BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs


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1 BIFURCATION PHENOMENA Lecture 1: Qualitative theory of planar ODEs Yuri A. Kuznetsov August, 2010
2 Contents 1. Solutions and orbits. 2. Equilibria. 3. Periodic orbits and limit cycles. 4. Homoclinic orbits.
3 Literature 1. A.A. Andronov, E.A. Leontovich, I.I. Gordon, and A.G. Maier Qualitative Theory of SecondOrder Dynamic Systems, Willey & Sons, London, L.P. Shilnikov, A.L. Shilnikov, D.V. Turaev, and L.O. Chua Methods of Qualitative Theory in Nonlinear Dynamics, Part I, World Scientific, Singapore, F. Dumortier, J. Llibre, and J.C. Artés Qualitative Theory of Planar Differential Systems, Universitext, SpringerVerlag, Berlin, 2006
4 1. SOLUTIONS AND ORBITS Newton s Second Law: mẍ = F(x, ẋ) { ẋ = y, ẏ = m 1 F(x, y) General planar system: { ẋ = P(x, y), ẏ = Q(x, y) where X = ( x y ) or Ẋ = f(x), X R 2,, f(x) = ( P(x, y) Q(x, y) Theorem 1 If f is smooth than for any inital point there exists y ( ) 0 x(t) a unique locally defined solution t such that x(0) = x y(t) 0 and y(0) = y 0. ). ( x0 )
5 Definition 1 Let I be the maximal definition interval of a solution t X(t), t I. The oriented by the advance of time image X(I) R 2 is called the orbit. f(x) X Vector field: X f(x) f(x) 0 is tangent to the orbit through X orbits do not cross. Definition 2 Phase portrait of a planar system is the collection of all its orbits in R 2. We draw only key orbits, which determine the topology of the phase portrait.
6 Types of orbits: 1. Equilibria: X(t) X 0 so that f(x 0 ) = Periodic orbits (cycles): X(t) X 0, X(t + T) = X(t), t R The minimal T > 0 is called the period of the cycle. 3. Connecting orbits: lim t ± X(t) = X ± with f(x ± ) = 0. If X = X + the connecting orbit is called homoclinic If X X + the connecting orbit is called heteroclinic. 4. All other orbits
7 Theorem 2 (PoincaréBendixson) A bounded orbit of a smooth system Ẋ = f(x), X R 2, tends to one of the following sets in the phase plane: (i) an equilibrium point; (ii) a periodic orbit; (iii) a union of equilibria and their connecting orbits.
8 2. EQUILIBRIA: Nullisoclines f(x) = 0 { P(x, y) = 0, Q(x, y) = 0. P = ( ) Px P y and Q = ( ) Qx Q y are orthogonal to P = 0 and Q = 0, resp. Q(x,y) = 0 P Q Jacobian matrix of the equilibrium X 0 : A = f X (X 0 ) = ( Px P y Q x Q y ) x=x0,y=y 0 y 0 P(x, y) = 0 If det A 0 the nullisoclines intersect transversally at X 0. If det A = 0 the nullisoclines are tangent at X 0. x 0
9 Eigenvalues of the equilibrium X 0 are the eigenvalues of A, i.e. the solutions of where λ 2 σλ + = 0, σ = λ 1 + λ 2 = SpA = P x (x 0, y 0 ) + Q y (x 0, y 0 ), = λ 1 λ 2 = det A = P x (x 0, y 0 )Q y (x 0, y 0 ) P y (x 0, y 0 )Q x (x 0, y 0 ). λ 1,2 = σ 2 ± σ 2 4 Definition 3 An equilibrium X 0 is hyperbolic if R(λ) 0. Equilibrium X 0 with λ 1 = 0 (i.e. det A = 0) is called multiple. Equilibrium X 0 with λ 1 + λ 2 = 0 (i.e. Sp A = 0) is called neutral.
10 Phase portraits of planar linear systems Ẏ = AY (n u,n s ) Eigenvalues Phase portrait Stability (0, 2) node stable focus (1, 1) saddle unstable node (2, 0) unstable focus
11 Definition 4 Two systems are called topologically equivalent if their phase portraits are homeomorphic, i.e. there is a continuous invertible transformation that maps orbits of one system onto orbits of the other, preserving their orientation. Theorem 3 (GrobmanHartman) Consider a smooth nonlinear system Ẋ = AX + F(X), F = O( X 2 ) O(2), and its linearization Ẏ = AY. If R(λ) 0 for all eigenvalues of A, then these systems are locally topologically equivalent near the origin. Warning: A stable/unstable node is locally topologically equivalent to a stable/unstable focus.
