Asymptotic behavior near transition fronts for equations of generalized Cahn Hilliard form

Size: px
Start display at page:

Download "Asymptotic behavior near transition fronts for equations of generalized Cahn Hilliard form"

Transcription

1 Asymptotic behavior near transition fronts for equations of generalized Cahn Hilliard form Peter HOWARD February 13, 7 Abstract We consider the asymptotic behavior of perturbations of standing wave solutions arising in evolutionary PDE of generalized Cahn Hilliard form in one space dimension. Such equations are well known to arise in the study of spinodal decomposition, a phenomenon in which the rapid cooling of a homogeneously mixed binary alloy causes separation to occur, resolving the mixture into its two components with their concentrations separated by sharp transition layers. Motivated by work of Bricmont, Kupiainen, and Taskinen [5], we regard the study of standing waves as an interesting step toward understanding the dynamics of these transitions. A critical feature of the Cahn Hilliard equation is that the linear operator that arises upon linearization of the equation about a standing wave solution has essential spectrum extending onto the imaginary axis, a feature that is known to complicate the step from spectral to nonlinear stability. Under the assumption of spectral stability, described in terms of an appropriate Evans function, we develop detailed asymptotics for perturbations from standing wave solutions, establishing phase-asymptotic orbital stability for initial perturbations decaying with appropriate algebraic rate. 1 Introduction We consider the asymptotic behavior of perturbations of standing-wave solutions ū(x, ū(± = u ± arising as equilibrium solutions in equations of generalized Cahn Hilliard form for which we assume (H b, c C (R. (H1 b(u ± >, c(ū(x c >, x R. u t = (b(uu x x (c(uu xxx x, x, u, b, c R, t >, (1.1 Our analysis is motivated by the distinguished role the Cahn Hilliard model plays in the study of spinodal decomposition, a phenomenon in which the rapid cooling of a homogeneously mixed binary alloy causes separation to occur, resolving the mixture into its two components with their concentrations separated by sharp transition layers [9, 11]. In this context, and for the case of incompressible fluids, the Cahn Hilliard equation is u t = {M(u (F (u κ u} u ν = u ν = ; x Ω, (1. where Ω denotes a bounded open subset of R n (n typically or 3, ν denotes the unit normal vector to Ω, u denotes the concentration of one component of the binary alloy (or possibly a difference between this concentration and the concentration at homogenous mixing, F(u denotes the bulk free energy of the alloy, and the typically small parameter κ is a measure of the strength of interfacial energy. (In the case that κ depends on u, a new term appears in (1. of the form 1 κ (u u ; see [9]. We take this natural form of the equation from [1].. 1

2 An intesting feature of equations of form (1.1 is that the second and fourth order regularizations can balance, and a wide variety of stationary solutions can arise, including standing waves. For example, in the case of (1.1 with b(u = 3 u 1 ; c(u 1 (1.3 (the case studied in [5], corresponding with F(u = (1/8u 4 (1/4u, M(u 1, and κ = 1 in (1., one readily verifies that the standing wave ū(x = tanh( x (1.4 is such a solution, often referred to as the kink solution. Motivated by the elegant result of Bricmont, Kupiainen, and Taskinen [5] (which we state below for comparison with the current analysis, we regard the study of standing waves as an interesting first step toward understanding the dynamics of these transitions. (See also [36] and [38] for related results in the case of multiple space dimensions. We stress that our focus is on standing waves only, and remark that linearization of (1.1 about a traveling wave leads to a linearized problem with non-vanishing convection and consequently an entirely different flavor than the problem that arises upon linearization about a standing wave. Indeed, upon shifting to a coordinate system moving along with the shock, a flux function is introduced f(u = su, and the wave can be regarded as a regularized undercompressive shock profile. Such problems have been considered in [16], and are quite similar to the problems considered in [5, 6]. A critical feature of equations of form (1.1 is that the linear operator that arises upon linearization of the equation about a standing wave solution has essential spectrum extending onto the imaginary axis, a feature that is known to complicate the step from spectral to nonlinear stability. The purpose of this paper is to study precisely this step from spectral to nonlinear stability. In particular, under the assumption of spectral stability (described below in terms of an appropriate Evans function and verified in the particular case (1.1 (1.3 with wave (1.4, we develop detailed asymptotics for perturbations from standing wave solutions, establishing phase-asymptotic orbital stability for initial perturbations decaying with algebraic rate (1 + x 3/. Our approach to this problem will be to extend to this setting methods developed previously in the context of conservation laws with diffusive and/or dispersive regularity, u t + f(u x = (b(uu x x + (c(uu xx x +..., (1.5 which also have no spectral gap. More precisely, we proceed by computing pointwise estimates on the Green s function for the linear equation that arises upon linearization of (1.1 about the wave ū(x (employing a contour-shifting approach introduced in [, 5]; see also [3, 45]. Such estimates are dependent upon the spectrum of the linear operator, which we understand here in terms of an appropriate Evans function (see, for example, [14, 1, 35, 5] and the discussion and references below. Finally, we employ the local tracking method developed in [34], an approach through which Green s function estimates on the linearized operator can be used to approximately locate shifts from the standing wave ū. Our general approach is similar to the analysis of [5], in which case the authors also employ Green s function estimates on the linear operator in order to close an iteration on the perturbation in some appropriately weighted space. A fundamental difference between the two analyses is that in [5], this iteration is carried out by the renormalization group method, a theory that has its origins in particle physics (see [8] and was introduced in the context of time-asymptotic behavior for nonlinear PDE in [17, 18, ], and further developed in [3, 4] (it pre-dates the current approach by about eight years. Briefly, the renormalization group method is an approach toward understanding asymptotic behavior of PDE that makes use of certain natural scalings in the PDE. This method is ideally suited for cases such as (1.1, for which the equation that arises upon linearization about the wave ū(x has the same natural scaling as one would use for the heat equation. Indeed, though the analysis of [5] is carried out in the context of a self-adjoint linearized equation (the integrated equation, the method could in principle be extended to the current setting for which the linearized operator is not generally self-adjoint even after integration. Nonetheless, the Green s function estimates required for any such extension would almost certainly be obtained by methods very similar to those employed here, which have been developed particularly for the case of non-self-adjoint problems. In this way, the current approach seems to represent a change of thinking from the point of view of classical mathematical physics to that of modern Evans function techniques. We emphasize, however, that the spectral analysis of both [5] and

3 the current analysis rely on the self-adjoint nature of the equation, and in the non-self-adjoint case spectral stability is left as a separate analysis (see the discussion following Remark 1.1. A more fundamental difficulty with the use of such a scaling technique as the renormalization group method in the context of the Cahn Hilliard equation arises in the extension to multiple space dimensions, in which case it is known that the leading eigenvalue of the linearized operator about a planar wave ū(x 1 (leading in the case of stability scales as λ ξ 3 (see [5], and consequently introduces a new cubic scale into the problem, which competes with the natural heat-equation scaling of (1.1. (Here, ξ R d1 denotes a Fourier variable associated with spatial components transverse to the planar wave. A different approach is taken in this setting in [36, 38], quite similar to the method employed here, and the authors conclude stability in space dimensions d 3 for the planar wave ū(x 1 = tanh x 1, arising in (1. with F(u = (1/8u 4 (1/4u, M(u 1 and κ = 1. The primary difference between the approach of [36, 38] and the current analysis is the local tracking function δ(t employed here, which can be generalized to the case of multiple space dimensions as a function of t and the transverse variable x = (x, x 3,..., x d (see [5, 6, 7, 8]. It is precisely this local tracking, which does not seem to fit in any straightforward fashion into the renormalization group framework, that allows us here to obtain stability for more slowly decaying data than considered in [5], and that allows for the extension of this method to the case of space dimensions d (an analysis we carry out in a separate paper. Finally, we note that in adddition to the standing waves considered in the current analysis and the planar waves discussed above, the Cahn Hillard equation admits a wide range of periodic solutions, and the methods here can be extended to that setting in a manner similar to the analyses of Oh and Zumbrun in the case of periodic solutions arising in the context of viscous conservation laws [46, 47]. Before setting up the analysis, we mention that equations of form (1.1 have been shown to arise in the area of mathematical biology in the context of cell formation and aggregation [44], and also that equations similar to (1.1 arise naturally in the modeling of thin film flows, for which under certain circumstances, the height h(t, x of a film moving along an inclined plane can be modeled by fourth order equations h t + (h h 3 x = β(u 3 u x x γ(u 3 u xxx x (see [6] and the references therein. As in the case of conservation laws, it is readily seen that solutions u(t, x initially near ū(x, will not generally approach ū(x, but rather will approach a translate of ū(x determined uniquely by the amount of perturbation mass (measured as R (u(, x ū(xdx carried into the shock layer. We proceed, then, by defining the perturbation v(t, x = u(t, x + δ(t ū(x, (1.6 for which δ(t will be chosen by the analysis to track the location of the perturbed solution in time. In this way, we compare the shapes of u and ū rather than their locations. (The type of stability we will conclude is orbital. Substituting v into (1.1, we obtain the perturbation equation with v t + (a(xv x = (b(xv x x (c(xv xxx x + δ(t(ū x (x + v x + Q(x, v, v x, v xxx x, (1.7 a(x = b (ūū x + c (ūū xxx ; b(x = b(ū(x; c(x := c(ū(x Q(x, v, v x, v xxx = O( vv x + O( vv xxx + O(e η x v, where η > and Q is a continuously differentiable function of its arguments. According to hypotheses (H (H1, we have that a C 1 (R, b, c C (R and for k =, 1 k xa(x = O(e α x ; k x(b(x b ± = O(e α x ; k x(c(x c ± = O(e α x, (1.9 where α > and ± represent the asymptotic limits as x ±. Regarding the convection coefficient a(x, we note that it decays to at both ± (see Section for more details. In comparison with conservation laws u t + f(u x = (b(uu x x, (1.8 3

4 this corresponds with the degenerate case, for which one of the asymptotic convection coefficients a ± = f (u ± for a traveling wave ū(x st is equal to the wave speed s, and both values can be taken without loss of generality as (see [3, 4]. In the case (1.1 (1.3 the wave (1.4 satisfies a(x = 3ū(xū x (x, from which we see that for x <, we have a(x >, while for x >, we have a(x <. In this way, the wave (1.4 is similar to Lax waves in the sense that characteristic speeds (values of the convection coefficient a(x impinge on the transition layer from both sides. The critical difference, again, is that in the case of equations of form (1.1 these characteristic speeds approach asymptotically. Finally, we mention that whereas this decay of a(x is algebraic in the case of degenerate viscous shock waves, it is exponential in the current setting, a difference critical in the Evans function analysis of Section. Another important feature of equations of form (1.1 is that the diffusion coefficient b(ū(x may not always be positive. In the case (1.1 (1.3 with wave (1.4, we have b(ū = 3 ū 1, (1.1 which is asymptotically positive at both ±, but negative near the transition layer at x =. Our assumptions (H (H1 clearly do not give us control over the possible destabilizing effect of this feature of the equations. The effect is, however, encoded in the spectrum of the linear operator Lv = (c(xv xxx x + (b(xv x x (a(xv x, (1.11 which we discuss further below. For now, we suffice to remark that the essential spectrum of L consists of the negative real axis, up to the imaginary axis, and so as in the case of regularized conservation laws, the step from spectral stability to nonlinear stability is problematic. Integrating (1.7, we have (after integration by parts and upon observing that e Lt ū x = ū x the integral equation v(t, x = t G(t, x; yv (ydy + δ(tū x (x [ G y (t s, x; y Q(y, v, v y, v yyy + δ(sv ] dyds, where G(t, x; y denotes a Green s function for the linear part of (1.7: (1.1 G t = LG; G(, x; y = δ y (x. (1.13 We divide G(t, x; y into terms for which the x dependence is exactly ū x (x (the excited terms and the remainder, G(t, x; y. In general, the excited terms do not decay for large time and correspond with mass accumulating at the origin, shifting the asymptotic location of the waves. Writing we have v(t, x = t ū x (x G(t, x; y = G(t, x; y + ū x (xe(t, y, G(t, x; yv (ydy + ū x (x t [ G y (t s, x; y Q(y, v, v y, v yyy + δ(sv Choosing δ(t to eliminate precisely the excited term, we have δ(t = e(t, yv (ydy + e(t, yv (ydy + δ(tū x (x ] dyds [ e y (t s, y Q(y, v, v y, v yyy + δ(sv ] dyds. t [ e y (t s, y Q(y, v, v y, v yyy + δ(sv ] dyds, (1.14 4

