Stability Computations for Nilpotent Hopf Bifurcations in Coupled Cell Systems

Stability Computations for Nilpotent Hopf Bifurcations in Coupled Cell Systems M. Golubitsky M. Krupa April 18, 006 Abstract Vanderbauwhede and van Gils, Krupa, and Langford studied unfoldings of bifurcations with purely imaginary eigenvalues and a nonsemisimple linearization, which generically occurs in codimension three. In networks of identical coupled ODE these nilpotent Hopf bifurcations can occur in codimension one. Elmhirst and Golubitsky show that these bifurcations can lead to surprising branching patterns of periodic solutions, where the type of bifurcation depends in part on the existence of an invariant subspace corresponding to partial synchrony. We study the stability of some of these bifurcating solutions. In the absence of partial synchrony the problem is similar to the generic codimension three problem. In this case we show that the bifurcating branches are generically unstable. When a synchrony subspace is present we obtain partial stability results by using only those near identity transformations that leave this subspace invariant. 1 Introduction Networks of coupled systems of differential equations arise naturally in a variety of contexts [10], from discretization of partial differential equations to models of locomotor central pattern generators [8]. The dynamics occurring in such networks often have properties that are nongeneric if the special USA Department of Mathematics, University of Houston, Houston, TX 7704-3008, USA Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM, 1

structure of the network is absent. One such property is the occurrence of Hopf bifurcation with non-semisimple eigenvalues in codimension one bifurcations. An example of a network with this property was given by Golubitsky, Nicol and Stewart [4]. Building on [4], Elmhirst and Golubitsky [1] analyzed branching for nilpotent Hopf bifurcations occurring in three different types of networks, finding branching patterns of periodic solutions very different from the single nontrivial branch in generic Hopf bifurcation. Nilpotent Hopf bifurcations occur when an equilibrium has a purely imaginary eigenvalue of algebraic multiplicity two and a non-semisimple linearization. Such bifurcations are of codimension three in the absence of special structure. Branching patterns were studied by Vanderbauwhede [1] using the Liapunov-Schmidt method and by van Gils, Krupa, and Langford [3] using the normal form approach. In the context of coupled cells there are degeneracies both in the linear and nonlinear parts of the vector field. Consequently, the results of either [1] or [3] have limited direct application to the coupled cell problem. As shown by Cesari and Hale, Liapunov-Schmidt reduction can be used to study Hopf bifurcations [7] and is the main tool used in [1]. This method has the advantage that branches of periodic solutions can be found by solving for the zeros of a reduced mapping and the disadvantage that the stability of these solutions is not necessary preserved in the reduction. The alternative reduction method, center manifold plus normal form, has the advantage of preserving stability of solutions, but is often more difficult to compute. A point of particular importance for coupled cell networks is that the network structure leads to degeneracies in the bifurcation equations obtained using either reduction method and unlike symmetry these degeneracies are not easy to keep track of. In either case the relationship between coefficients in the reduced equations and coefficients in the original coupled cell vector field is not easy to establish. Our goal is to use the normal form approach to study nilpotent Hopf bifurcations in coupled cell networks and thereby to compute the stability of periodic solutions emanating from these bifurcations. In this work we consider specifically two of the networks studied in [1], the three-cell and fivecell networks shown in Figure 1. Using normal form theory we are able to recover the bifurcation equations derived in [1] for both of these networks and obtain complete stability information for the five-cell network (all periodic solutions are unstable). We obtain only partial stability results for the threecell network.

