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Period-doubling bifurcation

Event in dynamical systems theory

Period-doubling bifurcation

Summary

Event in dynamical systems theory

In dynamical systems theory, a period-doubling bifurcation occurs when a slight change in a system's parameters causes a new periodic trajectory to emerge from an existing periodic trajectory—the new one having double the period of the original. With the doubled period, it takes twice as long (or, in a discrete dynamical system, twice as many iterations) for the numerical values visited by the system to repeat themselves.

A period-halving bifurcation occurs when a system switches to a new behavior with half the period of the original system.

A period-doubling cascade is an infinite sequence of period-doubling bifurcations. Such cascades are one route by which dynamical systems can develop chaos. In hydrodynamics, they are one of the possible routes to turbulence.

Period-halving bifurcations (L) leading to order, followed by period-doubling bifurcations (R) leading to chaos.

Examples

[[Bifurcation diagram]] for the logistic map.

It shows the attractor values, like x_* and x'_*, as a function of the parameter r.]]

Logistic map

The logistic map is :x_{n+1} = r x_n (1 - x_n) where x_n is a function of the (discrete) time n = 0, 1, 2, \ldots. The parameter r is assumed to lie in the interval [0,4], in which case x_n is bounded on [0,1].

For r between 1 and 3, x_n converges to the stable fixed point x_* = (r-1)/r. Then, for r between 3 and 3.44949, x_n converges to a permanent oscillation between two values x_* and x'_* that depend on r. As r grows larger, oscillations between 4 values, then 8, 16, 32, etc. appear. These period doublings culminate at r \approx 3.56995, beyond which more complex regimes appear. As r increases, there are some intervals where most starting values will converge to one or a small number of stable oscillations, such as near r=3.83, where there is a stable period-three solution.

In the interval where the period is 2^n for some positive integer n, not all the points actually have period 2^n. These are single points, rather than intervals. These points are said to be in unstable orbits, since nearby points do not approach the same orbit as them.

Kuramoto–Sivashinsky equation

''L<sup>2</sup>''-norm]] of the solution. For ''ν'' = 0.056, there exists a periodic orbit with period ''T'' ≈ 1.1759. Near ''ν'' ≈ 0.0558, this solution splits into 2 orbits, which further separate as ''ν'' is decreased. Exactly at the transitional value of ''ν'', the new orbit (red-dashed) has double the period of the original. (However, as ''ν'' increases further, the ratio of periods deviates from exactly 2.)

The Kuramoto–Sivashinsky equation is an example of a spatiotemporally continuous dynamical system that exhibits period doubling. It is one of the most well-studied nonlinear partial differential equations, originally introduced as a model of flame front propagation.

The one-dimensional Kuramoto–Sivashinsky equation is : u_t + u u_x + u_{xx} + \nu , u_{xxxx} = 0 A common choice for boundary conditions is spatial periodicity: u(x + 2 \pi, t) = u(x,t).

For large values of \nu, u(x,t) evolves toward steady (time-independent) solutions or simple periodic orbits. As \nu is decreased, the dynamics eventually develops chaos. The transition from order to chaos occurs via a cascade of period-doubling bifurcations, one of which is illustrated in the figure.

Logistic map for a modified Phillips curve

Consider the following logistical map for a modified Phillips curve:

\pi_{t} = f(u_{t}) + b \pi_{t}^e

\pi_{t+1} = \pi_{t}^e + c (\pi_{t} - \pi_{t}^e)

f(u) = \beta_{1} + \beta_{2} e^{-u} ,

b 0, 0 \leq c \leq 1, \frac {df} {du}

where :

  • \pi is the actual inflation
  • \pi^e is the expected inflation,
  • u is the level of unemployment,
  • m - \pi is the money supply growth rate.

Keeping \beta_{1} = -2.5, \ \beta_{2} = 20, \ c = 0.75 and varying b, the system undergoes period-doubling bifurcations and ultimately becomes chaotic.

Experimental observation

Period doubling has been observed in a number of experimental systems. There is also experimental evidence of period-doubling cascades. For example, sequences of 4 period doublings have been observed in the dynamics of convection rolls in water and mercury. Similarly, 4-5 doublings have been observed in certain nonlinear electronic circuits. However, the experimental precision required to detect the ith doubling event in a cascade increases exponentially with i, making it difficult to observe more than 5 doubling events in a cascade.

Notes

References

References

  1. Alligood (1996) et al., p. 532
  2. (2017). "Modern Classical Physics: Optics, Fluids, Plasmas, Elasticity, Relativity, and Statistical Physics". Princeton University Press.
  3. Strogatz (2015), pp. 360–373
  4. (2015). "An in-depth numerical study of the two-dimensional Kuramoto–Sivashinsky equation". Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.
  5. (1991). "Predicting chaos for infinite dimensional dynamical systems: the Kuramoto-Sivashinsky equation, a case study.". Proceedings of the National Academy of Sciences.
  6. (1991). "The route to chaos for the Kuramoto-Sivashinsky equation". Theoretical and Computational Fluid Dynamics.
  7. see Strogatz (2015) for a review
  8. (1981). "Transition to Chaotic Behavior via a Reproducible Sequence of Period-Doubling Bifurcations". Physical Review Letters.
  9. (1982). "Period doubling cascade in mercury, a quantitative measurement". Journal de Physique Lettres.
  10. (1981). "Period Doubling and Chaotic Behavior in a Driven Anharmonic Oscillator". Physical Review Letters.
  11. (1982). "Evidence for Universal Chaotic Behavior of a Driven Nonlinear Oscillator". Physical Review Letters.
  12. (1982). "Hopping Mechanism Generating1fNoise in Nonlinear Systems". Physical Review Letters.
  13. Strogatz (2015), pp. 360–373
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