Math 2.0

Dynamical systems and ergodic theory Definition

Chain recurrence

Builds on Metric spaceContinuous mapNon-wandering set

Definition

Let (X,d)(X, d) be a metric space and let f ⁣:X→Xf \colon X \to X be a continuous map. For ε>0\varepsilon > 0 and x,y∈Xx, y \in X, an ε\varepsilon-chain from xx to yy is a finite sequence x=x0,x1,…,xn=yx = x_0, x_1, \ldots, x_n = y with n≥1n \ge 1 and d(f(xi−1),xi)<εd(f(x_{i-1}), x_i) < \varepsilon for i=1,…,ni = 1, \ldots, n. A point x∈Xx \in X is chain recurrent if for every ε>0\varepsilon > 0 there is an ε\varepsilon-chain from xx to xx. The chain recurrent set ℛ(f)\mathcal{R}(f) is the set of chain recurrent points.

Remarks

For a continuous flow φt\varphi_t, an (ε,T)(\varepsilon, T)-chain from xx to yy is a sequence x=x0,…,xn=yx = x_0, \ldots, x_n = y with times t1,…,tn≥Tt_1, \ldots, t_n \ge T. It must satisfy d(φti(xi−1),xi)<εd(\varphi_{t_i}(x_{i-1}), x_i) < \varepsilon for each ii. A point xx is chain recurrent for the flow if such chains from xx to xx exist for all ε>0\varepsilon > 0 and T>0T > 0. The set ℛ(f)\mathcal{R}(f) is closed and contains the non-wandering set Ω(f)\Omega(f). Example: for the identity map, x0=x1=xx_0 = x_1 = x is an ε\varepsilon-chain from xx to xx for every ε\varepsilon, so every point is chain recurrent. Non-example: let f(x)=x/2f(x) = x/2 on [0,1][0, 1] and x>0x > 0, 0<ε<x/20 < \varepsilon < x/2. If xi−1≤xx_{i-1} \le x, then xi<xi−1/2+ε<xx_i < x_{i-1}/2 + \varepsilon < x, so by induction every xix_i with i≥1i \ge 1 is less than xx; no ε\varepsilon-chain returns to xx. For this map ℛ(f)={0}\mathcal{R}(f) = \set{0}.

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  1. Continuous map concept
  2. Metric space concept
  3. Non-wandering set concept
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Further reading

  1. Web https://en.wikipedia.org/wiki/Conley%27s_fundamental_theorem_of_dynamical_systems
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Tag2H2BRQD0YX
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Kinddefinition
WritingW0 stub
MSC37B20, 37B35
DefinesChain recurrence
UsesMetric space, Continuous map, Non-wandering set

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