1 1 4 3 3 5 Figure 1: Three-cell and five-cell networks with nilpotent linear parts. In the theory developed in [11, 5] graphs such as those in Figure 1 correspond to classes of systems of differential equations. The three-cell network corresponds to coupled systems of the form ẋ 1 = f(x 1, x 1, x 3, λ) ẋ = f(x, x 1, x 3, λ) ẋ 3 = f(x 3, x, x 3, λ) (1.1) where x 1, x, x 3 R k, λ R is a bifurcation parameter, and the overbar indicates that f : R k R k R R k satisfies f(a, b, c, λ) = f(a, c, b, λ). The five-cell network corresponds to systems of the form ẋ 1 = f(x 1, x 1, x 4, x 4, λ) ẋ = f(x, x 1, x, x 5, λ) ẋ 3 = f(x 3, x, x 4, x 4, λ) ẋ 4 = f(x 4, x, x 4, x 5, λ) ẋ 5 = f(x 5, x 1, x, x 3, λ) (1.) where x j R k, f : R k R 3k R R k, and the overbar indicates that f(a, b, c, d, λ) is invariant under permutation of b, c, d. By the results of [1] the five-cell network has branches of periodic orbits of opposite criticality whose amplitudes grow at order λ. We prove that these solutions are generically (within the class (1.)) unstable. For the threecell network, [1] proves the existence of two or four branches of periodic solutions, each of which grows at order λ 1/. One of these solutions has partial synchrony (since x 1 = x is a flow-invariant subspace). We obtain complete stability information for this partially synchronous solution. For the other solutions we outline a possible approach to the stability problem, noting that, unless there is a new idea, only partial results can be expected. 3

The structure of coupled cell networks may impose restrictions on both the linear and the nonlinear part of the normal form. The restrictions on the linear level are present in most networks, but the degeneracies at nonlinear level in the normal form may or may not be present. We conjecture that network architecture must force the presence of an invariant space of partial synchrony with a nontrivial intersection with the center subspace in order for restrictions on the nonlinear terms in the normal form to be present in a robust way. The five-cell network in [1] (Figure 1 (right)) is an example of a network where there are no restrictions on the nonlinear level, whereas the three-cell network in [1] (Figure 1 (left)) gives an example of a network with an invariant space of partial synchrony, thus providing an example where restrictions on cubic terms in the normal form are present. Section of this paper contains the analysis of systems with no restrictions on the nonlinear level. In Section 3 we treat systems with a flow-invariant synchrony subspace. No restrictions on reduction at cubic level In this section we consider the five-cell network (1.) analyzed Elmhirst and Golubitsky [1], who proved using the Liapunov-Schmidt method that there exist two branches of solutions with amplitude O(λ), one supercritical and one subcritical. Here we reprove the result of [1] using normal form theory and we show that both of the bifurcationg branches are unstable. Recall that the Liapunov-Schmidt reduction preserves the phase shift symmetry, which leads naturally to S 1 symmetry in the bifurcation equation. The normal form is not unique, but it can be chosen to be S 1 symmetric up to any finite order. We use the following S 1 equivariant normal form (derived in []). ( ż1 ż ) = ( i + λ 1 µ i + λ with z i C, λ R, µ C and The S 1 action is given by ) ( z1 z ) + Φ 1 ( z1 z Φ k Φ k (z 1 z 1, Im (z 1 z ), λ, µ). θ(z 1, z ) = (e iθ z 1, e iθ z ). ) + Φ ( 0z1 ), (.1) 4

Since (.1) is a normal form for a generic nilpotent Hopf bifurcation it has one real parameter λ and one complex parameter µ, which unfold the linear part. For a certain class of networks, including all the networks studied by [1], the network architecture forces the existence of a nontrivial Jordan block, which implies that µ = 0. Indeed, since we study only codimension one coupled cell bifurcations, we may assume that Φ k is independent of µ. The network architecture can also impose constraints on the nonlinear terms in the normal form. In this section we make a nondegenaracy assumption that holds for (1.) but is violated for any network with an invariant subspace of partial synchrony which has a nontrivial intersection with the center subspace. Networks of this type will be considered in Section 3. Let a + ib be defined as follows The nondegeneracy assumption is a + ib = Φ z 1 z 1 (0, 0, 0). The following result is proved using MAPLE. b 0. (.) Proposition.1 The condition (.) holds generically for the five-cell network (1.). In this section we prove the following results. Proposition. If b 0, then there exist two branches of periodic solutions with amplitude O(λ); one of the branches is supercritical and one is subcritical. Proposition.3 Periodic solutions on both branches are unstable. Proposition. is proved in section.1 and Proposition.3 is proved in section.. 5