5 after which, we have v(t, x = t G(t, x; yv (ydy [ G y (t s, x; y Q(y, v, v y, v yyy + δ(sv ] dyds. (1.15 Integral equations for v x and δ can immediately be obtained by differentiation of both sides of (1.14 and (1.15. Our approach will be to determine estimates on G(t, x; y and e(t, y sufficient for closing simultaneous iterations on v(t, x, v x (t, x, δ(t, and δ(t. To this end, we analyze the Green s function G(t, x; y through its Laplace transform G λ (x, y, which satisfies the ODE (t transformed to λ LG λ λg λ = δ y (x, (1.16 and can be estimated by standard methods. Letting φ + 1 (x; λ and φ+ (x; λ denote the (necessarily two linearly independent asymptotically decaying solutions at + of the eigenvalue ODE Lφ = λφ, (1.17 and φ 1 (x, λ and φ (x, λ similarly the two linearly independent asymptotically decaying solutions at, we write G λ (x, y as a linear combination { φ 1 G λ (x, y = (x; λn+ 1 (y; λ + φ (x; λn+ (y; λ, x < y φ + 1 (x; λn 1 (y; λ + φ+ (x; λn (y; λ, x > y. (1.18 Insisting, as usual, on the continuity of G λ (x, y and its first two x-derivatives in x, and on the jump in 3 x G λ(x, y at x = y, we have N 1 + (y; λ = W(φ+ 1, φ+, φ ; N + c(yw λ (y (y; λ = W(φ+ 1, φ+, φ 1 c(yw λ (y N 1 (y; λ = W(φ 1, φ, φ+ c(yw λ (y N (y; λ = W(φ 1, φ, φ+ 1, c(yw λ (y (1.19 where W(φ 1, φ,..., φ n denotes a square determinant of column vectors created by augmentation with an appropriate number of x-derivatives and W λ (y := W(φ 1, φ, φ+ 1, φ+. We see immediately from (1.18 and (1.19 that, away from essential spectrum, G λ (x, y is bounded so long as W λ (y is bounded away from. Since W λ (y is a Wronskian for (1.17, for each fixed λ its sign does not change as y varies. In light of this, we define the Evans function as D(λ = W λ (. (1. Introduced by Evans in the context of nerve impulse equations [14] (see also the early analysis of Jones for pulse solutions to the FitzHugh Nagumo equation [35], the Evans function serves as a characteristic function for the operator L. More precisely, away from essential spectrum, zeros of the Evans function correspond in location and multiplicity with eigenvalues of the operator L, an observation that has been made precise in [1] in the case pertaining to reaction diffusion equations of isolated eigenvalues, and in [1, 5] and [4] in the cases pertaining respectively to conservation laws and the nonlinear Schrödinger equation of nonstandard effective eigenvalues embedded in essential spectrum. (The latter correspond with resonant poles of L, as also examined in [48]. Briefly, we remark on the connection between our form of the Evans function (1. and the definition of Evans et al. [1, 14, 35]. Letting Φ ± k := (φ± k, φ± k, φ ± k, φ ± k tr, define Y ± (x; λ = Φ ± 1 (x; λ Φ± (x; λ, (1.1 where represents a wedge product on the space of vectors in R 4 (i.e., denotes an associative, bilinear operation on vectors v R 4, characterized by the relation between standard R 4 basis vectors e j and e k, e j e k = e k e j. In this case, we obtain through straightforward calculation that D(λ = e R x tra(y;λdy Y (x; λ Y + (x; λ, (1. 5

6 which is the form of [1, 14, 35]. (As described below, the matrix A is simply the matrix that arises when (1.17 is written as a first order system. One notable advantage of the formulation (1. is that the -forms Y ± (x; λ are the asymptotically decaying solutions of the equations where A is defined by Y ± = A ±(x; λy ±, Y ± = (Φ± 1 Φ± = Φ ± 1 Φ ± + Φ ± 1 Φ± = (AΦ ± 1 Φ± + Φ± 1 AΦ± = A ±Φ ± 1 Φ± = A ±Y ±. In this way, the wedge formulation can remain analytically valid in cases for which the wedge products Y ± cannot be uniquely resolved into components. In the current setting, the Φ ± k remain sufficiently distinct (away from essential spectrum that the two formulations are equivalent. We will observe in Section that D(λ is not analytic at λ =, but can be extended analytically on the Riemann surface ρ = λ. (This is quite similar to the analysis of Kapitula and Rubin in the case of the complex Ginzburg Landau equation [39], and the analyses of Guès et al. and of Zumbrun in the case of multidimensional shock stability in the vicinity of glancing points [19, 51], but differs markedly from the case of degenerate conservation laws, for which the Evans function has a dependence of the form λ lnλ [3, 4]. In light of this, we define the function D a (ρ := D(λ. The primary concern of this analysis is to show that under assumptions (H (H1, nonlinear stability of standing wave solutions ū(x of (1.1 is implied by the spectral condition (D: (D: The Evans function D(λ has precisely one zero in {Reλ }, necessarily at, and ρρ D a (. Remark 1.1. Under the assumption of condition (D, the point spectrum of L, aside from the distinguished point at λ =, lies to the left of a parabolic contour, which passes through the negative real axis and opens into the negative real half plane, λ s (k = c k + i c 1 k + c. (1.3 We will denote this contour Γ s. The essential spectrum of L consists of the negative real axis. While condition (D is generally quite difficult to verify analytically (see, for example, [13, 15, 35], it can be analyzed numerically [, 33, 31]. In the case of equations (1.1 (1.3 and the standing wave (1.4, (D is straightforward to verify (see [5] or Lemma.6 of the current analysis, in which we review the analysis of [5] for the sake of completeness. We are now in a position to state the first theorem of the paper. Theorem 1.1. Suppose ū(x is a standing wave solution to (1.1 and suppose (H (H1 hold, as well as stability criterion (D. Then for some fixed C and C E, and for positive contants M and K sufficiently large, and for η >, depending only on the spectrum and coefficients of L, the Green s function G(t, x; y described in (1.13 satisfies the following estimates for y (with symmetric estimates in the case y. (I For either x y Kt or t 1, and for α a multi-index in the variables x and y, α G(t, x; y Ct 1+ α 4 e xy 4/3 Mt 1/3, α 3. (II For x y Kt and t 1 where G(t, x; y = G(t, x; y + E(t, x; y, 6

7 (i y x (ii x y G(t, x; y = G y (t, x; y = G x (t, x; y = O( C [e (xy 4b t 4b t C 4b t y [e (xy 4b t + O(t 3/ e (xy Mt + O( x y (xy e Mt t3/ G xy (t, x; y = O(t 3/ e (xy Mt G(t, x; y = C [e (xy 4b t 4b t ] e (x+y 4b t + O(t 1 e (xy Mt ] e (x+y 4b t x + y (x+y e Mt t3/ + O(t 1/ e η x e y Mt + O(t 3/ e (xy Mt + O( y t 3/ eη x e y Mt. ] e (x+y 4b t + O(t 1 e (xy Mt x y G y (t, x; y = O( G x (t, x; y = t 3/ e (xy Mt C 4b t x [e (xy 4b t + O(t 3/ e (xy Mt ] e (x+y 4b t + O(t 1/ e η x e y x + y Mt + O( t G xy (t, x; y = O(t 3/ e (xy Mt 3/ e (x+y Mt + O(t 3/ e (xy Mt (iii y x and in all cases G(t, x; y = O(t 1/ e (x t 3/ s b+ b y Mt x b+ b y (x G y (t, x; y = O( e x b+ b y (x G x (t, x; y = O( e t 3/ G xy (t, x; y = O(t 3/ e (x s b+ b y Mt s b+ y b Mt s b+ y b Mt E(t, x; y = C E ū x (x C E + O( y t 3/ eη x e y (x Mt + O(t 3/ e + O(t 1/ e η x e y Mt + O(t 3/ e (x + O( y t 3/ eη x e y Mt y 4b t E y (t, x; y = y 4b tūx(xe ( e ζ dζ 1 + O(e η y 4b t ( 1 + O(e η y. s b+ b y Mt s b+ b y The estimates of Theorem 1.1 are quite similar to those of Lemma.1 in [38], in which the authors are considering a multidimensional generalization of (1.1 (1.3. Similar estimates are also obtained in [5] during the course of the analysis, though in that case the authors work with the integrated equation and consequently the term E(t, x; y, which does not decay as t grows, does not appear. In both of these cases, the analysis is restricted to the case of (1., with F(u = (1/8u 4 (1/4u, M(u 1, and κ = 1, and the wave (1.4. The estimates of Theorem 1.1 are sufficient for establishing the following theorem on the perturbations v(t, x. Mt 7

8 Theorem 1.. Suppose ū(x is a standing wave solution to (1.1, and suppose (H (H1 hold, as well as stability criterion (D. Then for Hölder continuous initial perturbations (u(, x ū(x C +γ (R, γ >, with (u(, x ū(xdx = (1.4 u(, x ū(x E (1 + x 3/, for some E sufficiently small, and for δ(t as defined in (1.14, there holds u(t, x + δ(t ū(x CE (1 + x + t 3/ x (u(t, x + δ(t ū(x CE [ t 1/4 (1 + t 1/4 (1 + x + t 3/ + (1 + t 3/4 e η x ] δ(t CE (1 + t 1/4 δ(t CE (1 + t 5/4. (1.5 In the estimates of Theorem 1., we have included v x (t, x in order to take advantage of the particular form of the nonlinearity Q, in which the term O( vv x is better than O(v, which arises in a similar analysis in the case of regularized conservation laws. Remark 1.. We note that in the current setting the assumption of zero mass initial data can be taken without loss of generality. As in the case of Lax waves arising in regularized conservation laws, the asymptotic shift of the wave can be located here entirely from the initial perturbation. In this way, the shift to a zero mass perturbation is simply a change of perspective, in which we consider the stability of the asymptotically selected wave rather than of the original wave. The validity of this a priori selection of the asymptotic translate is justified precisely by our decay estimate on δ(t, from which we verify that perturbations of the zero-mass wave do indeed approach the zero-mass wave. Of course, this means the stability we conclude is orbital. In light of Remark 1., we can state the following theorem regarding initial perturbations with non-zero mass. Corollary 1.1. Suppose ū(x is a standing wave solution to (1.1, and suppose (H (H1 hold, as well as stability criterion (D. Then for Hölder continuous initial perturbations (u(, x ū(x C +γ (R, γ >, with u(, x ū(x E (1 + x 3/, (1.6 for some E sufficiently small, there holds where u(t, x + x ū(x CE [(1 + x + t 3/ + (1 + t 1/4 e η x ], (1.7 1 x = u + u u(, x ū(xdx. We note specifically the relationship between Corollary 1.1 and the result of [5]. In [5], the authors employ the renormalization group method to establish the following result on (1.1 (1.3: For any p >, there exists δ > such that for v Xp δ, { } X p := v C (R : v X := sup(1 + x p+1 v (x < x R, the Cauchy problem (1.1 (1.3 with u(1, x = ū(x + v (x, where ū(x is as in (1.4, has a unique smooth solution u(t, x, t (1, satisfying for some x R depending only on v. u(t, ū( x L (R as t, 8