12 Trivial topological equivalences 1. Orbital equivalence: Ẋ = f(x) Ẏ = g(y )f(y ) where g : R 2 R is smooth positive function; Y = h(x) = X preserves orbits. 2. Smooth equivalence: Ẋ = f(x) Ẏ = h X (h 1 (Y ))f(h 1 (Y )), where h : R 2 R 2 is a smooth diffeomorphism; the substitution Y = h(x) transforms solutions onto solutions: Ẏ = h X (X)Ẋ = h X (X)f(X) where X = h 1 (Y ). 3. Smooth orbital equivalence:
13 Simplest critical cases λ 1 = 0, λ 2 0 By a linear diffeomorphism, Ẋ = f(x) can be transformed into { ẋ = ax 2 + bxy + cy 2 + O(3), ẏ = λ 2 y + O(2). If a 0 then Ẋ = f(x) is locally topologically equivalent near the origin to { ẋ = ax 2, Saddlenode (a > 0): ẏ = λ 2 y. λ 2 < 0 λ 2 > 0
14 λ 1,2 = ±iω, ω > 0 By a linear diffeomorphism, Ẋ = f(x) can be transformed into { ẋ = ωy + R(x, y), R = O(2), ẏ = ωx + S(x, y), S = O(2). Introduce z = x + iy C. Then this system becomes ż = iωz + g(z, z), where ( z + z g(z, z) = R 2, z z 2i Write its Taylor expansion in z, z: ) + is ( z + z 2, z z ). 2i g(z, z) = 1 2 g 20z 2 + g 11 z z g 02 z g 21z 2 z +... Definition 5 The first Lyapunov coefficient is l 1 = 1 2ω 2R(ig 20g 11 + ωg 21 ).
15 If l 1 0 then Ẋ = f(x) is locally topologically equivalent near the origin to { ρ = l1 ρ 3, ϕ = 1, where (ρ, ϕ) are polar coordinates: z = ρe iϕ. Weak focus: stable unstable l 1 < 0 l 1 > 0
16 3. PERIODIC ORBITS AND LIMIT CYCLES Poincaré map: ξ P(ξ) = µξ + O(2), ξ P(ξ) 0 where the multiplier µ = exp ( T 0 (div f)(x0 (t)) dt ) > 0 X 0 (t) Definition 6 A cycle of the planar system is hyperbolic if µ 1. The cycle is stable if µ < 1 and is unstable if µ > 1. ξ µ > 1 ξ = ξ µ < 1 ξ
17 Theorem 4 (BendixsonDulac) If (div f)(x) > 0 (< 0) in a disc D R 2, then Ẋ = f(x) has no periodic orbits in D. Proof: Suppose, there is a cycle C D and let Ω be a bounded domain with Ω = C. C Pdy Qdx = f, dx 0 C but C Pdy Qdx = (div f)dx > 0 Ω (or < 0), contradiction. f = ( P Q X dx ) f = ( C Q P )
18 Implications: 1. If div(gf) > 0 (< 0) in a disc D R 2 for a smooth positive function g : R 2 R, then Ẋ = f(x) has no periodic orbits in D. 2. If div(gf) > 0 (< 0) is an annulus A R 2 for a smooth positive function g : R 2 R, then Ẋ = f(x) has at most one periodic orbit in A. 3. If f(x) 0 and div(gf) < 0 in a trapping annulus A R 2 for a smooth positive function g : R 2 R, then Ẋ = f(x) has a unique stable periodic orbit in A.
19 Example: Consider { ẋ = y P(x, y), ẏ = ax + by + αx 2 + βy 2 Q(x, y). Define in R 2. Then g(x, y) = e 2βx > 0 x (gp) + y (gp) = x (e 2βx y) + y (e 2βx (ax + by + αx 2 + βy 2 )) = 2βe 2βx y + be 2βx + 2βe 2βx y = be 2βx 0 in R 2 if b 0. no periodic orbits.
