## Homework 1

In the following exercises, we are going to get familiar with the
Roessler system, which is a simple ODE system that exhibits chaos.
You can download the python script templates for Questions 3-5 from
here (right click, "save as").
If you prefer to use some other programming language for these
problems, please download and read the code as the comments
are intended to guide you through the algorithm.

#### Q1.1 \(\quad\) Equilibria of the Roessler flow (ChaosBook.org version14.5.7, exercise 2.8 a)

Find all equilibrium points \( (x_q, y_q,z_q) \) of the Roessler system (2.23). How many are there?1 2 3 4

#### Q1.2 \(\quad\) Equilibria of the Roessler flow (ChaosBook.org version14.5.7, exercise 2.8 b)

Assume that \( b=a \). As we shall see, some surprisingly large, and surprisingly small numbers arise in this system. In order to understand their size, introduce parameters \[ \epsilon = a/c \,,\; D = 1-4\epsilon^2 \,,\; p^{\pm} = (1\pm \sqrt D )/2 \,. \] Express all the equilibria in terms of \( (c,\epsilon,D,p^{\pm}) \), expand to the first order in \( \epsilon \), and evaluate for \( a=b=0.2 \), \(c=5.7\). Let tuple \( (x_q, y_q, z_q) \) denote the equilibrium that is close to the origin. Enter \(x_q\) in the following box with 4 decimal digits. In the case studied \( \epsilon\approx 0.03 \), so these estimates are quite accurate.#### Q1.3 \(\quad\) Runge-Kutta integration

Read**RungeKutta.py**and edit the lines where you see the comment \[ \mbox{#COMPLETE THIS LINE} \] and change 'None' assignments according to the Runge-Kutta method equations (http://goo.gl/TJG7m2 ). Set integration time to 10 by changing the value of \(\mbox{tFinal}\), and set the number of integration points to 1000 by changing value of \(\mbox{Nt}\).

Run \(\mbox{RungeKutta.py}\) to test your integrator, it should numerically integrate the one dimensional harmonic oscillator and plot you the position and velocity as a function of time. Do they look like those of the harmonic oscillator? If they do, then look at your display, where the program should have written the numerical value of the final position. Enter this number to the box below, Please use 4 decimal digits.

#### Q1.4 \(\quad\) Integrating Roessler system

In \( \mbox{Rossler.py} \), complete the \( \mbox{Velocity(ssp, t)}\) function using Roessler ODEs: \[ \begin{aligned} \dot{x} &= -y - z \\ \dot{y} &= x +ay \\ \dot{z} &= b +z(x-c)\, . \end{aligned} \] (Change the lines where you see the \( \mbox{#COMPLETE THIS LINE} \) comment inside the \( \mbox{ Veloctity(ssp, t) }\).)For now, ignore the functions \( \mbox{ Flow(), StabilityMatrix(), JacobianVelocity(), Jacobian() } \) and scroll down to the block which starts with \[ \mbox{ if __name__ == "__main__": } \] For your first simulation, set the initial time (\( \mbox{ tInitial }\)) to \(0\), final time (\( \mbox{ tFinal} \)) to \(100\) and number of data points (\( \mbox{ Nt} \)) to \(10000\). Make sure that \( \mbox{ RK4.py} \) from previous exercise is in your working folder, and lines lines where the solution is calculated reads \[ \begin{aligned} & \mbox{ sspSolution = rk.RK4(velRossler, ssp0, tArray)} \\ & \mbox{ #sspSolution = odeint(velRossler, ssp0, tArray) } \end{aligned} \] These lines determines which integrator to use in this exercise. We are first going to use our own \( \mbox{ RK4} \) integration from the previous example. Run \( \mbox{ Rossler.py} \) to test your program. Do you see the Roessler attractor (http://goo.gl/GE2Lhx )?

Now go back replace your RK4 implementation by \( \mbox{ odeint} \) from \( \mbox{ scipy.integrate} \) by commenting out the line which uses \( \mbox{ rk.RK4()} \) and removing \( \mbox{ #} \) from the beginning of the next line. Re-run the program, make sure that \( \mbox{ odeint} \) yields a similar picture. After making sure that you can produce the Roessler attractor, now set the initial condition for integration to \[ (x_0, y_0, z_0) = (9.269083709793489945, 0.0, 2.581592405683282632) \] by setting \( \mbox{ ssp0} \) and integration time to \[ t_f = 5.881088455554846384 \] by setting \( \mbox{ tFinal} \) and re-run the program. Does the orbit close onto itself? It should. Because the initial condition we have given is on the shortest periodic orbit of the Roessler system. After confirming that you can integrate the periodic orbit correctly, now change the integration time to \[ t_f = 2.0 \] and re-run

**Rossler.py**. The program will print the final position of the flow, enter the first number, namely, the \(x\) coordinate with at least 4 decimal digits to the box below and submit as your answer to this problem.

#### Q1.5 \(\quad\) Poincaré sections and return maps of the Rössler system

This exercise uses the Rossler.py module from the previous exercise, so attempt this question after completing question 4.In this exercise, we are going to look at the Poincaré sections and radial return maps on the Rössler attractor. Poincaré sections we are going to use are planes which include \( z \)-axis and are oriented at different angles in the \(x-y \) plane (just as in Figure 3.2 in ChaosBook.org version14.5.7).

Open \( \mbox{Poincare.py} \) and complete the definition of the rotation matrix (\( \mbox{zRotation(theta)} \)) according to: \[ R_z (\theta) = \left( \begin{array}{ccc} \cos \theta & - \sin \theta & 0 \\ \sin \theta & \cos \theta & 0 \\ 0 & 0 & 1 \end{array}\right) \] Next, complete the definition of \[ \mbox{UPoincare(ssp, sspTemplate=sspTemplate, nTemplate=nTemplate)} \] which returns \( 0 \) if the state space vector \( \mbox{ssp} \) is on the Poincaré section hyperplane defined by \( \mbox{sspTemplate} \) and \( \mbox{nTemplate} \).

A side note on the appearance of arguments of function UPoincare: On the second and third arguments of this function, we assign a 'default value' to the arguments \( \mbox{sspTemplate} \) and \( \mbox{nTemplate} \) which we define right before defining \( \mbox{UPoincare} \). This is a handy structure in python gives us the option of calling \( \mbox{UPoincare} \) with 1, 2, or 3 arguments. If we call it using only one argument \( \mbox{UPoincare(ssp)} \) the function is evaluated using default values for \( \mbox{sspTemplate} \) and \( \mbox{nTemplate} \), if we specify their values in the function call, the default values will be ignored.

Continue reading the code and complete the if statement below which you see the comment. \[ \mbox{#COMPLETE THE LINE ABOVE, HINT: } \] Read the rest of the code and run it! It should produce three figures like the ones at the bottom of this page.

The third figure is the radial return map of points on the Poincaré section. On this figure, read the value where the return map intersects with the \( r_n = r_{n+1} \) line. This is going to be your initial guess for the Newton solver which will find the fixed point of this map. Now go back to the code and uncomment and complete the lines below the comment \[ \begin{aligned} & \mbox{#UNCOMMENT FOLLOWING TWO LINES AFTER READING INITIAL GUESS FOR THE SOLVER} \\ & \mbox{#FROM THE RETURN MAP } \end{aligned} \] Rerun the program, which now should print the value of the fixed point of the return map on the output. Copy this number to the box below as your answer to this problem.

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