9 Moreover, for some constants A and B depending only on v, there holds u(t, x + x = ū(x + 1 d (e x 4t (Aū(x + B + o(t 1. 4πt dx The difference between Corollary 1.1 and the result of [5] (for the equation (1.1 (1.3, with wave (1.4 lies predominately in the difference in assumptions on the initial perturbation. In taking more rapidly decaying initial perturbations, we could increase the decay rate of our perturbation in time. More precisely, in the estimate of Theorem 1., for 1 < r < initial perturbations of size (1 + x r give temporal decay on u(t, x + δ(t ū(x at rate (1 + t r/ and δ(t decay at rate (1 + t (1r/. For r >, δ(t decays at the maximal rate (1 + t 1/, and the estimate of Corollary 1.1 becomes u(t, x + x ū(x CE [(1 + t 1/ e η x + (1 + t 1], (1.8 which almost recovers the detail of [5] Theorem 1.1. Finally, we note that the second order term in [5] Theorem 1.1 is the analogue here of the diffusion waves of Liu [41], and could be recovered in the current setting by an analysis similar to that of [9, 3, 49]. Outline of the paper. In Section, we carry out a general analysis of the Evans function for the eigenvalue problem (1.17, providing full details in the case (1.1 (1.3 with wave (1.4. In addition, we use this analysis to develop estimates on the Laplace-transformed Green s function G λ (x, y. In Section 3, we prove Theorem 1.1, while in Section 4 we prove Theorem 1.. Finally, some representative estimates on the integrations arising from our integral equations are provided in Section 5. Analysis of the Evans Function In this section we analyze the Evans function, as defined in (1., for our linear eigenvalue problem (1.17. We begin with a remark on the structure of standing waves ū(x arising in the context of (1.1. Upon substitution of such a wave into (1.1, we have the ODE (c(ūū xxx x (b(ūū x x =. (.1 Observing that ū x (x as x ±, we can integrate (.1 to obtain the third order equation c(ūū xxx b(ūū x =. (. Asymptotically, solutions to (. behave like solutions to the constant coefficient equations c ± ū xxx b ± ū x =, (.3 whose solutions grow and decay with rates ± b ± /c ± and. Since the solutions with rate correspond with constant solutions to (.1, we see that any solution that does not blow up must approach its endstates at exponential rate. We now begin our analysis of the Evans function by writing the eigenvalue problem (1.17 as a first order system W = A(x; λw, (.4 where A(x; λ = λ c(x a (x c(x a(x c(x + b (x c(x b(x c(x Under assumptions (H (H1, A(x; λ has the asymptotic behavior { A (λ + E(x; λ, x < A(x; λ = A + (λ + E(x; λ, x >, c (x c(x. 9

10 where lim A(x; λ = A ±(λ = x ± λ c ± 1 1 1, (.5 b ± c ± and for λ bounded E(x; λ = O(e α x. The eigenvalues of A ± (λ satisfy the relation, b ± ± b µ ± 4λc ± =. c ± Ordering these so that j < k Reµ j (λ Reµ k (λ, we have µ ± 1 (λ = b ± c ± + O( λ ; µ ± (λ = 1 b± λ + O( λ 3/ µ ± 3 (λ = + 1 b± λ + O( λ 3/ ; µ ± 4 (λ = + b ± c ± + O( λ, with associated eigenvectors V ± k = (1, µ ± k, (µ± k, (µ ± k 3 tr. A straightforward way in which to understand these expressions is through the relationship b ± b 4c± λ ± 4λc ± =, b ± + b ± 4λc ± where the right-hand side is now in the form of λ multiplied by a function that for λ sufficiently small is analytic in λ. We note that for λ sufficiently small, and away from essential spectrum (the negative real axis, these eigenvalues remain distinct. Also, we clearly have µ ± 1 = µ± 4 and µ± = µ± 3. Lemma.1. For the eigenvalue problem (1.17, assume a C 1 (R, b, c C (R, with b ± > and c ± >, and additionally that (1.9 holds. Then for some ᾱ > and k =, 1,, 3, we have the following estimates on a choice of linearly independent solutions of (1.17. For λ r, some r > sufficiently small, there holds: (i For x (ii For x k x φ 1 (x; λ = eµ 3 (λx (µ 3 (λk + O(e ᾱ x k x φ (x; λ = eµ 4 (λx (µ 4 (λk + O(e ᾱ x x k ψ 1 (x; λ = eµ 1 (λx (µ 1 (λk + O(e ᾱ x x k 1 ( ψ (x; λ = µ (λ µ (λk e µ (λx µ 3 (λk e µ(λx 3 + O(e ᾱ x. k x φ+ 1 (x; λ = eµ+ 1 (λx (µ + 1 (λk + O(e ᾱ x x k φ+ (x; λ = eµ+ (λx (µ + (λk + O(e ᾱ x x k 1 ( ψ+ 1 (x; λ = µ + 3 (λ µ + 3 (λk e µ+ 3 (λx µ + (λk e µ+ (λx + O(e ᾱ x k xψ + (x; λ = eµ+ 4 (λx (µ + 4 (λk + O(e ᾱ x. Proof. Lemma.1 can be proved by standard methods such as those of [5], pp We remark here only on the choice of our slow growth solutions ψ (x; λ and ψ+ 1 (x; λ. We could alternatively make the choice x k ψ (x; λ = eµ (λx (µ (λk + O(e ᾱ x k x ψ + 1 (x; λ = eµ+ 3 (λx (µ + 3 (λk + O(e ᾱ x. 1

11 The difficulty with this choice is that these growth solutions coalesce with the slow decay solutions φ 1 and φ + as λ. (See [3], in which this latter convention is taken. Following the analysis of [5], we take the linear combination of solutions stated in order to have a set of solutions of (1.17 that remains linearly independent as λ. In order to see that ψ (x; λ and ψ+ 1 (x; λ are valid choices, we note that their derivation depends precisely on this coalescence with the slow decay solutions φ 1 and φ+ as λ. In the case, for example, of ψ (x; λ, we proceed by letting φ (x be any λ = solution of (1.17 that neither grows nor decays as x. (The existence of such a solution follows immmediately from the slow decay solution φ 1. We search for solutions of the form ψ (x; λ = φ (xw(x; λ, for which direct substitution reveals c(xφ w (c(x(3φ w + 3φ w + φ w + b(xφ w + (b(xφ w a(xφ w = λφ w, (.6 and we make the critical observation that the only coefficient of undifferentiated w is λφ. In this way, the first order system associated with (.6 has the form (W k = k w W = A (λw + E(x; λw, where A (λ is precisely as in (.5, while E(x; λ has the particular form E(x; λ =, (.7 λo(e α x O(e α x O(e α x O(e α x for some α >. Searching for solutions W = e µ 3 x Z, we have the equation which can be integrated as Z(x = V 3 (λ + x Z + µ 3 IZ = A (λz + EZ, e (Aµ 3 (xy P E(y; λz(y; λdy M + e (Aµ 3 (xy QE(y; λz(y; λdy, x where similarly as in [5], P is a projection operator projecting onto the eigenspace associated with µ 1, µ, and µ 3, while Q is the projection operator projecting onto the eigenspace associated with µ 4. In this way, the first integral decays at exponential rate due to the exponential decay of E and the second integral decays at exponential rate due to the exponential decay of the combination e (µ 4 µ 3 (xy E(y; λ. Consequently, a standard contraction mapping closes for all x sufficiently large. This in turn justifies a direct iteration, in which V 3 (λ is taken as a first approximation for Z(x. Upon substitution for a second iterate, we observe 1 E(y; λv 3 + (λ = µ 3 (λ µ λo(e α y O(e α y O(e α y O(e α y 3 (λ = O( λ1/ e α y. µ 3 (λ3 Continuing the iteration, we conclude φ 1 (x; λ = eµ 3 (λx φ (x(1 + O( λ1/ e α x. Similarly, a slow growth solution can be constructed from φ (x, as ψ (x; λ = eµ (λx φ (x(1 + O( λ1/ e α x. 11

12 Any linear combination of φ 1 (x; λ and ψ (x; λ is also a solution of (1.17, and so we are justified in defining ψ 1 ( (x; λ := ψ µ (x; λ φ 1 (x; λ. We have, then, 1 ( ψ (x; λ φ 1 (x; λ µ = 1 ( µ e µ (λx φ (x(1 + O( λ1/ e α x e µ 3 (λx φ (x(1 + O( λ1/ e α x. = φ (x µ ( e µ (λx e µ 3 (λx + O( λ 1/ e α x. The estimate we state is obtained by scaling φ (x as φ (x = 1 + O(eα x. The case of ψ 1 + (x; λ can be analyzed similarly. Lemma.. Under the assumptions of Lemma.1, and for φ ± k, ψ± k as in Lemma.1, with k =, 1 and for D(λ as in (1. we have the following estimates. For some α >, (i For x x k W(φ 1, φ, ψ 1 = c(xw λ (x x k W(φ 1, φ, ψ = c(xw λ (x 1 (λx( c(d(λ eµ (µ k (µ 1 µ 4 (µ 1 µ 3 (µ 4 µ 3 + O(e α x 1 (λx( c(d(λ eµ 1 (µ 1 k (µ µ 4 (µ µ 3 x k W(φ 1, ψ 1, ψ 1 = (λx( c(xw λ (x c(d(λ eµ 4 (µ 4 (µ µ 1 (µ µ 3 µ x k W(φ, ψ 1, ψ 1 ( (µ = µ 1 (µ µ 4 (µ 1 µ 4 c(xw λ (x c(d(λ µ + O( λ 1/ e α x. µ (µ 4 µ 3 + O(e α x (µ 1 µ 3 + O(e α x ( e µ 3 (λx (µ 3 k e µ (λx (µ k (ii For x x k W(φ + 1, φ+, ψ+ 1 = c(xw λ (x x k W(φ + 1, φ+, ψ+ = c(xw λ (x x k W(φ + 1, ψ+ 1, ψ+ = c(xw λ (x x k W(φ +, ψ+ 1, ψ+ = c(xw λ (x 1 + (λx( c(d(λ eµ 4 (µ + 4 k ( µ+ 3 µ+ µ + (µ + 3 µ+ 1 (µ+ µ+ 1 + O(e α x (λx( c(d(λ eµ 3 (µ + 3 k (µ + 4 µ+ (µ+ 4 µ+ 1 (µ+ µ+ 1 + O(e α x 1 ( (µ + 4 µ + 3 (µ+ 4 µ+ 1 (µ+ 3 µ+ 1 ( e µ+ (λx (µ + c(d(λ k e µ+ 3 (λx (µ + 3 k + O( λ 1/ e α x µ (λx( c(d(λ eµ 1 (µ + 1 k (µ + 4 µ+ 3 (µ+ 4 µ+ (µ+ 3 µ+ + O(e α x. Proof. The estimates of Lemma. are each carried out in a similar straightforward manner, so we proceed only in the case of W(φ, ψ 1, ψ x. c(xw λ (x µ + 3 1

