u) = 2T 0. Thus J(u Π ) = J(u Π ) = T 0 ). Then arguing exactly as in the proof of and u Π, u Π Theorem 2 in [15], it follows that after a translation, u is radially symmetric. Remark 5 The situation is different for p >. The system (1) may still have solutions in some cases, and least energy solutions may also exist. For instance, if = 1 and p = 2 it can be proved, under suitable assumptions on g, that (1) admits a finite energy solution which is unique up to translations; hence it is a least energy solution (and it is symmetric with respect to a point). The existence and the symmetry of least energy solutions for (1) in the case p > 2 would be interesting problems to consider. ote that whenever (1) admits finite energy solutions in the case p >, they cannot admit a variational characterization as in Lemma 1 or Proposition 4 above. Indeed, any reasonable solution u of (1) should satisfy the Pohozaev identity ( p)j(u) = V (u); if u is nontrivial, then necessarily V (u) < 0. It turns out that in any admissible function space X, a condition like (C1) cannot hold for p >, no matter what the nonlinearity g is. More precisely, denote T λ := inf{j(u) u X and V (u) = λ}. Let λ 0. We claim that either the set {u X V (u) = λ} is empty (thus T λ = ), or we have T λ = 0. To see this we argue by contradiction and we assume that there is some 6

7 λ 0 such that T λ > 0. Let u X be such that V (u) = λ and J(u) < 2T λ. Choose ε > 0 sufficiently small, so that ε < 1 2 and 2ε p 1 < 1. Let ϕ(t) = G(u) dx. The function {x 1 <t} ϕ is continuous, lim ϕ(t) = 0 and lim ϕ(t) = λ, hence there exist t 1, t 2 R, t 1 < t 2 t t { such that ϕ(t 1 ) = ε 2 λ and ϕ(t 2) = (1 ε u(x) if 2 )λ. Let u x1 t 1(x) = 1, u(2t 1 x 1, x ) if x 1 > t 1, { u(x) if x1 > t u 2 (x) = 2, u(2t 2 x 1, x where x ) if x 1 t 2, = (x 2,..., x ). A simple change of variables shows that V (u 1 ) = 2 G(u) dx = ελ and V (u 2 ) = 2 G(u) dx = {x 1 <t 1 } {x 1 >t 2 } ελ. Since J(u 1 ) J(u 2 ) = 2 m u i p dx 2J(u), we see that J(u 1 ) p {x 1 <t 1 } {x 1 >t 2 } i=1 J(u) or J(u 2 ) J(u). Assume that J(u 1 ) J(u) < 2T λ. For σ = ε 1 we have V ((u 1 ) σ ) = σ V (u 1 ) = λ and J((u 1 ) σ ) = σ p J(u 1 ) σ p J(u) < ε p 1 2T λ < T λ, contradicting the definition of T λ. Our claim is thus proved. 3 Monotonicity results Throughout this section we assume that m = 1. Given a measurable function f : R [0, ) such that measure({x R f(x) > α}) is finite for any α > 0, we denote by f the Schwarz rearrangement of f. We consider the following additional conditions for an admissible space X. (vi) For any u X and t 0, s 0, we have min(u, t) X and max(u, s) X. (vii) If u X and is a radial function and u 0 (respectively u 0), then u X (respectively ( u) X ). ote that assumption (vii) is needed only in the proof of Theorem 8 below. Proposition 6 Let X be an admissible function space such that for any v X the functions v = max(v, 0) and v = min(v, 0) belong to X. Assume that 1 < p < and (C1) holds. If u X is a solution of (P λ ) for some λ > 0, then u does not change sign. Proof. This is a simple consequence of scaling. Indeed, let u be as above. It is clear that V (u ) V (u ) = V (u) = λ and J(u ) J(u ) = J(u). If V (u ) < 0, then necessarily V (u ) > λ. For σ = ( λ V (u ) ) 1 (0, 1) we have V ((u ) σ ) = σ V (u ) = λ and J((u ) σ ) = σ p J(u ) σ p J(u) < J(u), contradicting the fact that u is a minimizer. Thus necessarily V (u ) 0. In the same way V (u ) 0, therefore V (u ), V (u ) [0, λ]. Using inequality (3) (which trivially holds if V (v) = 0), we get T λ p = J(u) = J(u ) J(u ) T V (u ) p T V (u ) p, which gives ( V (u ) 1 λ ) p ( V (u ) λ ) p. (10) Since V (u )V (u ) = λ, (10) implies that either V (u ) = 0 or V (u ) = 0. If V (u ) = 0 and V (u ) = λ we see that u satisfies the constraint and J(u ) = J(u) J(u ) J(u). (11) 7

