- (Problem 3.1.3 in Strogatz) Consider the following non-dimensional equation
x = r + x ln(1 + x)
- Sketch all qualitatively different phase portraits remember to label fixed points, indicate their stability,and indicate the flow direction on the horizontal axis. [Note: phase portrait is a generic term for what Ive been calling the phase line in class].
- Show that a saddle-node bifurcation occurs at some critical value of r.
- Sketch the bifurcation diagram.
- The following non-dimensional equation models population growth
N = RN N(1 N)2 (1)
- Draw a bifurcation diagram for this equation as R
- At each bifurcation, the systems qualitative dynamics change, so that the phase portrait differs from oneside of the bifurcation to the other. Identify regions with similar dynamics and sketch a phase portrait for each region. [Note: phase portrait is a generic term for what Ive been calling the phase line in class].
- Pick one region and sketch several trajectories, N(t), for several different initial conditions. On your plot of N(t), indicate the fixed points.
- Use Matlab to check your answer to part c. (You dont need to turn this in but its a good idea to useMatlab to check your work when you can).
- Consider the equation
x = x1/3 (2)
- a) Using Matlab, perform the following two simulations:
- Simulate this equation, running time backwards from t = 1.52 to t = 0, starting from x(t = 1.52) = 1. ii. Simulate this equation, running time forwards from t = 0 to t = 1.52, starting from x(t = 0) = 0.
- If youve done the simulations correctly (or at least in the same way that I did), then the trajectoriescross. In class, I claimed that trajectories cannot cross. Explain this apparent contradiction.
- Calculate the exact solution for the simulation in part i. Is this solution unique? How does it differ fromthe computed solution? Explain the source of any differences.
- Calculate the exact solution for the simulation in part ii. Is this solution unique? How does it differ fromthe computed solution? Explain the source of any differences.
- In class (and on Homework 1), weve been discussing the non-dimensional form of an equation modeling the production of a protein:
- Suppose = 4. Linearize about each fixed point to determine stability. Which one is the most stable (i.e., where do small perturbations decay the fastest)?
- For how big an initial perturbation is the linear approximation good? Use Matlab to explore this. To doso, youll need to define what a good approximation is (e.g., error less than 1%, 0.1%), and then use Matlab to calculate the difference between the exact solution, generated by Matlab, and the linear approximation.
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