Bound-state solutions and well-posedness of the dispersion-managed nonlinear Schrödinger and related equations

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Bound-state solutions and well-posedness of the dispersion-managed nonlinear Schrödinger and related equations J. Albert and E. Kahlil University of Oklahoma, Langston University 10th IMACS Conference, Athens, GA, March 2017 1 / 17

The one-dimensional nonlinear Schrödinger (NLS) equation iu t + u xx + u 2 u = 0 models the propagation of the envelopes of oscillatory pulses in a homogenous medium. In many applications, a more suitable model equation is iu t + d(t)u xx + u 2 u = 0. For example, in dispersion-managed optical fibers, one would take d(t) to be a periodic function of the spatial variable t. 2 / 17

For the NLS equation with periodic coefficient d(t), Antonelli, Saut, & Sparber (2012) proved global well-posedness of the initial-value problem in L 2 (R), assuming d(t) is piecewise constant. The NLS equation is known to have bound-state solutions of the form u(x, t) = e iωt φ(x) where ω R is arbitrary and φ(x) is a localized (hyperbolic secant) function. Numerical studies suggest that the periodic-coefficient equation has solutions which are similar in that they are localized in x and periodic in t. (See, e.g., Bronski & Kutz 1997; or Grigoryan et al. 1997.) Figure: Numerical simulation of solitons in dispersion managed fibers; due to A. Berntson at Chalmers U., Sweden. 3 / 17

DMNLS equation For the equation iu t + d(t)u xx + u 2 u = 0, if d(t) = 1 ɛ δ( t ɛ ) + α, where δ(t) is periodic and has mean value zero, then in the limit as ɛ 0, the solution with given initial data u(x, 0) is well approximated in rescaled variables by the solution of the dispersion-managed NLS equation (Gabitov & Turitsyn 1996, Zharnitsky et al., 2001): iu t + αu xx + 1 0 T (s) 1 [ T (s)u 2 T (s)u ] ds = 0 with the same initial data. Here T (t) = e i( t 0 δ(t )dt ) 2 x is the solution operator for the initial-value problem for the linear Schrödinger equation iu t + δ(t)u xx = 0. 4 / 17

In fact, the DMNLS equation can be written in Hamiltonian form u t = i E(u), with Hamiltonian E(u) = α 2 u x 2 dx 1 4 1 0 T (s)u 4 dx ds. Thus the energy space is H 1 (R) in case α 0, but is L 2 (R) in case α = 0. Note that the value α = 0 is consistent with the assumptions underlying the derivation of DMNLS as a model equation, and is within the range of values of α one would expect to see in applications. We assume throughout this talk that δ(t) is piecewise C 1 and bounded away from zero. 5 / 17

We can ask: Does DMNLS have bound-state solutions like those of NLS, of the form u(x, t) = e iωt φ(x) for localized φ? If so, what can we say about the stability of these solutions? In particular, is DMNLS well-posed in energy space? (In case α > 0, energy space is H 1, so well-posedness is easy.) 6 / 17

Bound-state solutions u(x, t) = e iωt φ(x) correspond to critical points φ for the variational problem inf { E(f ) : f X, f L 2 (R 2 ) = λ }, where X is energy space (H 1 if α 0, L 2 if α=0.) Minimizers of this problem are called ground states. In case α > 0, Zharnitsky et al. (2001) proved that the set S of minimizers is nonempty, and in fact every minimizing sequence f j has a subsequence which converges in H 1 to S. It follows that S is a stable set for the initial-value problem for DMNLS in H 1. In case α < 0, Zharnitsky et al. showed bound states (if they exist) cannot be minimizers, and did numerical experiments suggesting that either bound states do not exist or are not stable. 7 / 17

CR equation Faou, Germain, & Hani (2016) considered solutions of the cubic nonlinear Schrodinger equation in R 2, iu t + u + u 2 u = 0, which have small amplitude ɛ and are periodic with large period L in both spatial variables. They showed that as ɛ 0 and L with ɛl 2 1, solutions are well approximated by those of the continuous resonant (CR) equation, iu t + U 2 (s) 1 [ U 2 (s)u 2 U 2 (s)u ] ds = 0, in which U 2 (t) = e it is the solution operator for the linear Schrödinger equation iu t + u = 0 on R 2. 8 / 17

This equation is of Hamiltonian form u t = i E 2 (u), with Hamiltonian E 2 (u) = 1 U 2 (s)u 4 dx ds. 4 R 2 Bound-state solutions u(x, t) = e iωt φ(x) correspond to critical points φ for the variational problem inf { E 2 (f ) : f L 2 (R 2 ) = λ }. Minimizers are the functions φ which attain the best constant S 2 in the Strichartz inequality ( ) 1/4 ( ) 1/2 U 2 (s)f 4 dx ds S 2 f 2 dx. R 2 R 2 Thus ground states of CR correspond to maximizers for the Strichartz inequality. 9 / 17