8 Since u is a minimizer, we must have equality in (11) and this gives J(u ) = 0, hence u = 0 and u = u 0. Similarly V (u ) = 0 implies u = u 0. Proposition 7 Let an admissible space X satisfy the condition (vi). Assume that p = and (D1) holds. We have: (a) if G < 0 on [ ε, 0) (0, ε] for some ε > 0, then u X is a minimizer of (P 0 ) if and only if it solves the problem minimize J(v) in the set { v X v 0, V (v) 0}; (P 0 ) (b) if G > 0 on [ ε, 0) (0, ε], then u X solves (P 0 ) if and only if it solves the problem minimize J(v) in the set { v X v 0, V (v) 0}. (P 0 ) Moreover, any minimizer of (P 0 ) or (P 0 ) does not change sign. Proof. It clearly suffices to prove (a). Consider v X such that v 0 a.e. and V (v) > 0. For t 0 we define v t (x) = min(v(x), t). By (vi) we have v t X. We claim that there exists t > 0 such that V (v t ) = 0. The continuity of G, properties (i) and (iii) in the definition of admissible spaces and the dominated convergence theorem imply that the mapping t V (v t ) = G(v t (x)) dx R is continuous on (0, ). Since G(v ε (x)) < 0 whenever v(x) 0 and we cannot have v(x) = 0 a.e. because V (v) > 0, we infer that V (v ε ) < 0. We claim that there exists t 0 > ε such that V (v t 0 ) > 0. Two situations may occur: Case 1. There exists an increasing sequence t n such that {G(t n )} n=1 is bounded from below. Let m = inf n 1 G(t n ). By dominated convergence we get V (v tn ) V (v) = {v t n} G(t n ) G(v(x)) dx {v t n} m G(v(x)) dx 0 as n ; hence V (v t n ) 1 2V (v) > 0 for n sufficiently large. Case 2. G(s) as s. Then, since v 0 a.e. and V (v) > 0, we see that the set A = {s > 0 G(s) > 0} is nonempty. Let M = sup A <. It follows that G(s) 0 for s M. It is clear that M > ε and V (v M ) V (v) > 0. The claim is thus proved. ow the continuity of the mapping t V (v t ) implies that there exists t (ε, t 0 ) such that V (v t ) = 0. Similarly, if w X, w 0 a.e. and V (w) > 0 there is some t > 0 such that V ( ( w) t ) = 0. ext let u 0 X be a minimizer of (P 0 ). Suppose V (u) > 0 for some u X. Then at least one of the quantities V (u ) and V (u ) is positive. If V (u ) > 0, take t > 0 such that V (u t ) = 0. We have u t X \ {0} and J(u) J(u ) J(u t ) J(u 0 ) = T 0. (12) Hence inf{j(u) u X, u 0, V (u) 0} = J(u 0 ) = T 0 and u 0 is a solution of (P 0 ). Conversely, assume that u is a solution of (P 0 ). We prove that V (u ) = V (u ) = V (u) = 0. (13) 8

9 We argue again by contradiction. If (13) does not hold, the inequality V (u ) V (u ) = V (u) 0 implies that at least one of the quantities V (u ) and V (u ) must be positive. Suppose that V (u ) > 0. As above we find t > 0 such that V (u t ) = 0 and then (12) holds for u. Moreover, since u is a minimizer of (P 0 ) we have J(u) T 0 and therefore all inequalities in (12) are in fact equalities. But J(u ) = J(u t ) implies u p dx = 0, hence u = 0 a.e. on {u > t } which gives ((u t ) ) = 0 a.e. {u>t } and we infer that (u t ) = 0 a.e., that is u t a.e. Then we have u = u t and consequently V (u ) = V (u t ) = 0, contrary to our assumption. We argue similarly if V (u ) > 0 and (13) is proved. Since V (u) = 0 and J(u) = T 0 = J(u 0 ), we