.1 Proof of Proposition. Recall that periodic orbits near a Hopf bifurcation correspond to relative equilibria of the S 1 symmetric normal form. We define new variables (w 1, w ), suitable for the analysis of relative equilibria, as follows: z 1 = w 1 e i(1 τ)t, z = w e i(1 τ)t (.3) After transforming to the new variables, we observe that in both equations there is a factor e i(1 τ)t. We cancel this factor and obtain the following ẇ 1 = (λ + iτ)w 1 + w + Φ 1 w 1 ẇ = (λ + iτ)w + Φ w 1 + Φ 1 w (.4) We will carry out the analysis for (.4) truncated at lowest order: ẇ 1 = (λ + iτ)w 1 + w ẇ = (λ + iτ)w + (a + bi)w 1 w 1 (.5) By finding the equilibria of (.5) near 0 with λ and τ small we obtain all the first order approximations of small amplitude periodic solutions of the original problem. The result can be extended to (.4) by standard perturbation theory. We need to solve: 0 = (λ + iτ)w 1 + w 0 = (λ + iτ)w + (a + ib)w 1 w 1 (.6) We solve the first equation in (.6) for w as function of w 1 and substitute the result into the second equation. Subsequently we cancel the factor w 1, obtaining the bifurcation equation: 0 = (λ + iτ) + (a + ib)w 1 w 1 (.7) Equation (.7) is S 1 invariant, so when finding solutions we can assume that w 1 = x > 0. We substitute this choice into (.7) and replace the complex equation by two real ones, obtaining: 0 = τ λ + ax 0 = τλ + bx. (.8) We now prove a result which implies Proposition.. 6

Proposition.4 Assume b 0 and let = a + b a. Then the solutions of (.8) are given by τ = λ b, x = ( ) λ, (.9) b Proof Solving the second equation in (.8) for x we obtain x = τλ b. (.10) Consequently we reduce (.8) to the quadratic equation: bτ + aλτ bλ = 0 One choice of the solution is τ = λ b (.11) Combining with (.10) we conclude that x = ( ) λ, b which is the positive solution. The other choice of the solution for τ gives x < 0, which is impossible... Proof of Proposition.3 We first note that the Floquet exponents of the small amplitude periodic solutions of the normal form system (.1) are just the eigenvalues of the linearization of (.4) at zeroes of that system. The proof of Proposition.3 proceeds as follows. We compute the eigenvalues of the linearization of the truncated system (.5) at the solutions (.8). The characteristic polynomial is of degree four, but it has a 0 root corresponding to the eigenvector along the orbit of the normal form S 1 symmetry. We show below that the three nonzero roots of this characteristic polynomial correspond to the roots of ˆq(µ) = ˆµ 3 4ˆµ + (1 + 3K)ˆµ + 4(1 + K) (.1) 7

in the scaled variable ˆµ = µ/λ, where K = /b > 0 is a constant depending on a and b. More precisely, we show that a root ˆµ of (.1) corresponds to an eigenvalue of the linearization of the truncated system (.5) at a solution for some λ 0, where µ = λˆµ and τ = Kλ. Rather then trying to find the roots of ˆq explicitly, which would result in lengthy formulas, we prove that ˆq always has at least one root with positive real part and at least one root with negative real part, which proves Proposition.3 covering both the cases of λ > 0 and λ < 0. The proof divides into two parts: the derivation of (.1) and the existence of a positive real part eigenvalue. Derivation of ˆq. We begin by obtaining the linearization and its determinant. We transform (.5) to real coordinates: w 1 = x 1 + y 1, w = x + y. The system (.5) in the real coordinates becomes: ẋ 1 = λx 1 τy 1 + x ẏ 1 = τx 1 + λy 1 + y ẋ = λx τy + (x 1 + y 1 )(ax 1 by 1 ) ẏ = τx + λy + (x 1 + y 1)(bx 1 + ay 1 ) (.13) Recall that we have found equilibria of the form (x, 0), where x satisfies (.8). Linearizing (.13) at such an equilibrium we get the matrix: λ τ 1 0 A = τ λ 0 1 3ax bx λ τ 3bx ax τ λ Let ( ) ( λ τ 3ax bx B = and C = τ λ 3bx ax Note that det A = det(b C) and similarly ). p(µ) = det(a µi) = det((b µi) C). 8