13 Computing directly, and observing (c(xw λ (x =, we have x W(φ, ψ 1, ψ c(xw λ (x For the denominator, we note Abel s relation, or = xw(φ, ψ 1, ψ. c(xw λ (x W λ(x = W λ (e R x tra(y;λdy = D(λe R x c (y c(y dy = D(λ c( c(x, For the numerator, we compute φ x W(φ ψ1 ψ, ψ 1, ψ = det = 1 µ 1 µ c(xw λ (x = c(d(λ. (.8 φ φ ψ1 ψ1 ψ ψ det µ 4 µ 1 µ e (µ 1 +µ +µ 4 x (µ 4 3 (µ 1 3 (µ det µ 4 µ 1 µ 3 (µ 4 3 (µ 1 3 (µ 3 3 e (µ 1 +µ 3 +µ 4 x + O(e α x. We mention particularly that in the exponentially decaying terms of this last calculation, we have observed the estimate 1 µ (λx e µ 3 (λx O(e ᾱ x 1 C 1 (λ(eµ µ (λ λx O(e ᾱ x for some < α < ᾱ. Computing the determinants, we find x W(φ, ψ 1, ψ = 1 µ = O(e α x, [ (µ 3 (µ µ 1 (µ µ 4 (µ 3 µ 4 e(µ 1 +µ +µ 4 x (µ (µ 3 µ 1 (µ 3 µ 4 (µ 1 µ 4 ]e (µ 1 +µ 3 +µ 4 x + O(e α x, for which we observe that with µ 1 = µ 4 and µ = µ 3, we have and (µ µ 1 (µ µ 4 (µ 3 µ 4 = (µ 3 µ 1 (µ 3 µ 4 (µ 1 µ 4, e (µ 1 +µ +µ 4 x = e µ 3 x e (µ 1 +µ 3 +µ 4 x = e µ x. Combining these last observations with (.8, we conclude our argument for the case of interest. The remaining estimates follow similarly. In addition to Lemmas.1 and., we have the following estimates on the N ± k. Lemma.3. Under the assumptions of Theorem 1.1, we have the following estimates on the N ± k (with similar estimates for x. For x, k =, 1, and for λ r, some r sufficiently small, k x N 1 (x; λ = O( λ1+ k e µ (λx k x N (x; λ = O( λ 1 + k e µ (λx k xn + 1 (x; λ = O( λ 1 ( e µ (λx µ (λk e µ 3 (λx µ 3 (λk + O( λ 1 + k e µ 3 (λx k xn + (x; λ = O( λ1+ k e µ (λx + O(1e µ 4 (λx. (.9 of (

14 Proof. We note at the outset that for x, we will take the expansions φ + k (x; λ = A+ k (λφ 1 (x; λ + B+ k (λφ (x; λ + C+ k (λψ 1 (x; λ + D+ k (λψ (x; λ. (.1 Without loss of generality, we take the convention according to which there must hold φ + 1 (x; = ū x(x = φ (x;, (.11 A + 1 (λ = O( λ1/ ; B + 1 (λ = 1 + O( λ1/ ; C + 1 (λ = O( λ1/ ; D + 1 (λ = O( λ1/ ; A + (λ = O(1; B+ (λ = O(1; C+ (λ = O(1; D+ (λ = O(1. (.1 As each estimate of Lemma.3 is proven similarly, we provide details only in the case of x N1. We have, similarly as in the proof of Lemma. x N1 (x; λ = xw(φ 1, φ, φ+, c(xw λ (x for which we compute φ x W(φ 1 φ φ + 1, φ, φ+ = det. φ 1 φ 1 φ φ φ + φ + In order to derive expressions for the terms φ ± k, we consider the eigenvalue problem (1.17. In general, we have the relation (c(xφ ± k + (b(xφ ± k (a(xφ ± k = λφ ± k. (.13 For φ 1 and φ, upon integration from up to x, and keeping in mind that a(x decays at exponential rate as x ±, we have c(xφ k x + b(xφ k a(xφ k = λ φ k (y; λdy. The most straightforward case is φ (x; λ, which for x < decays at exponential rate even for λ =. In this case, we define x W (x; λ = φ (y; λdy = O(1eµ 4 (λx. (.14 Proceeding similarly for φ 1 (x; λ, which fails to decay for λ =, we define W1 (x; λ = x λ φ 1 (y; λdy = x λ e µ 3 (λy (1 + O(e ᾱ y dy = 1 λ µ 3 (λx + λo(e α x, 3 (λeµ so that with c(xφ 1 + b(xφ 1 a(xφ 1 = λw1 (x; λ, W1 (x; λ = eµ 3 λ (λx ( µ 3 (λ + O( λ1/ e α x. Finally, for φ + (x; λ in the case x <, we must expand in terms of the linearly independent solutions φ k and ψ k, φ + (x; λ = A+ (λφ 1 (x; λ + B+ (λφ (x; λ + C+ (λψ 1 (x; λ + D+ (λψ (x, λ. 14

15 In this case, we integrate (.13 for y [x, + to obtain c(xφ + (x; λ b(xφ + (x; λ + a(xφ + (x; λ = λ where we divide this final integration up as M φ + (y; λdy = φ + (y; λdy + x x M x φ + (y; λdy =: λw + (x; λ, φ + (y; λdy, where M > is chosen sufficiently large so that the estimates of Lemma.1 hold for x M. For the integration over y > M, we have φ + (y; λdy = O(1dy + M M On the other hand, for integration over y < M, we have M x Combining these last observations, we conclude e µ+ (λy (1 + O(e ᾱ y dy = O( λ 1/. M M φ + (y; λdy = A+ (λ φ 1 (y; λdy + B+ (λ x x M M + C + (λ ψ1 (y; λdy + D+ (λ x x φ ψ (y; λdy (y, λdy. W + (x; λ = O(1 + M M λ [A + (λ φ 1 (y; λdy + B+ (λ φ (y; λdy x x M M ] + C + (λ ψ1 (y; λdy + D+ (λ ψ (y, λdy = O(1e µ 1 (λx x Omitting coefficient dependence on y for brevity of notation, we have φ 1 φ φ + det φ 1 φ 1 = det φ φ φ + φ + φ 1 φ φ + φ 1 b c φ 1 a c φ 1 λ c W 1 1 = det 1 = det a c φ 1 b c 1 b c φ φ x a c φ λ c W φ 1 φ φ + φ 1 λ φ φ + c W 1 λ c W λ φ 1 φ φ +. φ φ + λ c W 1 λ c W λ c W+ c W+ φ + b c φ+ a c φ+ λ c W+ We proceed by expanding this last determinant along its bottom row, giving (.15 λ c(x W 1 (x; λw(φ, φ+ + λ λ c(x W (x; λw(φ 1, φ+ + c(x W+ (x; λw(φ 1, φ. (.16 For the first expression in (.16, we observe W(φ, φ+ = A+ (λw(φ, φ 1 + C+ (λw(φ, ψ 1 + D+ (λw(φ, ψ = O(1e (µ 1 +µ 4 y = O(1, 15

16 while similarly In this way, the terms in (.16 give respectively W(φ 1, φ+ = O(1e(µ 1 +µ 3 y. O( λ 1/ e (µ 1 +µ 3 +µ 4 y + O( λ e (µ 1 +µ 3 +µ 4 y + O( λ 1/ e (µ 1 +µ 3 +µ 4 y. We now recall the relationship µ 3 + µ =, and note that according to spectral criterion (D, there holds D(λ = c 1 λ + O( λ 3/. Upon division, then, by c(yw λ (y = c(d(λ, we conclude the claimed estimate. The remaining estimates of Lemma.3 follow similarly. Lemma.4. Under the assumptions of Theorem 1.1, and for C + k (λ and D+ k (λ as defined in (.1, there holds C 1 + (λd+ (λ C+ (λd+ 1 (λ = O( λ. Proof. We first observe that by augmenting (.1 with y-derivatives up to third order, we obtain the matrix equations φ 1 φ ψ1 ψ A + φ + φ 1 φ ψ1 ψ k k φ 1 φ ψ1 ψ B + k C + = φ + k k φ + D + k. (.17 k Proceeding by Cramer s rule, we have, for example, φ 1 φ ψ 1 ψ C + 1 (λ = W(φ 1, φ, φ+ 1, ψ W(φ 1, φ, ψ 1, ψ, where the W notation is defined immediately following (1.19. By linear independence, the denominator of this last expression is non-zero, while for the numerator, we compute similarly as in (.15 W(φ 1, φ, φ+ 1, ψ = det = ( ψ φ + k φ 1 φ φ + 1 ψ φ 1 φ 1 λ c(x W 1 b(x c(x ψ φ φ λ c(x W+ + a(x b(x ψ ψ 1 + ψ 1 + λ c(x W+ 1 ψ ψ ψ b(x c(x ψ W(φ 1, φ, φ+ 1 + O( λ, + a(x b(x ψ where ψ is treated in a distinguished manner because it cannot be integrated to an asymptotic limit. Proceeding similarly, we also have W(φ 1, φ, φ 1, ψ C+ (λ = W(φ 1, φ, φ+, ψ = ( ψ b(x c(x ψ a(x + b(x ψ W(φ 1, φ, φ 1, ψ D+ 1 (λ = W(φ 1, φ, ψ 1, φ+ 1 ( = ψ 1 b(x c(x ψ a(x 1 + b(x ψ 1 W(φ 1, φ, φ 1, ψ D+ (λ = W(φ 1, φ, ψ 1, φ+ ( = ψ 1 b(x c(x ψ a(x 1 + b(x ψ 1 W(φ 1, φ, φ+ + O( λ1/ W(φ 1, φ, φ+ 1 + O( λ W(φ 1, φ, φ+ + O( λ1/. 16

17 Combining these observations, we compute W(φ 1, φ, φ 1, ψ ( C + 1 (λd+ (λ C+ (λd+ 1 (λ = [( ψ b(x [ ( ψ1 [( ψ c(x ψ + a(x b(x ψ b(x c(x ψ a(x 1 + b(x c(x ψ [ ( ψ1 b(x = ( ψ b(x c(x ψ ( ψ1 b(x b(x ψ 1 + a(x b(x ψ a(x + b(x ψ W(φ 1, φ, φ+ 1 + O( λ ] ] W(φ 1, φ, φ+ + O( λ1/ W(φ 1, φ, φ+ + O( λ1/ c(x ψ a(x ] 1 + b(x ψ 1 W(φ 1, φ, φ+ 1 + O( λ W(φ 1, φ, φ+ 1 O( λ1/ c(x ψ 1 ( ψ b(x ( + ψ1 + O( λ 3/. c(x ψ + a(x b(x ψ 1 + a(x b(x ψ b(x c(x ψ a(x 1 + b(x ψ 1 W(φ 1, φ, φ+ O( λ W(φ 1, φ, φ+ O( λ W(φ 1, φ, φ+ 1 O( λ1/ Recalling that φ (x; = ū x(x = φ + 1 (x,, we have that determinants involving both of these functions must vanish as λ, necessarily at rate λ 1/ or better by analyticity in ρ. We conclude the claimed estimate. We next state our main theorem on behavior of the Evans function for small values of λ, which we note is simply the extension to the current setting of Proposition.7 of [7]. Lemma.5. Under the assumptions of Theorem 1.1, and for D(λ as defined in (1., we have D(λ = γ(u + u λ + O( λ 3/, ] with γ = 1 φ 1 (; λ ū x( φ + (; λ c( det φ 1 (; λ ūxx ( φ + (; λ. φ 1 (; λ ūxxx ( φ + (; λ Proof. Observing that the solutions φ ± k (x; λ are analytic in the variable ρ := λ, we set D a (ρ := D(λ. We have, then, ρ D a ( = W( ρ φ 1, φ, φ+ 1, φ+ + W(φ 1, ρφ, φ+ 1, φ+ + W(φ 1, φ, ρφ + 1, φ+ + W(φ 1, φ, φ+ 1, ρφ + = W(φ 1, ρ(φ φ+ 1, ū x(, φ +, where the terms for which neither φ + 1 nor φ are differentiated are due to the choice of scaling (.11. We observe here that the fast-decaying solutions φ and φ+ 1 have been derived analytically in λ = ρ, and thus ρ φ (x; = ρ φ + 1 (x; =. (.18 In this way, we see immediately that ρ D a ( =. 17