see that u solves (P 0 ). Lastly we show that if u is a minimizer of (P 0 ), then either u = 0 a.e. or u = 0 a.e. (but we cannot have u = u = 0 a.e. because J(u) = T 0 > 0). Indeed, if u 0 and u 0, (13) would imply J(u ) T 0 and J(u ) T 0 and this would give T 0 = J(u) = J(u ) J(u ) 2T 0 > 0, which is a contradiction. This completes the proof. ext we prove the monotonicity of scalar minimizers. Theorem 8 Let X be an admissible space satisfying the conditions (vi) and (vii). We assume that conditions (C1)-(C3) hold if 1 < p <, respectively conditions (D1)-(D3) hold if p =. In the case p =, we also assume that there exists ε > 0 such that either G > 0 or G < 0 on [ ε, 0) (0, ε]. Then any least energy solution u of (1) such that lim x u(x) = 0 is, up to a translation, radially symmetric and monotone with respect to r = x [0, ). Proof. Symmetry follows directly from Propositions 3 and 4. Hence there is a function ũ : [0, ) R such that u(x) = ũ( x ) = ũ(r). From Lemma 1 and Proposition 4 we know that any least energy solution is a minimizer of (P λ ) for some λ > 0, respectively of (P 0 ). We will show that whenever u(x) = ũ(r) solves one of these minimization problems and tends to zero at infinity, ũ is monotone on [0, ). The proof relies on Lemma 9 below. The first part of this Lemma is well known and the second part is a simple consequence of Lemma 3.2 p. 163 in [6]. Lemma 9 ([6]) Let w be a nonnegative measurable function defined on R such that for any t > 0 the function (w t) belongs to W 1,p (R ) and has compact support. Then we have w p dx w p dx. (14) R R Moreover, if equality holds in (14) then for any t (0, sup ess(w)) the level set {x R w(x) > t} is equivalent to a ball. ow let u be as above. From Proposition 6 and Proposition 7, we know that u has constant sign; hence we may assume that u 0. Since u C 1 and lim x u(x) = 0, we see that u is bounded and (u t) belongs to W 1,p (R ) and has compact support for any t > 0. By assumption (vii) we have u X. It is clear that V (u ) = V (u), u 0 if u 0, and Lemma 9 implies that J(u ) J(u). Since u is a minimizer of (P λ ) (respectively of (P 0 )), we have necessarily J(u) J(u ), and hence J(u) = J(u ). Using Lemma 9 again we infer that for any t (0, sup(u)), the set E t = {x R u(x) > t} is equivalent to a ball. 9

11 However, in the case p = 2 and 3, the symmetry, positivity and monotonicity of minimizers for problem (P λ ) have been proved in [10] in the zero-mass case (that is, when g(0) = g (0) = 0). The proofs in [10] rely on some sharp estimates of the decay of solutions at infinity (which are a consequence of the zero-mass condition) and on a result in [6]. ote that in [10] it is not assumed that g is continuous on R, but it is assumed that g 0 on (0, ) and g 0 on (, 0), respectively. Remark 12 If 1 < p < and m = 1, it has been proved in [9], under general conditions on g, that problem (P λ ) admits minimizers (thus (1) has least energy solutions). The minimizers found in [9] were radially symmetric by construction. It follows from Proposition 3 that any least energy solution is radially symmetric. If, in addition to the assumptions of Theorem 8, it is assumed that g is locally Lipschitz on (0, ) and non-increasing on some interval (0, s 0 ) and 1 < p < 2, it has been proved in [8] that any nonnegative solution of (1) is radially symmetric and that u(x) = ũ( x ) satisfies ũ (r) < 0 whenever r > 0 and ũ(r) > 0. The same result is true when p > 2 if it is assumed