Using (.8) it follows that ( ) (λ µ) (B µi) C = τ 3ax (λ µ)τ + bx (λ µ)τ 3bx (λ µ) τ ax ( ) µ = λµ ax τµ τµ bx µ λµ Note that when µ = 0 we see that det A = 0, as expected. We now have p(µ) = µq(µ), where : q(µ) = det((b µi) C) µ = µ 3 4λµ + (λ + 6τ )µ + 4λ(λ + τ ). Next recall from (.9) that τ = λ /b. Then q(µ) = µ 3 4λµ + (1 + 3K)λ µ + 4(1 + K)λ 3. Finally, we divide q by λ 3 and obtain the polynomial (.1). Verification of a real part positive root. As mentioned at the beginning of the section, the roots of q cannot be expressed in simple form for general a and b. We can however show that the roots of q are never purely imaginary, and then prove Proposition.3 by verifying the root structure of q for a single choice of a and b. The basic tool that we use is the fact that a cubic polynomial µ 3 + a µ + a 1 µ + a 0 has purely imaginary roots if and only if a 0 a 1 a = 0. (.14) Clearly ˆq cannot have a 0 root. We also prove that it can never have a root on the imaginary axis. In the case of ˆq, we have a 0 a 1 a = 4(3 + 7K), which is nonzero for any choice of a and b 0. We can easily find a specific choice of a and b (for example K = 1) for which ˆq has both a root with positive real part and a root with negative real part. The result must hold by continuous dependence of the roots of ˆq on a and b. 9

3 Equations with synchrony subspace Consider a three-cell system of the form (1.1). Then there is a synchrony subspace defined by x 1 = x. We assume for simplicity that the internal dynamics is two dimensional, which implies that the synchrony subspace is four dimensional. We assume that there is a Hopf bifurcation from a synchronous equilibrium and that the eigenspace of the critical eigenvalue is not contained in the synchrony subspace. The following is proved in [1]. Lemma 3.1 The eigenspace of the critical eigenvalue is contained in the synchrony subspace. The intersection of the center subspace with the synchrony subspace is the eigenspace. We now perform a center manifold reduction to a four dimensional center manifold. Clearly the intersection of the center manifold with the synchrony subspace is a two-dimensional invariant manifold tangent to the critical eigenspace. Moreover, [9, Lemma 4.1] lets us choose coordinates (z 1, z ) on the center manifold in such a way that the two-dimensional plane z = 0 is both the critical eigenspace and is flow invariant. General theory [] tells us that there is an S 1 symmetric normal form. We prove that there is such a normal form for which the space z = 0 is flow invariant. The question centers about how the invariant space z = 0 transforms when the system is brought to normal form. More precisely, consider ż 1 = iz 1 + z + f 1 (z 1, z ) ż = iz + f (z 1, z ). (3.1) We assume that f and g are C smooth functions whose constant and linear terms vanish. We prove the following. Theorem 3. Assume z = 0 is an invariant space for (3.1), or, equivalently, that f (z 1, 0) = 0. Then, for any N > 0, (3.1) can be transformed to the normal form ż 1 = iz 1 + z + g 1 (z 1, z ) + O( z N+1 ) ż = iz + g (z 1, z ) + O( z N+1 ) (3.) where g 1 and g are S 1 -equivariant polynomial mappings of degree N, and (3.) has an invariant space z = 0. 10

The next subsection is devoted to the proof of Theorem 3.. Note that S 1 symmetric normal forms are not unique and that Theorem 3. does not hold for every such normal form, including the normal form of []. In the sequel we consider the truncated and unfolded normal form: ż 1 = (λ + i)z 1 + z + g 1 (z 1, z ) ż = (λ + i)z + g (z 1, z ) (3.3) where g 1, g are S 1 -equivariant polynomial mappings homogeneous of degree 3, and λ is a bifurcation parameter. 3.1 Proof of Theorem 3. Suppose that a vector field F has a flow-invariant subspace W and that ϕ is a diffeomorphism that leaves W invariant. Then the change of coordinates of F by ϕ is a vector field that leaves W invariant. For each n N we carry out the proof of Theorem 3. in two steps, each of which preserves the invariant plane z = 0. Step 1: Use a transformation of the form ( ) ( z1 w = 1 w + q(w 1, w ) z ), (3.4) where q is a homogeneous polynomial of degree n satisfies q(w 1, 0) = 0. We show that we can choose q so that the terms of order n in the resulting ẇ equation are S 1 -equivariant and the space w = 0 remains flow-invariant. Step : We use the transformation ( ) ( ) z1 w1 + p(w = 1, w ) z w (3.5) so that the terms of order n in the resulting ẇ 1 equation are S 1 -equivariant, the RHS of the w equation remains unchanged up to order n, and the space w = 0 remains flow-invariant. Let L = ( i 1 0 i 11 ).