18 Proceeding similarly for ρρ D a (ρ, we find ρρ D a ( = W( ρ φ 1 (;, ρ(φ φ+ 1 (;, ū x(, φ + (; + W(φ 1 (;, ρ(φ φ+ 1 (;, ū x(, ρ φ + (; + W(φ 1 (;, ρφ (;, ρφ + 1 (;, φ+ (; + W(φ 1 (;, ρρ(φ φ+ 1 (;, ū x(, φ + (;. Upon substitution of (.18, all terms with only single partials are eliminated, and we have ρρ D a ( = W(φ 1 (;, ρρ(φ φ+ 1 (;, ū x(, φ + (;. In order to understand ρ derivatives of φ and φ+ 1, we proceed similarly as in (.13, setting (c(xφ ± k + (b(xφ ± k (a(xφ ± k = ρ φ ± k, (.19 where prime here denotes differentiation with respect to x. Keeping in mind that φ and φ+ 1 exponential rate even for λ =, we have, upon integration on (, x], both decay at c(xφ + b(xφ a(xφ = ρ W, where W is as in (.14, and similarly for φ+ 1. Upon differentiation with respect to ρ, we find c(x( ρ φ + b(x( ρ φ a(x( ρ φ = ρw + ρ ( ρ W. with again a similar relationship for φ + 1. We next take a second ρ derivative of (.19 to obtain, upon integration and evaluation at ρ =, c(x( ρρ φ + b(x( ρρ φ a(x( ρρ φ = W (x;. Recalling that we have and similarly We conclude W (x; ρ := x φ (y; ρdy, x W (x; = ū y (ydy = ū(x u, x W 1 + (x; = ū y (ydy = ū(x u +. c(x( ρρ (φ φ+ 1 + b(x( ρρ (φ φ+ 1 a(x( ρρ (φ φ+ 1 = (u + u. Finally, we have φ 1 (; ρρ(φ φ+ 1 (; ū x( φ + (; φ 1 (; ρρ (φ ρρ D a ( = det φ+ 1 (; ū xx ( φ + (; φ 1 (; ρρ (φ φ+ 1 (; ū xxx ( φ + (; φ 1 (; ρρ (φ φ+ 1 (; ū xxxx ( φ + (; φ 1 (; ρρ(φ φ+ 1 (; ū x( φ + (; φ 1 (; ρρ (φ = det φ+ 1 (; ū xx ( φ + (; φ 1 (; ρρ (φ φ+ 1 (; ū xxx ( φ + (;, c( (u + u from which the claimed relationship is immediate. We now state for completeness a lemma asserting that (D is known to hold in the case (1.1 (1.3 with wave (

19 Lemma.6. For the case (1.1 (1.3, and for the standing front (1.4, spectral condition (D holds. Proof. In order to verify the first assertion of (D that the only zero that D(λ has with non-negative real part is λ = we first note that the integrated variable w(x = x φ(y; λdy satisfies the integrated eigenvalue problem [ Lw = λw; Lw := x ( xx V (xw x ], where V (x = (3/cosh (x/, and L is clearly a self-adjoint operator. Away from essential spectrum, the eigenvalues of L correspond with those of L, and so aside from the point λ = (which is an eigenvalue of L but not of L, our study reduces to that of L, which has been considered in [5, 36, 38] (see additionally the alternative analysis of [1]. For completeness, we briefly review the observations of [5, 36, 38]. As pointed out in [36, 38], the middle operator Mw := w xx + (1 + V (xw has been shown in [43] to have two isolated eigenvalues at and 3 4, and essential spectrum on the line [1,. It is an immediate consequence of the Spectral Theorem (see e.g. [37], p. 36 that M is a (nonstrictly positive operator. In the event that λ is an eigenvalue of L (necessarily real, we have that for some eigenfunction w associated with λ that (Mw x x = λw. Upon multiplication by w and integration over R, we have w x Mw x dx = λ w L. We can conclude by the positivity of M that λ. According to Lemma.5, the second assertion in stability criterion (D is verified if γ. This can be checked by a careful study of solutions to the eigenvalue problem (1.17. In the case of (1.1 (1.3, and profile (1.4, (1.17 becomes φ xxxx + (b(xφ xx = λφ, (. with b(x = 3 ū(x 1 ; ū(x = tanhx. In the case of φ 1 (x; λ, (. can be integrated on x (, x], and we obtain where as in the proof of Lemma.3 Setting λ =, we have φ 1 xxx + (b(xφ 1 x = λw1 (x; λ, W 1 (x; λ = eµ 3 (λx( λ µ 3 (λ + O( λ1/ e α x. φ 1 (x; xxx + (b(xφ 1 (x; x =. (.1 Proceeding similarly, we see that φ + (x; solves precisely the same equation. We can solve (.1 exactly by integrating once, and solving the equation φ xx + b(xφ = c 1. Taking c 1 = 1, we find the three linearly independent solutions φ 1(x = ū x (x [ φ (x = ū x(x φ 3 (x = cosh x. sinh x cosh3 x + 3 sinh x cosh x + 3 x ] It follows that φ 1 (x; and φ+ (x; must both be linear combinations of φ and φ 3, where without loss of generality we can choose to remove a constant multiple of the exponentially decaying function ū x without 19

20 affecting the estimates of Lemma.1. More precisely, we obtain a scaling that agrees with that of Lemma.1 by choosing φ 1 (x; = (φ (x + φ 3 (x φ + (x; = φ (x φ 3(x. Computing directly, we find γ =. This concludes the proof of Lemma.6. We conclude this section by combining the estimates of Lemmas.1.3 to obtain estimates on G λ (x, y for values of λ sufficiently small. We have the following lemma. Lemma.7. Under the assumptions of Theorem 1.1, and for G λ (x, y as defined in (1.18, we have the following estimates. For G λ (x, y = G λ (x, y + E λ (x, y, and λ < r, for some suitably small constant r, there holds (i For y x (ii For x y (iii For y x G λ (x, y = c 1 λ 1/ (e µ (λx e µ 3 (λx e µ (λy + O( λ 1/ e µ 3 (λ(x+y + O(1e µ (λ(xy µ y Gλ (x, y = c (λ 1 (e µ λ 1/ (λx e µ 3 (λx e µ (λy + O(1e µ 3 (λ(x+y + O( λ 1/ e µ (λ(xy + O( λ 1/ e η x e µ (λy + O(e η xy x Gλ (x, y = O(1(e µ (λx + e µ 3 (λx e µ (λy + O( λ 1/ e η x e µ (λy + O(e η xy xy Gλ (x, y = O( λ 1/ (e µ (λx + e µ 3 (λx e µ (λy + O(e η x e µ (λy + O(e η xy G λ (x, y = c λ 1/ e µ (λx (e µ (λy e µ 3 (λy + O( λ 1/ e µ 3 (λ(x+y + O(1e µ 3 (λ(xy y Gλ (x, y = O(1e µ (λx (e µ (λy + e µ 3 (λy + O( λ 1/ e η x e µ (λy + O(e η xy µ x Gλ (x, y = c (λ e µ λ 1/ (λx (e µ (λy e µ 3 (λy + O(1e µ 3 (λ(x+y + O( λ 1/ e µ 3 (λ(xy + O( λ 1/ e η x e µ (λy + O(e η xy xy Gλ (x, y = O( λ 1/ e µ (λx (e µ (λy + e µ 3 (λy + O( λ 1/ e η x e µ (λy + O(e η xy. G λ (x, y = O( λ 1/ e µ+ (λxµ (λy y Gλ (x, y = O(1e µ+ (λxµ (λy + O(e η x e µ (λy x Gλ (x, y = O(1e µ+ (λxµ (λy + O( λ 1/ e η x e µ (λy xy Gλ (x, y = O( λ 1/ e µ+ (λxµ (λy + O(e η x e µ (λy

21 and in all cases E λ (x, y = c E λ Remark.1. We note that the difference terms µ ūx(xe (λy (1 + O(e η y µ y E λ (x, y = c (λ E ū x (xe µ (λy (1 + O(e η y. λ (. c 1 λ 1/ (e µ (λx e µ 3 (λx, which clearly vanish at x =, arise naturally from our choice of ψ (x; λ and moreover are expected since the mass acculating near x = is recorded in the excited terms. However, since we additionally have a term O( λ 1/ e µ 3 (λ(x+y, there is no real advantage to be taken from the cancellation. In this way, our estimates do not seem quite as sharp as those of [38], obtained for a multidimensional generalization of (1.1 (1.3. We would also mention that we will point out in the proof of Lemma.7 precisely why it is that y-derivatives of E λ (x, y do not have a term that would correspond with differentiation of e ηy. Proof. We observe at the outset the relations, y N1 (y; λ = C+ (λ yw(φ 1, φ, ψ 1 (y; λ D + c(yw λ (y (λ yw(φ 1, φ, ψ (y; λ c(yw λ (y y N (y; λ = C+ 1 (λ yw(φ 1, φ, ψ 1 (y; λ + D 1 + c(yw λ (y (λ yw(φ 1, φ, ψ (y; λ. c(yw λ (y (.3 Since proofs of the four estimates in each case are similar, we provide details only for the estimates on y-derivatives. The case of y-derivatives is chosen because there is a subtle point in this case in which the estimates of Lemma. do not quite suffice, and we must use (.3 and the estimates of Lemma.3. Case (i: y x. For y x, we have y G λ (x, y = φ + 1 (x; λ yn1 (y; λ + φ+ (x; λ yn (y; λ [ = (A + C+ 1 A+ 1 C+ φ 1 (x + (B+ C+ 1 B+ 1 C+ φ (x ] + (D + C+ 1 D+ 1 C+ ψ (x y W(φ 1, φ, ψ 1 (y c(yw λ (y [ + (A + D+ 1 A+ 1 D+ φ 1 (x + (B+ D+ 1 B+ 1 D+ φ (x ] + (D 1 + C+ D+ C+ 1 ψ 1 (x y W(φ 1, φ, ψ (y. c(yw λ (y (.4 We group these into three sets of terms, beginning with the leading order G λ expression (D + C+ 1 D+ 1 C+ ψ (x yw(φ 1, φ, ψ 1 (y c(yw λ (y = (c 1 λ 1/ + O(1(e µ (λx e µ 3 (λx + O( λ 1/ e α x e µ (λy (µ (λ + O(e α y µ = c (λ 1 (e µ λ 1/ (λx e µ 3 (λx e µ (λ + O( λ 1/ e µ (λ(xy + O( λ 1/ e η x e µ (λy O(e η( x + y. We note in particular that we have made critical use here of Lemma.4; otherwise, we have employed the estimates of Lemma. in straightfoward fashion. 1

22 Next, we consider contributions to the excited term y E λ (x, y. In this case, we take [ B 1 + (λφ (x; λ C + (λ yw(φ 1, φ, ψ 1 (y; λ + D + c(yw λ (y (λ yw(φ 1, φ, ψ (y; λ ] c(yw λ (y = B 1 + (λφ (x; λ yn1 (y; λ ( ( = c 1 λ 1/ + O(1 ū x (x + O( λ 1/ e η x e µ (λy (1 + O(e η y = c 1 λ 1/ ū x (xe µ (λy (1 + O(e η y + O(e η x e µ (λx. It is of particular importance to note that the undifferentiated excited term is precisely the same thing with y-derivatives omitted. In this way, we see that y-differentiation improves the singularity of E λ (x, y as λ. For the remaining terms, we group according to (.3 in order to obtain A + (λφ 1 (x; λ yn (y; λ + A+ 1 (λφ 1 (x; λ yn1 (y; λ + B + (λφ (x; λ yn (y; λ + (D+ (λc+ 1 (λ D+ 1 (λc+ (λψ 1 (x; λ yw(φ 1, φ, ψ c(yw λ (y (.5 For the first three terms on the right hand side of (.5, we have an estimate by ( c 1 + O( λ 1/ e µ 3 (λxµ (λy (1 + O(e η x = O(1e µ 3 (λxµ (λy. For the third term on the right hand side of (.5, keeping in mind Lemma.4, we have (D + (λc+ 1 (λ D+ 1 (λc+ (λψ 1 (x; λ yw(φ 1, φ, ψ c(yw λ (y Case (ii: x y. For x y, we have = O(1e µ 1 (λ(xy. (.6 y G λ (x, y = φ 1 (x; λ yn 1 + (y; λ + φ (x; λ yn + (y; λ. (.7 Beginning again with the leading order G λ estimate, we have while for the excited and correction terms, we compute φ 1 (x; λ yn + 1 (y; λ = O(1eµ 3 (λ(xy, (.8 φ (x; λ yn + (y; λ ( = ū x (x + O( λ 1/ e η x [(k 1 λ 1/ + O(1e µ (λy (1 + O(e α y + O(1e µ(λy] 4 = k 1 λ 1/ ū x (xe µ (λy (1 + O(e α y + O(e η x e µ (λy + O(e η xy. For the excited term, we take Case (iii: y x. For y x, we have For the leading order G λ term, we take y E λ (x, y = k 1 λ 1/ ū x (xe µ (λy (1 + O(e α y. y G λ (x, y = φ + 1 (x; λ yn1 (y; λ + φ+ (x; λ yn (y; λ. (.9 φ + (x; λ yn (y; λ = O(1eµ+ (λxµ (λy, while for the excited and correction terms, we compute φ + 1 (x; λ yn1 (ū (y; λ = x (x + O( λ 1/ e η x (n 1 λ 1/ + O(1e µ (λy (1 + O(e α y.