20 Reversible systems Definition 7 A smooth system Ẋ = f(x) is called reversible if f(jx) = Jf(X) for a matrix J such that J 2 = E. The transformation X JX is called an involution. If there is an orbit segment without equilibria connecting two points in the fixed subspace {Y : JY = Y } of the involution, there is a periodic orbit of Ẋ = f(x). Periodic orbits occur in continuos familes. Example: 4 { ẋ = y, ẏ = x + xy x 3, J ( x y ) = ( x y ) y x
21 Example: A preypredator model ξη ξ = ξ (1 + αξ)(1 + βη) f 1(ξ, η), ξη η = η + (1 + αξ)(1 + βη) f 2(ξ, η), where α, β > 0 and x, y 0. There is a family of closed orbits for α = β if 0 < α = β < 1 4. since the system is reversible with involution J : (ξ, η) (η, ξ). There are no closed orbits if α β, since the choice g(ξ, η) = ξ a η b (1 + αξ)(1 + βη), with appropriate a and b implies div(gf) = (α β)ξg.
22 Planar Hamiltonian systems: H : R 2 R (smooth) { ẋ = Hy (x, y), Ḣ = H ẏ = H x (x, y). x ẋ + H y ẏ 0 H(x(t), y(t)) = h Potential system: H(x, y) = y2 2 + U(x) (reversible: y y, t t). where T = ds dh h=h0 (1) (2) (3) y h H(x,y) = h (3) (3) (2) S(h) = area inside y2 + U(x) = h (1) 2 The LotkaVolterra preypredator model is orbitally equivalent to a Hamiltonian system. U(x) x
23 Dissipative perturbations of 2D Hamiltonian systems { ( ẋ = Hy (x, y) + εp(x, y), P(x, y) F(x, y) = ẏ = H x (x, y) + εq(x, y), Q(x, y) ). Let X 0 (t) correspond to the T 0 periodic orbit C 0 at ε = 0 and let Ω 0 = domain bounded by C 0. X Ω C 0 Γ 0 Theorem 5 (PontryaginMelnikov) If Ω 0 div F(X) dx = 0 but T0 0 div F(X0 (t)) dt 0 then there exists an annulus contaning C 0 in which the system has a unique periodic orbit C ε for all sufficiently small ε, such that C ε C 0 as ε 0.
24 Example: Van der Pol equation ẍ + x = εẋ(1 x 2 ) { ẋ = y, ẏ = x + εy(1 x 2 ), For ε = 0, H(x, y) = 1 2 (x2 + y 2 ) and X 0 (t) = with T 0 = 2π. Then C 0 div F dxdy = and T0 ( rsin t rcos t F(x, y) = ), C 0 = {(x, y) : x 2 + y 2 = r 2, r > 0} ( P(x, y) Q(x, y) C 0 Pdy Qdx = ) 2π 0 2π = ( 0 y(1 x 2 ) ). r 2 cos 2 t(1 r 2 sin 2 t)dt = π 4 r2 (4 r 2 ) div 0 F(X0 (t)) dt = (1 0 4sin2 t)dt = 2π A cycle close to r = 2 exists for small ε 0.
25 4. HOMOCLINIC ORBITS Homoclinic orbits to saddles: small Γ 0 big Γ 0 X 0 X 0 Definition 8 The real number σ = λ 1 + λ 2 = (div f)(x 0 ) is called the saddle quantity of X 0. Γ 0 Γ 0 X 0 X 0 σ < 0 σ > 0
26 Singular map: { ẋ = λ1 x ẏ = λ 2 y y Q Regular map: ξ = (η) = η λ 1 λ2 η = Q(ξ) = Aξ + O(2), A > 0. 1 ξ η η 0 1 x Poincaré map: η η = Q( (η)) = Aη λ 1 λ The homoclinic orbit is stable if σ < 0 and is unstable if σ > 0.
27 If σ = λ 1 + λ 2 = 0, then if if (div f)(x0 (t)) dt < 0 the homoclinic orbit is stable; (div f)(x0 (t)) dt > 0 the homoclinic orbit is unstable. Homoclinic orbits to saddlenodes: X 0 X 0 Γ 0 Γ 0 codim 1 codim 2
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