Define the adjoint operator ad L by ad L (q) = iq (q z1 (iz 1 + z ) + q z (iz ) q z1 (i z 1 z ) q z (i z )).(3.6) Let P n be the space of homogeneous polynomials of degree n in z 1, z 1, z, z. It follows that, for every n > 1, ad L is a linear transformation of P n into itself. Suppose a change of coordinates of the form (3.4) is applied to (3.1), with q P n. Then the transformed system has the form ẇ 1 = iw 1 + w + q + f 1 (w 1, w ) + O( z n+1 ) ẇ = iw + f (w 1, w ) + ad L (q) + O( z n+1 ) (3.7) Note that for any n > 1, ad L can be used to remove terms of order n from the RHS of (3.1). The following two lemmas specify which terms can be removed. Lemma 3.3 The subspace P n can be decomposed into ad L invariant subspaces V k, where k = 0,..., n, with V k = span { z k 1 1 zl 1 1 z k zl : k 1 + k = k; l 1 + l = n k } Moreover, the spaces V k,0 V k defined by V k,0 = span { z k 1 1 zl 1 1 z k zl : k + l > 0, k 1 + k = k; l 1 + l = n k } are also invariant for ad L. Proof Follows by inspection from the definition of ad L. Lemma 3.4 If k n+1 then ad L restricted to either V k or V k,0 is an isomorphism. Proof Suppose z k 1 1 z l 1 1 z k z l is an element of P n. Then It follows that ad L (z k 1 1 zl 1 1 z k zl ) =i(n + 1 k)z k 1 1 zl 1 1 z k zl + k 1 z k 1 1 1 z l 1 1 z k +1 z l + l 1 z k 1 1 zl 1 1 1 z k zl +1 ad L = (n + 1 k)i + N where N is nilpotent. The claim about V k follows. The claim about V k,0 is proved analogously. 1

Corollary 3.5 Terms in V k can be removed provided that k n+1. When n is odd and k = n+1 the terms in V k are S 1 -equivariant. Proof of Theorem 3. Suppose we apply a transformation of the form (3.5), with p homogeneous of order n, to a system of the form (3.1). Then the transformed system has the form ẇ 1 = iw 1 + f 1 (w 1, w ) + ad L (p) + O( z n+1 ) ẇ = iw + f (w 1 + p, w ). (3.8) Note that (3.8) still has an invariant space w = 0, regardless of the form of p, since f (w 1 + p, 0) = 0. Also, the w equation in (3.8) can be rewritten in the form ẇ = iw + f (w 1, w ) + O( z n+1 ) which means that the equivariance of f up to order n is preserved. It now follows that we can bring (3.1) to the form (3.) by successively applying transformations of the form (3.4) and (3.5). At any order n we first carry out (3.4) and then (3.5), bringing the system to the normal form of order n and preserving the invariance of w = 0. 3. Branching Suppose a normal form system of equations of the form (3.3) is given. Transforming to the variables (.3) we obtain the equations ẇ 1 = (λ + τi)w 1 + w + g 1 (w 1, w ) ẇ = (λ + τi)w + g (w 1, w ) (3.9) where τ is a small parameter corresponding to the deviation of the period from π. Recall that periodic orbits of (1.1) near a Hopf bifurcation correspond to equilibria of (3.9). We look for synchronous periodic orbits which correspond to equilibria of (3.9) with w = 0. We can assume, due to S 1 symmetry, that w 1 = x R. Consequently we obtain the branching equations: λ + p(x ) = 0 τ + q(x ) = 0. where p and q are such that g 1 (x, 0) = x(p(x ) + iq(x )). Expanding: p(x ) = A R x + O(x 4 ), q(x ) = A I x + O(x 4 ) 13 (3.10)

