Stability for the Yamabe equation on non-compact manifolds

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1 Stability for the Yamabe equation on non-compact manifolds Jimmy Petean CIMAT Guanajuato, México Tokyo University of Science November, 2015

2 Yamabe equation: Introduction M closed smooth manifold g =, x Riemannian metric on M. Look for metrics of constant scalar curvature in the conformal class [g] = {f.g : f : M R >0 }. It amounts to solving the Yamabe equation: a n g u + s g u = λ u p 1 a n = 4(n 1) n 2, s g the scalar curvature, p = p n = 2n n 2, λ R is the scalar curvature of u p 2 g.

3 Sign of λ is determined by [g]. Yamabe equation is the Euler-Lagrange equation for the Hilbert-Einstein functional restricted to [g]: M S(h) = s h dvol h Vol(M, h) n 2 n Let the Yamabe constant of (M, [g]) be Y (M, [g]) = inf S(h) = inf h [g] f M a n f 2 + s g f 2 dvol g ( M f p dvol g ) 2/p

4 1 Infimum in the definition of Y (M, [g]) is always achived H. Yamabe-N. Trudinger-T. Aubin-R. Schoen. There is always at least one (volume 1) solution of the Yamabe equation. 2 Solution is unique if Y (M, [g]) 0. 3 Solution is unique if g is Einstein (M. Obata). 4 In general multiple solutions when Y(M,[g]) >0

5 (M,g) non-compact Riemannian manifold Consider the case s g positive, constant. Define its Yamabe constant by: Y (M, [g]) = inf Y g (f ) = inf f f = inf f M a n f 2 + s g f 2 dvol g ( M f p dvol g ) 2/p Q(f ) f 2. p f 0, f L 2 1 (M, g), assume that the embedding L2 1 Lp holds (positive injectivity radius and bounded Ricci curvature).

6 Questions 1 Compute (O. Kobayashi, R. Schoen) Y (M) = sup {[g]} Y (M, [g]) Y (S n, [g n 0 ]) (T. Aubin). 2 Find all solutions of the Yamabe equation on [g]. Can we solved the Yamabe equation on (S n S m, g n 0 + Tgm 0 ) (T > 0, n, m 2 ), compute the Yamabe constants? Solution is not unique for T big (or small).

7 Noncompact manifolds appear: lim Y T (Sn S m, [g0 n + Tgm 0 ])) = Y (Sn R m, g0 n + g E) (K. Akutagawa-L. Florit-J. Petean) It is fundamental for understanding the behavior of Y (M) under codim k 3-surgery Y (M) inf{y (M), c(n, k)} (B. Ammann-M. Dahl-E. Humbert), generalizing the case of 0-surgery (Kobayashi) Y (M) Y (M).

8 Stability, Compact case (M, g) with constant positive scalar curvature, u smooth function on M h u (t) = Y g (1 + tu) Since s g is constant h u(0) = 0. If g were a Yamabe metric then h u(0) 0. In general if the inequality holds for all u we say that g is a stable solution of the Yamabe equation. Standard computation: ( h u(0) = 2 V 2/p Q(u) s g (p 1) u 2 + (p 2)s ( ) ) 2 g u M V M

9 Then g is stable if for all u such that u = 0 one has a n u 2 2 (p 2)s g u which means λ 1 (g) s g n 1. In particular this holds for any Yamabe metric. For some canonical metric g we might want to study stability for other solutions of the Yamabe equation, and write everything in terms of g. Consider for instance (S 3 S 1, g0 3 + Tdt2 ) (all solutions known (O. Kobayashi, R. Schoen), minimizer is the only stable one) (S 2 S 2, g0 2 + Tg2 0 ) (there are solutions computed numerically, candidate for minimizer).

10 Let (X, h) has constant positive scalar curvature, f L 2 1 (X) be a smooth positive solution of the Yamabe equation. Then f is stable if for all u L 2 1 (X) such that f p 1 u dv h = 0 we have Let Q h (u) X f p 2 u 2 (p 1) Q h(f ) dv h f p p α(x, h, f ) = inf u N(h,f ) Q h (u) X f p 2 u 2 dv h.

11 Consider (M m, g) closed with positive constant scalar curvature and (X, h) = (M R n, g + g n E ). f a critical point of Y h which is a smooth radial decreasing positive function on R n. Theorem Exists u N(g + ge n, f ) which achieves the infimum in the definition of α(m R n, g + ge n, f ). Every minimizer is a smooth function which solves the equation a n u + (s g αf p 2 )u = 0 (1) The space of solutions of this equation is finite dimensional.

12 Stability, Y R n-minimizer (M, g) closed, constant positive scalar curvature. g n E the Euclidean metric on R n. Assume that m, n 2. For a Riemannian product (Z, G) = (M 1 M 2, g + h) consider the restricion of Y G to functions on one of the variables and let Y Mi (Z, G) = inf Y G (u). u L 2 1 (M i ) Y R n(m R n, g + ge n ) can be computed in terms of the best constant in the Gagliardo-Nirenberg inequality (K. Akutagawa, L. Florit, J. Petean):

13 Gagliardo-Nirenberg inequality u 2 p m+n σ u 2n m+n 2 u 2m m+n 2. invariant by replacing u by cu λ (x) = cu(λx). The best constant is σ m,n = u C 0 inf (Rn ) {0} 2 u 2m m+n 2 u 2 p m+n u 2n m+n 1.