Stability Analysis of Stationary Solutions for the Cahn Hilliard Equation

Stability Analysis of Stationary Solutions for the Cahn Hilliard Equation Stability Analysis of Stationary Solutions for the Cahn Hilliard Equation Peter Howard, Texas A&M University University of Louisville, Oct. 19, 2007 References d = 1: Commun. Math. Phys. 269 (2007) 765

More information

Nonlinear stability of time-periodic viscous shocks. Margaret Beck Brown University

Nonlinear stability of time-periodic viscous shocks. Margaret Beck Brown University Nonlinear stability of time-periodic viscous shocks Margaret Beck Brown University Motivation Time-periodic patterns in reaction-diffusion systems: t x Experiment: chemical reaction chlorite-iodite-malonic-acid

More information

Pointwise Green s Function Estimates Toward Stability for Degenerate Viscous Shock Waves

Pointwise Green s Function Estimates Toward Stability for Degenerate Viscous Shock Waves Communications in Partial Differential Equations, 3: 73, 006 Copyright Taylor & Francis, LLC ISSN 0360-530 print/53-433 online DOI: 0.080/0360530050035894 Pointwise Green s Function Estimates Toward Stability

More information

Asymptotic stability of the critical Fisher-KPP front using pointwise estimates

Asymptotic stability of the critical Fisher-KPP front using pointwise estimates Asymptotic stability of the critical Fisher-KPP front using pointwise estimates Grégory Faye and Matt Holzer 2 CNS, UM 529, Institut de Mathématiques de Toulouse, 3062 Toulouse Cede, France 2 Department

More information

Nonlinear stability of semidiscrete shocks for two-sided schemes

Nonlinear stability of semidiscrete shocks for two-sided schemes Nonlinear stability of semidiscrete shocks for two-sided schemes Margaret Beck Boston University Joint work with Hermen Jan Hupkes, Björn Sandstede, and Kevin Zumbrun Setting: semi-discrete conservation

More information

Evans function review

Evans function review Evans function review Part I: History, construction, properties and applications Strathclyde, April 18th 2005 Simon J.A. Malham http://www.ma.hw.ac.uk/ simonm/talks/ Acknowledgments T.J. Bridges, C.K.R.T.

More information

The Evans function and the stability of travelling waves

The Evans function and the stability of travelling waves The Evans function and the stability of travelling waves Jitse Niesen (University of Leeds) Collaborators: Veerle Ledoux (Ghent) Simon Malham (Heriot Watt) Vera Thümmler (Bielefeld) PANDA meeting, University

More information

THE MASLOV AND MORSE INDICES FOR SYSTEM SCHRÖDINGER OPERATORS ON R. 1. Introduction

THE MASLOV AND MORSE INDICES FOR SYSTEM SCHRÖDINGER OPERATORS ON R. 1. Introduction THE MASLOV AND MORSE INDICES FOR SYSTEM SCHRÖDINGER OPERATORS ON R P. HOWARD, Y. LATUSHKIN, AND A. SUKHTAYEV Abstract. Assuming a symmetric matrix-valued potential that approaches constant endstates with

More information

Lecture Notes on PDEs

Lecture Notes on PDEs Lecture Notes on PDEs Alberto Bressan February 26, 2012 1 Elliptic equations Let IR n be a bounded open set Given measurable functions a ij, b i, c : IR, consider the linear, second order differential

More information

Numerical Approximation of Phase Field Models

Numerical Approximation of Phase Field Models Numerical Approximation of Phase Field Models Lecture 2: Allen Cahn and Cahn Hilliard Equations with Smooth Potentials Robert Nürnberg Department of Mathematics Imperial College London TUM Summer School

More information

Introduction LECTURE 1

Introduction LECTURE 1 LECTURE 1 Introduction The source of all great mathematics is the special case, the concrete example. It is frequent in mathematics that every instance of a concept of seemingly great generality is in

More information

THE MASLOV AND MORSE INDICES FOR SCHRÖDINGER OPERATORS ON R. 1. Introduction. Hy := y + V (x)y = λy, dom(h) = H 1 (R),

THE MASLOV AND MORSE INDICES FOR SCHRÖDINGER OPERATORS ON R. 1. Introduction. Hy := y + V (x)y = λy, dom(h) = H 1 (R), THE MASLOV AND MORSE INDICES FOR SCHRÖDINGER OPERATORS ON R P. HOWARD, Y. LATUSHKIN, AND A. SUKHTAYEV Abstract. Assuming a symmetric potential that approaches constant endstates with a sufficient asymptotic

More information

Benjamin-Ono equation: Lax pair and simplicity of eigenvalues

Benjamin-Ono equation: Lax pair and simplicity of eigenvalues Benjamin-Ono equation: Lax pair and simplicity of eigenvalues The Benjamin-Ono equation is u t + 2uu x + Hu x x = where the Hilbert transform H is defined as Hϕx) = P.V. π ϕy) x y dy. Unfortunately the

More information

Section 12.6: Non-homogeneous Problems

Section 12.6: Non-homogeneous Problems Section 12.6: Non-homogeneous Problems 1 Introduction Up to this point all the problems we have considered are we what we call homogeneous problems. This means that for an interval < x < l the problems

More information

UNIQUENESS OF POSITIVE SOLUTION TO SOME COUPLED COOPERATIVE VARIATIONAL ELLIPTIC SYSTEMS

UNIQUENESS OF POSITIVE SOLUTION TO SOME COUPLED COOPERATIVE VARIATIONAL ELLIPTIC SYSTEMS TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 00, Number 0, Pages 000 000 S 0002-9947(XX)0000-0 UNIQUENESS OF POSITIVE SOLUTION TO SOME COUPLED COOPERATIVE VARIATIONAL ELLIPTIC SYSTEMS YULIAN

More information

Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games

Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games Stability of Feedback Solutions for Infinite Horizon Noncooperative Differential Games Alberto Bressan ) and Khai T. Nguyen ) *) Department of Mathematics, Penn State University **) Department of Mathematics,

More information

Chapter 3 Second Order Linear Equations

Chapter 3 Second Order Linear Equations Partial Differential Equations (Math 3303) A Ë@ Õæ Aë áöß @. X. @ 2015-2014 ú GA JË@ É Ë@ Chapter 3 Second Order Linear Equations Second-order partial differential equations for an known function u(x,

More information

RANDOM PROPERTIES BENOIT PAUSADER

RANDOM PROPERTIES BENOIT PAUSADER RANDOM PROPERTIES BENOIT PAUSADER. Quasilinear problems In general, one consider the following trichotomy for nonlinear PDEs: A semilinear problem is a problem where the highest-order terms appears linearly

More information

Class Meeting # 2: The Diffusion (aka Heat) Equation

Class Meeting # 2: The Diffusion (aka Heat) Equation MATH 8.52 COURSE NOTES - CLASS MEETING # 2 8.52 Introduction to PDEs, Fall 20 Professor: Jared Speck Class Meeting # 2: The Diffusion (aka Heat) Equation The heat equation for a function u(, x (.0.). Introduction

More information

Nonlinear convective stability of travelling fronts near Turing and Hopf instabilities

Nonlinear convective stability of travelling fronts near Turing and Hopf instabilities Nonlinear convective stability of travelling fronts near Turing and Hopf instabilities Margaret Beck Joint work with Anna Ghazaryan, University of Kansas and Björn Sandstede, Brown University September

More information

Spectral stability of periodic waves in dispersive models

Spectral stability of periodic waves in dispersive models in dispersive models Collaborators: Th. Gallay, E. Lombardi T. Kapitula, A. Scheel in dispersive models One-dimensional nonlinear waves Standing and travelling waves u(x ct) with c = 0 or c 0 periodic

More information

Stability of compressive and undercompressive thin film travelling waves

Stability of compressive and undercompressive thin film travelling waves Euro. Jnl of Applied Mathematics (001), vol. 1, pp. 53 91. c 001 Cambridge University Press Printed in the United Kingdom 53 Stability of compressive and undercompressive thin film travelling waves ANDREA

More information

3 Applications of partial differentiation

3 Applications of partial differentiation Advanced Calculus Chapter 3 Applications of partial differentiation 37 3 Applications of partial differentiation 3.1 Stationary points Higher derivatives Let U R 2 and f : U R. The partial derivatives

More information

Green s Functions and Distributions

Green s Functions and Distributions CHAPTER 9 Green s Functions and Distributions 9.1. Boundary Value Problems We would like to study, and solve if possible, boundary value problems such as the following: (1.1) u = f in U u = g on U, where

More information

Varying the direction of propagation in reaction-diffusion equations in periodic media

Varying the direction of propagation in reaction-diffusion equations in periodic media Varying the direction of propagation in reaction-diffusion equations in periodic media Matthieu Alfaro 1 and Thomas Giletti 2. Contents 1 Introduction 2 1.1 Main assumptions....................................

More information

Existence Theory: Green s Functions

Existence Theory: Green s Functions Chapter 5 Existence Theory: Green s Functions In this chapter we describe a method for constructing a Green s Function The method outlined is formal (not rigorous) When we find a solution to a PDE by constructing

More information

Mathematical Methods - Lecture 9

Mathematical Methods - Lecture 9 Mathematical Methods - Lecture 9 Yuliya Tarabalka Inria Sophia-Antipolis Méditerranée, Titane team, http://www-sop.inria.fr/members/yuliya.tarabalka/ Tel.: +33 (0)4 92 38 77 09 email: yuliya.tarabalka@inria.fr

More information

A review of stability and dynamical behaviors of differential equations:

A review of stability and dynamical behaviors of differential equations: A review of stability and dynamical behaviors of differential equations: scalar ODE: u t = f(u), system of ODEs: u t = f(u, v), v t = g(u, v), reaction-diffusion equation: u t = D u + f(u), x Ω, with boundary

More information

MATH 205C: STATIONARY PHASE LEMMA

MATH 205C: STATIONARY PHASE LEMMA MATH 205C: STATIONARY PHASE LEMMA For ω, consider an integral of the form I(ω) = e iωf(x) u(x) dx, where u Cc (R n ) complex valued, with support in a compact set K, and f C (R n ) real valued. Thus, I(ω)

More information

Partial differential equation for temperature u(x, t) in a heat conducting insulated rod along the x-axis is given by the Heat equation:

Partial differential equation for temperature u(x, t) in a heat conducting insulated rod along the x-axis is given by the Heat equation: Chapter 7 Heat Equation Partial differential equation for temperature u(x, t) in a heat conducting insulated rod along the x-axis is given by the Heat equation: u t = ku x x, x, t > (7.1) Here k is a constant