we obtain that (3.10) at lowest order have the form: λ + A R x = 0 τ + A I x = 0. (3.11) 3.3 Stability of the synchronous solution We assume that x is a solution of (3.10). We now compute the Jacobian of (3.9) at the solution w 1 = x, w = 0. The Jacobian of (3.9) is given in block form as ( ) Dw1 g J = 1 (x, 0) D w g 1 (x, 0), 0 D w g (x, 0) where 0 denotes the zero matrix and D wi g j are real matrices. Using complex notation (D w g) p (u) = g g (p)u + w w (p)ū. Since J is upper block diagonal, its eigenvalues are given by the eigenvalues of D w1 g 1 (x, 0) and the eigenvalues of D w g (x, 0). It follows also that D w1 g 1 (x, 0) has an eigenvalue 0, corresponding to translation along the S 1 group orbit, and an eigenvalue p(x ) (for the definition of p see the sentence following (3.10)). Hence the branch can only be stable if it is supercritical. The other two eigenvalues to both have negative real part is tr D w g (x, 0) < 0 and det D w g (x, 0) > 0, which is equivalent to Writing: Re g w (x, 0) < 0 and g (x, 0) w g (x, 0) w > 0. (3.1) g w (x, 0) = Bx + O(x 4 ) and g w (x, 0) = Cx + O(x 4 ) we obtain that (3.1) is given, up to O(x ), by Re B < 0 and B C > 0. (3.13) 14

0.4 x1r 0.4 0. x1r 0. 0 10 0 30 40 50 60 70 t 0 85 90 95 100 0. t 0. 0.4 0.4 Figure : Synchronous periodic solution transient on left and no transient on right. Simulation with f in (3.14), λ = 0.1, α R = 0.5, β R = 0.5, α I = 1, and β I = 0.75. It is clear that conditions (3.13) can be satisfied. Figure shows a stable synchronous solution, computed for a network of type (1.1) with f given as follows: f(a, b, c) =λa + Ka b c + 1 a (β R a + β I Ka) + 1 4 (β RLa β I LKa)(b 1 b + c 1 c ) 1 (β RLKa + β I La)(b 1 b + c 1 c ) (3.14) + 1 ( b + c )(α R a + α I Ka) where λ R, α, β C, ( ) 0 1 K = 1 0 and L = ( 1 0 0 1 ) 15

3.4 Remarks on stability of asynchronous solutions In this section we consider a truncation of (3.9) of the form ẇ 1 = (λ + iτ)w 1 + w + Aw 1w 1 ẇ = (λ + iτ)w + Bw w 1 w 1 (3.15) For (3.15) we can easily find explicit expression for an asynchronous solution and we can derive a sufficient condition for stability, which can be satisfied. Thus we prove that asynchronous solutions can be stable. The branching equations for (3.15) are 0 = (λ + iτ)w 1 + w + Aw 1 w 1 0 = (λ + iτ)w + Bw w 1 w 1 (3.16) Due to the S 1 action there exists a solution of (3.16) of the form (x, w ), where x is real. We can now easily solve (3.16), obtaining the branching equations λ + B R x = 0 τ + B I x = 0 w = (B A)x 3. (3.17) Remark By the results of [1] a network of the form (1.1) has two or four branches of solutions. For C = 0 we are in the case of two branches of solutions, rather than four. We prove the following result on stability of solutions given by (3.17). Proposition 3.6 The branch given by (3.17) can only be stable if it is supercritical. Moreover, there exists an open region in the space of coefficients (A, B), where this solution is stable Proof Rewriting 3.15 in real form we obtain ẋ 1 = λx 1 τy 1 + x + (x 1 + y1)(a R x 1 A I y 1 ) ẏ 1 = τx 1 + λy 1 + y + (x 1 + y1)(a I x 1 + A R y 1 ) ẋ = λx τy + (B R x B I y )(x 1 + y 1 ) ẏ = τx + λy + (B R y + B I x )(x 1 + y 1 ) (3.18) 16