In fact, it is known that φ is a maximizer for the Strichartz inequality if and only if φ(x) = αe β x a 2 +b x, where α 0, β > 0, a R 2, and b R 2 are arbitrary. Hence S 2 = (1/2) 1/2 (Foschi, 2007). Hundertmark and Zharnitsky (2006) gave a beautiful proof of this fact based on the following geometric interpretation of E 2 (f ): E 2 (f ) = 1 16 f f, P(f f ) L 2 (R 4 ), where (f f )(x 1, x 2, x 3, x 4 ) := f (x 1, x 2 )f (x 3, x 4 ), and P is the orthogonal projection of L 2 (R 4 ) onto the subspace of functions which are invariant under all rotations of R 4 which fix both the points (1, 0, 1, 0) and (0, 1, 0, 1). A curious fact is that E 2 (f ) = E 2 (ˆf ) for all f L 2 (R 2 ). In fact, u is a solution of the CR equation if and only if û is a solution. 10 / 17

1DCR equation A one-dimensional analogue of the CR equation is iu t + U 1 (s) 1 [ U 1 (s)u 4 U 1 (s)u ] ds = 0, where U 1 (t) = e it 2 x Schrödinger equation is the solution operator for the linear iu t + u xx = 0 on R. The 1DCR equation would be expected to model the behavior of small-amplitude solutions with large period L for the one-dimensional quintic NLS equation iu t + u xx + u 5 u x = 0. 11 / 17

Here the Hamiltonian is E 1 (u) = 1 6 U 2 (s)u 6 dx ds. Bound-state solutions correspond to critical points φ for inf { E 1 (f ) : f L 2 (R 2 ) = λ }, and ground states are maximizers for the Strichartz inequality ( ) 1/6 ( ) 1/2 U 1 (s)f 6 dx ds S 1 f 2 dx. R 2 Foschi showed that φ is a maximizer iff it is a Gaussian, and S 1 = (1/12) 1/12. Hundertmark and Zharnitsky also gave a geometric interpretation of E 1. 12 / 17

Global well-posedness for DMNLS and 1DCR Theorem Suppose r 0. For every u 0 H r and every M > 0, the DMNLS equation (for any α R) and the 1DCR equation have unique strong solutions u C([0, M]; H r ) with initial data u 0. We have u L q t ([0, M], L p x(r)) for every p and q satisfying 2 p, 4 q, and 2/q = (1/2) (1/p). The map taking u 0 to u is a locally Lipschitz map from H r to C([0, M]; H r ). Remark: the same result holds for iu t + u xx + u 2 u = 0, and is known to be sharp in the sense that it does not hold when r < 0. 13 / 17

Theorem (Kunze, 2004) Suppose α = 0. Then for each λ > 0, the variational problem I λ := inf {E(f ) : f L 2 = λ} (1) has a non-empty set of minimizers S. Moreover, every minimizing sequence f j has a subsequence which converges in L 2 to S. It follows that S is a stable set for the initial-value problem in L 2. Remark: this is not yet an orbital stability result, since we do not yet know the structure of S. 14 / 17

Kunze s idea (see also Kunze, Moeser, & Zharnitsky [2005]) is to apply the concentration compactness lemma both to f j and to the Fourier transforms ˆf j, ruling out vanishing and splitting by using the subadditivity and negativity of I λ as a function of λ. We conclude that both f j and ˆf j, when suitably translated, are tight. Now, since ˆf j is tight, we can decompose f j into a low-frequency part fj L which is bounded in H 1, uniformly in j, and a high-frequency part which is small in L 2, uniformly in j. But since f j is tight, then so is fj L. Using the compactness of the embedding of H 1 into L 2 on bounded domains, we can then conclude that f L j has a subsequence which converges strongly in L 2. Hence so also does f j. 15 / 17

The global well-posedness result for 1DCR is sharp in the sense that it does not hold for r < 0. Theorem Suppose r < 0 and M > 0. There exists B > 0 and C > 0 such that for every δ > 0, there exist two solutions u(x, t) and v(x, t) of 1DCR in C([0, M], H r ), with initial data u 0 and v 0, for which u 0 H r B, v 0 H r B, u 0 v 0 H r < δ, (2) and u(x, M) v(x, M) H r C. (3) This shows that that there cannot exist a locally uniformly continuous map from initial data to solutions in H r when r < 0. 16 / 17

This is proved by taking u 0 (x) = βω 1 e inx φ(ω 1 x), v 0 (x) = βω 2 e inx φ(ω 2 x), where φ(x) is a (Gaussian) bound-state solution, and β = N r (1/4), ω 1 = N, ω 2 = N(1 + δ), and N > 0 is a suitable large number. Remark: The proof depends on knowing explicitly how the solution behaves when the initial data is dilated: u(x, t) = βω 1 e iβ4 ω 2 1 t e inx φ(ω 1 x) v(x, t) = βω 2 e iβ4 ω 2 2 t e inx φ(ω 2 x). Such formulas are, however, not available for the DMNLS equation. 17 / 17