More information

SPRING 2006 PRELIMINARY EXAMINATION SOLUTIONS

SPRING 2006 PRELIMINARY EXAMINATION SOLUTIONS SPRING 006 PRELIMINARY EXAMINATION SOLUTIONS 1A. Let G be the subgroup of the free abelian group Z 4 consisting of all integer vectors (x, y, z, w) such that x + 3y + 5z + 7w = 0. (a) Determine a linearly

More information

Exponential Stability of the Traveling Fronts for a Pseudo-Para. Pseudo-Parabolic Fisher-KPP Equation

Exponential Stability of the Traveling Fronts for a Pseudo-Para. Pseudo-Parabolic Fisher-KPP Equation Exponential Stability of the Traveling Fronts for a Pseudo-Parabolic Fisher-KPP Equation Based on joint work with Xueli Bai (Center for PDE, East China Normal Univ.) and Yang Cao (Dalian University of

More information

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms

08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms (February 24, 2017) 08a. Operators on Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/real/notes 2016-17/08a-ops

More information

Notes: Outline. Diffusive flux. Notes: Notes: Advection-diffusion

Notes: Outline. Diffusive flux. Notes: Notes: Advection-diffusion Outline This lecture Diffusion and advection-diffusion Riemann problem for advection Diagonalization of hyperbolic system, reduction to advection equations Characteristics and Riemann problem for acoustics

More information

THE CAHN-HILLIARD EQUATION WITH A LOGARITHMIC POTENTIAL AND DYNAMIC BOUNDARY CONDITIONS

THE CAHN-HILLIARD EQUATION WITH A LOGARITHMIC POTENTIAL AND DYNAMIC BOUNDARY CONDITIONS THE CAHN-HILLIARD EQUATION WITH A LOGARITHMIC POTENTIAL AND DYNAMIC BOUNDARY CONDITIONS Alain Miranville Université de Poitiers, France Collaborators : L. Cherfils, G. Gilardi, G.R. Goldstein, G. Schimperna,

More information

Multisolitonic solutions from a Bäcklund transformation for a parametric coupled Korteweg-de Vries system

Multisolitonic solutions from a Bäcklund transformation for a parametric coupled Korteweg-de Vries system arxiv:407.7743v3 [math-ph] 3 Jan 205 Multisolitonic solutions from a Bäcklund transformation for a parametric coupled Korteweg-de Vries system L. Cortés Vega*, A. Restuccia**, A. Sotomayor* January 5,

More information

Practice Problems For Test 3

Practice Problems For Test 3 Practice Problems For Test 3 Power Series Preliminary Material. Find the interval of convergence of the following. Be sure to determine the convergence at the endpoints. (a) ( ) k (x ) k (x 3) k= k (b)

More information

Separation of Variables in Linear PDE: One-Dimensional Problems

Separation of Variables in Linear PDE: One-Dimensional Problems Separation of Variables in Linear PDE: One-Dimensional Problems Now we apply the theory of Hilbert spaces to linear differential equations with partial derivatives (PDE). We start with a particular example,

More information

TRANSPORT IN POROUS MEDIA

TRANSPORT IN POROUS MEDIA 1 TRANSPORT IN POROUS MEDIA G. ALLAIRE CMAP, Ecole Polytechnique 1. Introduction 2. Main result in an unbounded domain 3. Asymptotic expansions with drift 4. Two-scale convergence with drift 5. The case

More information

Final Exam May 4, 2016

Final Exam May 4, 2016 1 Math 425 / AMCS 525 Dr. DeTurck Final Exam May 4, 2016 You may use your book and notes on this exam. Show your work in the exam book. Work only the problems that correspond to the section that you prepared.

More information

Stability, the Maslov Index, and Spatial Dynamics

Stability, the Maslov Index, and Spatial Dynamics Stability, the Maslov Index, and Spatial Dynamics Margaret Beck Boston University joint work with Graham Cox (MUN), Chris Jones (UNC), Yuri Latushkin (Missouri), Kelly McQuighan (Google), Alim Sukhtayev

More information

Lu u. µ (, ) the equation. has the non-zero solution

Lu u. µ (, ) the equation. has the non-zero solution MODULE 18 Topics: Eigenvalues and eigenvectors for differential operators In analogy to the matrix eigenvalue problem Ax = λx we shall consider the eigenvalue problem Lu = µu where µ is a real or complex

More information

Practice Problems For Test 3

Practice Problems For Test 3 Practice Problems For Test 3 Power Series Preliminary Material. Find the interval of convergence of the following. Be sure to determine the convergence at the endpoints. (a) ( ) k (x ) k (x 3) k= k (b)

More information

Answers to Problem Set Number MIT (Fall 2005).

Answers to Problem Set Number MIT (Fall 2005). Answers to Problem Set Number 6. 18.305 MIT (Fall 2005). D. Margetis and R. Rosales (MIT, Math. Dept., Cambridge, MA 02139). December 12, 2005. Course TA: Nikos Savva, MIT, Dept. of Mathematics, Cambridge,

More information

MA22S3 Summary Sheet: Ordinary Differential Equations

MA22S3 Summary Sheet: Ordinary Differential Equations MA22S3 Summary Sheet: Ordinary Differential Equations December 14, 2017 Kreyszig s textbook is a suitable guide for this part of the module. Contents 1 Terminology 1 2 First order separable 2 2.1 Separable

More information

Understand the existence and uniqueness theorems and what they tell you about solutions to initial value problems.

Understand the existence and uniqueness theorems and what they tell you about solutions to initial value problems. Review Outline To review for the final, look over the following outline and look at problems from the book and on the old exam s and exam reviews to find problems about each of the following topics.. Basics

More information

Nonlinear Stability for Multidimensional Fourth-Order Shock Fronts

Nonlinear Stability for Multidimensional Fourth-Order Shock Fronts Arch. Rational Mech. Anal. 26 Digital Object Identifier DOI.7/s25-5-9-y Nonlinear Stability for Multidimensional Fourth-Order Shock Fronts Peter Howard & Changbing Hu Communicated by C.M. Dafermos Abstract

More information

Physics 202 Laboratory 5. Linear Algebra 1. Laboratory 5. Physics 202 Laboratory

Physics 202 Laboratory 5. Linear Algebra 1. Laboratory 5. Physics 202 Laboratory Physics 202 Laboratory 5 Linear Algebra Laboratory 5 Physics 202 Laboratory We close our whirlwind tour of numerical methods by advertising some elements of (numerical) linear algebra. There are three

More information

Resolvent Estimates and Quantification of Nonlinear Stability

Resolvent Estimates and Quantification of Nonlinear Stability Resolvent Estimates and Quantification of Nonlinear Stability Heinz Otto Kreiss Department of Mathematics, UCLA, Los Angeles, CA 995 Jens Lorenz Department of Mathematics and Statistics, UNM, Albuquerque,

More information

Stability of Patterns

Stability of Patterns Stability of Patterns Steve Schecter Mathematics Department North Carolina State University 1 2 Overview Motivation Systems of viscous conservation laws and their variants are partial differential equations

More information

Math 322. Spring 2015 Review Problems for Midterm 2

Math 322. Spring 2015 Review Problems for Midterm 2 Linear Algebra: Topic: Linear Independence of vectors. Question. Math 3. Spring Review Problems for Midterm Explain why if A is not square, then either the row vectors or the column vectors of A are linearly

More information

Spectral Analysis for Periodic Solutions of the Cahn Hilliard Equation on R

Spectral Analysis for Periodic Solutions of the Cahn Hilliard Equation on R Spectral Analysis for Periodic Solutions of the Cahn Hilliard Equation on R Peter Howard November 17, 29 Abstract We consider the spectrum associated with the linear operator obtained when the Cahn Hilliard

More information

Dispersion relations, stability and linearization

Dispersion relations, stability and linearization Dispersion relations, stability and linearization 1 Dispersion relations Suppose that u(x, t) is a function with domain { < x 0}, and it satisfies a linear, constant coefficient partial differential

More information

The following definition is fundamental.

The following definition is fundamental. 1. Some Basics from Linear Algebra With these notes, I will try and clarify certain topics that I only quickly mention in class. First and foremost, I will assume that you are familiar with many basic

More information

Numerical Evans Function Computation Jeffrey Humpherys Brigham Young University INTRODUCTION

Numerical Evans Function Computation Jeffrey Humpherys Brigham Young University INTRODUCTION Numerical Evans Function Computation Jeffrey Humpherys Brigham Young University INTRODUCTION 1 Traveling Wave Consider the evolution equation u t = F(u, u x,u xx,...). A traveling wave with speed is a

More information

Slow Modulation & Large-Time Dynamics Near Periodic Waves

Slow Modulation & Large-Time Dynamics Near Periodic Waves Slow Modulation & Large-Time Dynamics Near Periodic Waves Miguel Rodrigues IRMAR Université Rennes 1 France SIAG-APDE Prize Lecture Jointly with Mathew Johnson (Kansas), Pascal Noble (INSA Toulouse), Kevin

More information

BOUNDARY VALUE PROBLEMS ON A HALF SIERPINSKI GASKET

BOUNDARY VALUE PROBLEMS ON A HALF SIERPINSKI GASKET BOUNDARY VALUE PROBLEMS ON A HALF SIERPINSKI GASKET WEILIN LI AND ROBERT S. STRICHARTZ Abstract. We study boundary value problems for the Laplacian on a domain Ω consisting of the left half of the Sierpinski

More information

Hamiltonian partial differential equations and Painlevé transcendents

Hamiltonian partial differential equations and Painlevé transcendents The 6th TIMS-OCAMI-WASEDA Joint International Workshop on Integrable Systems and Mathematical Physics March 22-26, 2014 Hamiltonian partial differential equations and Painlevé transcendents Boris DUBROVIN

More information

MATH 425, HOMEWORK 3 SOLUTIONS

MATH 425, HOMEWORK 3 SOLUTIONS MATH 425, HOMEWORK 3 SOLUTIONS Exercise. (The differentiation property of the heat equation In this exercise, we will use the fact that the derivative of a solution to the heat equation again solves the

More information

Partial Differential Equations

Partial Differential Equations M3M3 Partial Differential Equations Solutions to problem sheet 3/4 1* (i) Show that the second order linear differential operators L and M, defined in some domain Ω R n, and given by Mφ = Lφ = j=1 j=1

More information

Hamiltonian partial differential equations and Painlevé transcendents

Hamiltonian partial differential equations and Painlevé transcendents Winter School on PDEs St Etienne de Tinée February 2-6, 2015 Hamiltonian partial differential equations and Painlevé transcendents Boris DUBROVIN SISSA, Trieste Lecture 2 Recall: the main goal is to compare

More information

Convex Functions and Optimization

Convex Functions and Optimization Chapter 5 Convex Functions and Optimization 5.1 Convex Functions Our next topic is that of convex functions. Again, we will concentrate on the context of a map f : R n R although the situation can be generalized

More information

The influence of a line with fast diffusion on Fisher-KPP propagation : integral models

The influence of a line with fast diffusion on Fisher-KPP propagation : integral models The influence of a line with fast diffusion on Fisher-KPP propagation : integral models Antoine Pauthier Institut de Mathématique de Toulouse PhD supervised by Henri Berestycki (EHESS) and Jean-Michel

More information

Partial Differential Equations

Partial Differential Equations Part II Partial Differential Equations Year 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2015 Paper 4, Section II 29E Partial Differential Equations 72 (a) Show that the Cauchy problem for u(x,

More information

Travelling-wave spatially periodic forcing of asymmetric binary mixtures

Travelling-wave spatially periodic forcing of asymmetric binary mixtures Travelling-wave spatially periodic forcing of asymmetric binary mixtures Lennon Ó Náraigh Home fixture 8th October 2018 Travelling waves, binary fluids 8th October 2018 1 / 32 Context of work I Binary

More information

Oblique derivative problems for elliptic and parabolic equations, Lecture II

Oblique derivative problems for elliptic and parabolic equations, Lecture II of the for elliptic and parabolic equations, Lecture II Iowa State University July 22, 2011 of the 1 2 of the of the As a preliminary step in our further we now look at a special situation for elliptic.