Linearizing (3.18) about the solution (3.17) yields the following Jacobian matrix: (3A R B R )x (B I A I )x 1 0 (3A I B I )x (A R B R )x 0 1 x 4 (B R (B R A R ) B I (B I A I )) 0 0 0 x 4 (B R (B I A R ) + B I (B R A R )) 0 0 0, (3.19) where x is determined by the first equation in (3.17). The characteristic polynomial for (3.19) has the form with p(µ) = µ(a 0 x 6 + a 1 x 4 µ + a x µ + µ 3 ) a 0 = B R ((B I A I ) + (B R A R ) ) a 1 = (A R B R ) + (A R + B R )(A R B R ) + 3(A I B I ) a = 4A R B R We can now introduce a polynomial q: q(ν) = a 0 + a 1 ν + a ν + ν 3. The roots of p and q are in 1-1 correspondence (if x 0), namely if ν 0 is a root of q then ν 0 x is a root of p. The coefficients a 0 and a correspond to the product and the sum of the roots, respectively, so a 0 < 0 and a < 0 are necessary for stability. Since a 0 < 0 is equivalent to B R < 0, A I B I and A R B R the branch can only be stable if it is supercritical. If a 0 = 0, a 1 > 0 and a < 0 then q has a 0 eigenvalue and two eigenvalues with negative real parts. It follows that the conditions a 0 < 0, a 1 > 0 and a < 0 imply stability provided that a 0 is sufficiently close to 0. Figure 3 shows a stable asynchronous solution computed for a network of type (1.1). Acknowledgments The research of MG was supported in part by NSF Grant DMS-04459. The research of MK was supported in part by NSF Grant DMS-0406608. MG thanks the University of Toronto for its hospitality. 17

0.4 x1r 0. 0 85 90 95 100 t 0. 0.4 Figure 3: Asynchronous periodic solution obtained by simulation with f in (3.14), λ = 0.1, α R = 1.5, β R = 0.5, α I = 1, and β I = 0.75. References [1] T. Elmhirst and M. Golubitsky. Nilpotent Hopf Bifurcations in Coupled Cell Systems. SIAM J. Appl. Dynam. Sys. (006). To appear. [] C. Elphick, E. Tirapegui, M. E. Brachet, P. Coullet and G. Iooss. A simple global characterization for normal forms of singular vector fields. Physica D 9 (1987) 95-17. [3] S.A. van Gils, M. Krupa, and W.F. Langford. Hopf bifurcation with non-semisimple 1:1 resonance Nonlinearity 3 (1990) 85 850. [4] M. Golubitsky, M. Nicol, and I. Stewart. Some curious phenomena in coupled cell networks. J. Nonl. Sci. 14 No. (004) 119 36. [5] M. Golubitsky, I. Stewart, and A. Török. Patterns of synchrony in coupled cell networks with multiple arrows. SIAM J. Appl. Dynam. Sys. 4 No. 1 (005) 78 100. [6] G. Iooss and W.F. Langford. Near reversible 1:1 resonance. Draft (005). [7] M. Golubitsky and D.G. Schaeffer. Singularities and Groups in Bifurcation Theory: Vol. I, Appl. Math. Sci. 51, Springer Verlag, New York, 1984. 18

[8] N. Kopell and G.B. Ermentrout. Coupled oscillators and the design of central pattern generators. Math. Biosci. 89 (1988) 14 3. [9] M. Leite and M. Golubitsky. Homogeneous three-cell networks. Nonlinearity (006). Submitted. [10] I. Stewart. Networking opportunity. Nature 47 (004) 601 604. [11] I. Stewart, M. Golubitsky, and M. Pivato. Symmetry groupoids and patterns of synchrony in coupled cell networks. SIAM J. Appl. Dynam. Sys. No. 4 (003) 609 646. [1] A. Vanderbauwhede. Hopf bifurcations with non-simple eigenvalues. In: Multiparameter Bifurcation Theory (M. Golubitsky and J. Guckenheimer, eds), Contemp. Math. 56 (1986) 343 353. 19