14 The infimum is actually achieved. The minimizer is a solution of the Euler-Lagrange equation of the functional in parenthesis: n u + m u 2 2 u 2 2 u (m + n) u 2 2 u p u p 1 = 0. (2) p By invariance if a function u is a minimizer so is cu λ given by cu λ (x) = cu(λx) for any constants c, λ R >0. By picking c, λ appriopriately we can choose the (constant) coefficients appearing in the equation. In particular one would have a solution of u + u u p 1 = 0 (3)

15 It is known since classical work of Gidas-Ni-Nirenberg that all solutions of (3), which are positive and vanish at infinity, are radial functions. It is also known the existence of a radial solution. Moreover, M. K. Kwong proved that such a solution is unique. In our situation we will prefer to first choose λ so that a m+n m u 2 2 = ns g u 2 2 and then pick c so that (m + n)a m+n u 2 2 = s gn u p p. Then the resulting function f K satisfies a m+n f K + s g f K = s g f p 1 K (4)

16 The metric g K = f p 2 K (g + ge n ) has scalar curvature s g K = s g A minimizer for Y R n(m R n, g + ge n ) must be a solution of (4). And by the previous comments the solution is unique, so actually the solution f m,n,sg K is the unique minimizer for Y R n(m R n, g + ge n ). We have Y R n(m R n, g + g n E ) = s gvol(g K ) 2 m+n. which can be expressed in terms of σ m,n and the volume of g.

17 Let g be a Riemannian metric on the closed m-manifold M of constant scalar curvature s g = m(m 1). To simplify we will use the notation G = g + g n E, N = m + n Let f : Rn R >0 be the unique solution of equation (4) discussed in the previous section. Note that Q G (f ) = m(m 1) f p p V. Lemma If α = α(m R n, G, f ) < (p 1)m(m 1) then it is realized by a function u(y, x) = a(y)b(x) where a : M R, g a = λ 1 a, λ 1 is the first positive eigenvalue, and b L 2 1 (Rn ) satisties the equation: ( a N b + a N λ 1 + m(m 1) αf p 2) b = 0 (5)

18 By previous Theorem there exists a minimizer and it is a solution of the equation ( a N u + m(m 1) αf p 2) u = 0 (and the space of solutions is finite dimensional). f depends only on R n : if u is a solution then g u is also a solution. It follows that there is a finite number of linearly independent g - eigenfunctions a 1 (y),..., a k (y), g a i = λ i a i (λ i 0), such that u = Σa i (y)b i (x) for some b i : R n R. Then Σ k i=1 a N(λ i a i (y)b i (x) +a i (y) b i (x)) + (m(m 1) αf p 2 ) a i (y)b i (x) = 0.

19 But then since the a i are linearly independent it follows that for each i ( a N (λ i b i (x) + b i (x)) + m(m 1) αf p 2) b i (x) = 0. So a i b i is also a solution for each i: there is a minimizer of the form a(y)b(x) with g a = λa for some λ 0. If λ = 0 we take a = 1 and then we must have R n bf p 1 dx = 0. Since f is a Y R n-minimizer it is R n -stable we would have α(m R n, G, f ) (p 1) E G(f ) f p p = (p 1)m(m 1) If λ > 0 note that Q G (ab) R f p 2 a 2 b 2 = R a n N b s gb 2 R b 2 R f p 2 b 2 + a N λ R n f p 2 b 2. n n n

20 Therefore f is unstable if and only if exists b L 2 1 (Rn ) {0} R a n N b m(m 1)b2 R b 2 R f p 2 b 2 +a N λ n 1 R f p 2 b 2 < (p 1)m(m 1) n n Lemma For each λ 0 A(λ) = inf b L 2 1 (Rn ) {0} R a n N b s gb 2 R b R f p 2 b 2 + λ 2 n n R f p 2 b 2 n is realized by a radial decreasing function.

21 Then A(λ) is strictly increasing function of λ. A(0) m(m 1) (take b = f ) and A( ) =. Then exists a unique λ = λ m,n such that A(λ m,n ) = (p 1)m(m 1). It follows that f is unstable if and only if λ 1 < λ m,n. Recall that if g is a Yamabe metric on M m with scalar curvature m(m 1) then λ 1 (g) m. Theorem If λ m,n m then f p 2 (g + ge n ) is stable for any Yamabe metric g

22 λ m,n can be computed numerically. The minimizer b for A(λ m,n ) is a solution of a N b + (m(m 1) + a N λ m,n )b = (p 1)m(m 1)f p 2 b. In general consider the equation b + Kb = Cf p 2 b, (6) where C = (p 1)m(m 1)/a N and K is a (variable) positive constant. A radial solution is given by a solution of the ordinary linear differential equation: u (t) + n 1 u (t) + (Cf p 2 K )u(t) = 0 (7) t with u(0) = 1, u (0) = 0.

23 Denote the solution u by u K. We have 3 possibilities: a) u K is always decreasing and positive. b) u K (t) = 0 for some t > 0. c) u K has a local minimum at some t t 0. By Sturm comparison, K 1 < K 2, if the solution u K1 verifies (c) then the solution u K2 also verifies (c). If u K2 verifies (b) then u K1 also verifies (b). Moreover if u K2 verifies (a) then u K1 verifies (b).

24 It follows that for λ = λ m,n the equation u (t) + n 1 ( ( )) m(m 1) u (t) + Cf p 2 + λ u(t) = 0 (8) t a N is positive and decreasing. For λ > λ m,n the solution has a local minimum and for λ < λ m,n has a 0 at finite time. The function f can be computed numerically and then for a fixed λ one can compute numerically the solution of (8) and check whether λ < λ m,n or λ > λ m,n.

25 For example: λ 2, λ 3, λ 4, λ 5,

26 Thank you!!

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