More information

Hamiltonian partial differential equations and Painlevé transcendents

Hamiltonian partial differential equations and Painlevé transcendents The 6th TIMS-OCAMI-WASEDA Joint International Workshop on Integrable Systems and Mathematical Physics March 22-26, 2014 Hamiltonian partial differential equations and Painlevé transcendents Boris DUBROVIN

More information

Coherent structures near the boundary between excitable and oscillatory media

Coherent structures near the boundary between excitable and oscillatory media Coherent structures near the boundary between excitable and oscillatory media Jeremy Bellay University of Minnesota Department of Computer Science 200 Union St. S.E. Minneapolis, MN 55455, USA Arnd Scheel

More information

13 PDEs on spatially bounded domains: initial boundary value problems (IBVPs)

13 PDEs on spatially bounded domains: initial boundary value problems (IBVPs) 13 PDEs on spatially bounded domains: initial boundary value problems (IBVPs) A prototypical problem we will discuss in detail is the 1D diffusion equation u t = Du xx < x < l, t > finite-length rod u(x,

More information

Linear Hyperbolic Systems

Linear Hyperbolic Systems Linear Hyperbolic Systems Professor Dr E F Toro Laboratory of Applied Mathematics University of Trento, Italy eleuterio.toro@unitn.it http://www.ing.unitn.it/toro October 8, 2014 1 / 56 We study some basic

More information

z x = f x (x, y, a, b), z y = f y (x, y, a, b). F(x, y, z, z x, z y ) = 0. This is a PDE for the unknown function of two independent variables.

z x = f x (x, y, a, b), z y = f y (x, y, a, b). F(x, y, z, z x, z y ) = 0. This is a PDE for the unknown function of two independent variables. Chapter 2 First order PDE 2.1 How and Why First order PDE appear? 2.1.1 Physical origins Conservation laws form one of the two fundamental parts of any mathematical model of Continuum Mechanics. These

More information

arxiv: v2 [math.oc] 31 Jul 2017

arxiv: v2 [math.oc] 31 Jul 2017 An unconstrained framework for eigenvalue problems Yunho Kim arxiv:6.09707v [math.oc] 3 Jul 07 May 0, 08 Abstract In this paper, we propose an unconstrained framework for eigenvalue problems in both discrete

More information

A Perron-type theorem on the principal eigenvalue of nonsymmetric elliptic operators

A Perron-type theorem on the principal eigenvalue of nonsymmetric elliptic operators A Perron-type theorem on the principal eigenvalue of nonsymmetric elliptic operators Lei Ni And I cherish more than anything else the Analogies, my most trustworthy masters. They know all the secrets of

More information

Starting from Heat Equation

Starting from Heat Equation Department of Applied Mathematics National Chiao Tung University Hsin-Chu 30010, TAIWAN 20th August 2009 Analytical Theory of Heat The differential equations of the propagation of heat express the most

More information

B. Differential Equations A differential equation is an equation of the form

B. Differential Equations A differential equation is an equation of the form B Differential Equations A differential equation is an equation of the form ( n) F[ t; x(, xʹ (, x ʹ ʹ (, x ( ; α] = 0 dx d x ( n) d x where x ʹ ( =, x ʹ ʹ ( =,, x ( = n A differential equation describes

More information

Criteria for pointwise growth and their role in invasion processes

Criteria for pointwise growth and their role in invasion processes Criteria for pointwise growth and their role in invasion processes Matt Holzer and Arnd Scheel University of Minnesota School of Mathematics 127 Vincent Hall, 206 Church St SE Minneapolis, MN 55455, USA

More information

New methods of reduction for ordinary differential equations

New methods of reduction for ordinary differential equations IMA Journal of Applied Mathematics (2001) 66, 111 125 New methods of reduction for ordinary differential equations C. MURIEL AND J. L. ROMERO Departamento de Matemáticas, Universidad de Cádiz, PO Box 40,

More information

REVIEW OF DIFFERENTIAL CALCULUS

REVIEW OF DIFFERENTIAL CALCULUS REVIEW OF DIFFERENTIAL CALCULUS DONU ARAPURA 1. Limits and continuity To simplify the statements, we will often stick to two variables, but everything holds with any number of variables. Let f(x, y) be

More information

Travelling waves. Chapter 8. 1 Introduction

Travelling waves. Chapter 8. 1 Introduction Chapter 8 Travelling waves 1 Introduction One of the cornerstones in the study of both linear and nonlinear PDEs is the wave propagation. A wave is a recognizable signal which is transferred from one part

More information

An Introduction to Stability Theory for Nonlinear PDEs

An Introduction to Stability Theory for Nonlinear PDEs An Introduction to Stability Theory for Nonlinear PDEs Mathew A. Johnson 1 Abstract These notes were prepared for the 217 Participating School in Analysis of PDE: Stability of Solitons and Periodic Waves

More information

AM 205: lecture 14. Last time: Boundary value problems Today: Numerical solution of PDEs

AM 205: lecture 14. Last time: Boundary value problems Today: Numerical solution of PDEs AM 205: lecture 14 Last time: Boundary value problems Today: Numerical solution of PDEs ODE BVPs A more general approach is to formulate a coupled system of equations for the BVP based on a finite difference

More information

REGULARITY RESULTS FOR THE EQUATION u 11 u 22 = Introduction

REGULARITY RESULTS FOR THE EQUATION u 11 u 22 = Introduction REGULARITY RESULTS FOR THE EQUATION u 11 u 22 = 1 CONNOR MOONEY AND OVIDIU SAVIN Abstract. We study the equation u 11 u 22 = 1 in R 2. Our results include an interior C 2 estimate, classical solvability

More information

A sharp diffuse interface tracking method for approximating evolving interfaces

A sharp diffuse interface tracking method for approximating evolving interfaces A sharp diffuse interface tracking method for approximating evolving interfaces Vanessa Styles and Charlie Elliott University of Sussex Overview Introduction Phase field models Double well and double obstacle

More information

Lecture No 1 Introduction to Diffusion equations The heat equat

Lecture No 1 Introduction to Diffusion equations The heat equat Lecture No 1 Introduction to Diffusion equations The heat equation Columbia University IAS summer program June, 2009 Outline of the lectures We will discuss some basic models of diffusion equations and

More information

Math 123 Homework Assignment #2 Due Monday, April 21, 2008

Math 123 Homework Assignment #2 Due Monday, April 21, 2008 Math 123 Homework Assignment #2 Due Monday, April 21, 2008 Part I: 1. Suppose that A is a C -algebra. (a) Suppose that e A satisfies xe = x for all x A. Show that e = e and that e = 1. Conclude that e

More information

A COUNTEREXAMPLE TO AN ENDPOINT BILINEAR STRICHARTZ INEQUALITY TERENCE TAO. t L x (R R2 ) f L 2 x (R2 )

A COUNTEREXAMPLE TO AN ENDPOINT BILINEAR STRICHARTZ INEQUALITY TERENCE TAO. t L x (R R2 ) f L 2 x (R2 ) Electronic Journal of Differential Equations, Vol. 2006(2006), No. 5, pp. 6. ISSN: 072-669. URL: http://ejde.math.txstate.edu or http://ejde.math.unt.edu ftp ejde.math.txstate.edu (login: ftp) A COUNTEREXAMPLE

More information

Implicit Functions, Curves and Surfaces

Implicit Functions, Curves and Surfaces Chapter 11 Implicit Functions, Curves and Surfaces 11.1 Implicit Function Theorem Motivation. In many problems, objects or quantities of interest can only be described indirectly or implicitly. It is then

More information

Classification of Second order PDEs

Classification of Second order PDEs Chapter 3 Classification of Second order PDEs This chapter deals with a finer classification of second order quasilinear PDEs, as compared to Chapter 1. In Section 3.1, we present a formal procedure to

More information

Determinant of the Schrödinger Operator on a Metric Graph

Determinant of the Schrödinger Operator on a Metric Graph Contemporary Mathematics Volume 00, XXXX Determinant of the Schrödinger Operator on a Metric Graph Leonid Friedlander Abstract. In the paper, we derive a formula for computing the determinant of a Schrödinger

More information

Krein-Rutman Theorem and the Principal Eigenvalue

Krein-Rutman Theorem and the Principal Eigenvalue Chapter 1 Krein-Rutman Theorem and the Principal Eigenvalue The Krein-Rutman theorem plays a very important role in nonlinear partial differential equations, as it provides the abstract basis for the proof

More information

Spectral analysis of θ-periodic Schrödinger operators and applications to periodic waves

Spectral analysis of θ-periodic Schrödinger operators and applications to periodic waves Spectral analysis of θ-periodic Schrödinger operators and applications to periodic waves Peter Howard and Soyeun Jung July 28, 2017 Abstract Assuming a symmetric matrix-valued potential, we consider the

More information

Putzer s Algorithm. Norman Lebovitz. September 8, 2016

Putzer s Algorithm. Norman Lebovitz. September 8, 2016 Putzer s Algorithm Norman Lebovitz September 8, 2016 1 Putzer s algorithm The differential equation dx = Ax, (1) dt where A is an n n matrix of constants, possesses the fundamental matrix solution exp(at),

More information

Introduction to Partial Differential Equations

Introduction to Partial Differential Equations Introduction to Partial Differential Equations Philippe B. Laval KSU Current Semester Philippe B. Laval (KSU) Key Concepts Current Semester 1 / 25 Introduction The purpose of this section is to define

More information

4. Analysis of heat conduction

4. Analysis of heat conduction 4. Analysis of heat conduction John Richard Thome 11 mars 2008 John Richard Thome (LTCM - SGM - EPFL) Heat transfer - Conduction 11 mars 2008 1 / 47 4.1 The well-posed problem Before we go further with

More information

THE NUMBER OF POLYNOMIAL SOLUTIONS OF POLYNOMIAL RICCATI EQUATIONS

THE NUMBER OF POLYNOMIAL SOLUTIONS OF POLYNOMIAL RICCATI EQUATIONS This is a preprint of: The number of polynomial solutions of polynomial Riccati equations, Armengol Gasull, Joan Torregrosa, Xiang Zhang, J. Differential Equations, vol. 261, 5071 5093, 2016. DOI: [10.1016/j.jde.2016.07.019]

More information

The variational iteration method for solving linear and nonlinear ODEs and scientific models with variable coefficients

The variational iteration method for solving linear and nonlinear ODEs and scientific models with variable coefficients Cent. Eur. J. Eng. 4 24 64-7 DOI:.2478/s353-3-4-6 Central European Journal of Engineering The variational iteration method for solving linear and nonlinear ODEs and scientific models with variable coefficients

More information

Heat Equation, Wave Equation, Properties, External Forcing

Heat Equation, Wave Equation, Properties, External Forcing MATH348-Advanced Engineering Mathematics Homework Solutions: PDE Part II Heat Equation, Wave Equation, Properties, External Forcing Text: Chapter 1.3-1.5 ecture Notes : 14 and 15 ecture Slides: 6 Quote

More information

ODE Final exam - Solutions

ODE Final exam - Solutions ODE Final exam - Solutions May 3, 018 1 Computational questions (30 For all the following ODE s with given initial condition, find the expression of the solution as a function of the time variable t You

More information

Stability of an abstract wave equation with delay and a Kelvin Voigt damping

Stability of an abstract wave equation with delay and a Kelvin Voigt damping Stability of an abstract wave equation with delay and a Kelvin Voigt damping University of Monastir/UPSAY/LMV-UVSQ Joint work with Serge Nicaise and Cristina Pignotti Outline 1 Problem The idea Stability

More information

Review and problem list for Applied Math I

Review and problem list for Applied Math I Review and problem list for Applied Math I (This is a first version of a serious review sheet; it may contain errors and it certainly omits a number of topic which were covered in the course. Let me know

More information