in addition that the critical set of the solution u is reduced to one point (see [16]). These assumptions are not necessary for us but, of course, we only deal with least energy solutions. Remark 13 (i) The symmetry results in Section 2 hold without any change if we replace m the functional J by a functional of the form A i (u, u i )dx where ξ A i (u, ξ) is p-homogeneous for any i = 1,..., m. R i=1 (ii) Our method still works for more general functionals of the form J(u) = 1 m x α A i (u) u i p dx and Ṽ (u) = x β G(u) dx. p R i=1 R In this case, using Theorem 1 in [15], we obtain that minimizers (and the corresponding minimum action solutions) are axially symmetric. Functionals of this type appear, e.g., in the Caffarelli-Kohn-irenberg problem (which consists in minimizing u q x aq dx under the constraint u p x bp dx = const., R R where q > 1, p > 1, a b < q and 0 < 1 q 1 p = 1a b ). It has been proved that minimizers for this problem exist and, in general, are not radially symmetric (see [4] and references therein). Acknowledgment The research of the first author was supported in part by KRF J02301 of Korea Research Foundation. References [1] H. Berestycki, P.-L. Lions, onlinear scalar field equations, I. Existence of a ground state, Arch. Rational Mech. Anal. 82 (1983), [2] H. Berestycki, T. Gallouët, O. Kavian, Equations de champs scalaires euclidens non linéaires dans le plan, C.R. Acad. Sc. Paris Série I - Math. 297 (1983), and Publications du Laboratoire d Analyse umérique, Université de Paris VI, [3] H. Brézis, E. H. Lieb, Minimum Action Solutions of Some Vector Field Equations, Comm. Math. Phys. 96 (1984),

12 [4] J. Byeon, Z.-Q. Wang, Symmetry breaking of extremal functions for the Caffarelli- Kohn-irenberg inequalities, Comm. Contemp. Math. 4 (2002), [5] F. Brock, Positivity and radial symmetry of solutions to some variational problems in R, J. Math. Anal. Appl. 296 (2004), [6] J. E. Brothers, W.P. Ziemer, Minimal rearrangements of Sobolev functions, J. reine angew. Math. 384 (1988), [7] J. Busca, B. Sirakov, Symmetry results for semilinear elliptic systems in the whole space, J. Diff. Eq. 163, o. 1 (2000), [8] L. Damascelli, F. Pacella, M. Ramaswamy, Symmetry of ground states of p-laplace equations via the moving plane method, Arch. Rational Mech. Anal. 148 (1999), [9] A. Ferrero, F. Gazzola, On subcriticality assumptions for the existence of ground states of quasilinear elliptic equations, Adv. Diff. Eq. 8, o. 9 (2003), [10] M. Flucher, S. Müller, Radial symmetry and decay rate of variational ground states in the zero mass case, SIAM. J. Math. Anal. 29, o. 3 (1998), [11] B. Gidas, W.. i, L. irenberg, Symmetry of positive solutions of nonlinear elliptic equations in R n, Adv. Math. Supp. Stud. 7A (1981), [12] P.L. Lions, The concentration-compactness principle in the Calculus of Variations, The locally compact case, Part 2, Ann. Inst. H. Poincaré Anal. on Linéaire 1 (1984), [13] O. Lopes, Radial symmetry of minimizers for some translation and rotation invariant functionals, J. Diff. Eq. 124 (1996), [14] O. Lopes, M. Montenegro, Symmetry of mountain pass solutions for some vector field equations, J. Dyn. Diff. Eq. 18, o. 4 (2006), [15] M. Mariş, On the symmetry of minimizers, Arch. Rational Mech. Anal., in press, DOI /s ; arxiv: ( [16] J. Serrin, H. Zou, Symmetry of ground states of quasilinear elliptic equations, Arch. Rational Mech. Anal. 148 (1999),

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