1. MA354 1.1 Dynamical Systems MODELING CHANGE

2. Introduction to Dynamical Systems

3. Modeling Change: Dynamical Systems A dynamical system is a changing system. Definition Dynamic: marked by continuous and productive activity or change (Merriam Webster)

4. Modeling Change: Dynamical Systems A dynamical system is a changing system. Definition Dynamic: marked by continuous and productive activity or change (Merriam Webster)

5. Historical Context the term ‘dynamical system’ originated from the field of Newtonian mechanics the evolution rule was given implicitly by a relation that gives the state of the system only a short time into the future. system: x 1, x 2, x 3, … (states as time increases) Implicit relation: x n+1 = f(x n ) Source: Wikipedia 17 th century

6. Dynamical Systems Cont. To determine the state for all future times requires iterating the relation many times— each advancing time a small step. The iteration procedure is referred to as solving the system or integrating the system. Source: Wikipedia

7. Once the system can be solved, given an initial point it is possible to determine all its future points Before the advent of fast computing machines, solving a dynamical system was difficult in practice and could only be accomplished for a small class of dynamical systems. Source: Wikipedia Dynamical Systems Cont.

8. A Classic Dynamical System The double pendulum The model tracks the velocities and positions of the two masses. Source: Wikipedia Evidences rich dynamical behavior, including chaotic behavior for some parameters. Motion described by coupled ODEs. Source: math.uwaterloo

9. The Double Pendulum Chaotic: sensitive dependence upon initial conditions Source: math.uwaterloo These two pendulums start out with slightly different initial velocities.

10. State and State Space A dynamical system is a system that is changing over time. At each moment in time, the system has a state. The state is a list of the variables that describe the system. –Example: Bouncing ball State is the position and the velocity of the ball

11. State and State Space Over time, the system’s state changes. We say that the system moves through state space The state space is an n-dimensional space that includes all possible states. As the system moves through state space, it traces a path called its trajectory, orbit, or numerical solution.

12. Dimension of the State Space n-dimensional As n increases, the system becomes more complicated. Usually, the dimension of state space is greater than the number of spatial variables, as the evolution of a system depends upon more than just position – for example, it may also depend upon velocity.

13. The double pendulum State space: 4 dimensional (What are the static parameters of the system?) What are the 4 changing variables (state variables) that the system depends upon? Must completely describe the system at time t.

14. Mathematical Description of Dynamical Systems

15. Modeling Change: Dynamical Systems From your book: ‘Powerful paradigm’

16. Modeling Change: Dynamical Systems Powerful paradigm: future value = present value + change equivalently: change = future value – current value

17. Modeling Change: Dynamical Systems Powerful paradigm: future value = present value + change equivalently: change = future value – current value

18. Modeling Change: Dynamical Systems Powerful paradigm: future value = present value + change equivalently: change = future value – current value change = current value – previous value

19. Descriptions of Dynamical Systems Discrete versus continuous Implicit versus explicit As n th term of a sequence versus n th difference between terms

20. Descriptions of Dynamical Systems Discrete versus continuous Implicit versus explicit As n th term of a sequence versus n th difference between terms

21. Describing Change (Discrete verses Continuous) Discrete description: Difference Equation Continuous description: Differential Equation

22. Descriptions of Dynamical Systems Discrete versus continuous Implicit versus explicit As n th term of a sequence versus n th difference between terms

23. Implicit Equations Since dynamical systems are defined by defining the change that occurs between events, they are often defined implicitly rather than explicitly. (Example: differential equations are implicit, describing how the function is changing, rather than the function explicitly)

24. Explicit Verses Implicit Equations Implicit Expression: Explicit Expression: To find the nth term, you must calculate the first (n-1) terms. To find the nth term, you simply plug in n and make a single computation. First 10 terms: {1,1,2,3,5,8,13,21,34,55} First 10 terms: {1,1,2,3,5,8,13,21.0,34.0,55.0}

25. Example Given the following sequence, find the explicit and implicit descriptions:

26. More Examples of Implicit Relations I.a k+1 = a k ∙ a k II.a k = 5 III.a k+2 = a k + a k+1 Constant Sequence Fibonacci Sequence

27. Exercise I Generate the first 5 terms of the sequence for rule I given that a 1 =1. I. A(k+1)=A (k)*A (k)

28. Exercise I Generate the first 5 terms of the sequence for rule I given that a 1 =1. I. a k+1 = a k ∙ a k

29. Exercise I Generate the first 3 terms of the sequence for rule I given that a 1 =3. I. a k+1 = a k ∙ a k

30. Role of an ‘Initial Condition’ These are called different trajectories of the dynamical system. An interesting problem in dynamical systems is describing the type of trajectories that are possible with any specific system. Consider the implications of a memoryless system…

31. Exercise II Generate the first 5 terms of the sequence for rule II. II. a k =5

32. Exercise III Generate the first 8 terms of the sequence for rule III given that a 1 =1 and a 2 =1. III. a k+2 = a k + a k+1

33. Exercise III Generate the first 8 terms of the sequence for rule III given that a 1 =1 and a 2 =-1. III. a k+2 = a k + a k+1

34. Descriptions of Dynamical Systems Discrete versus continuous Implicit versus explicit As n th term of a sequence versus n th difference between terms

35. Modeling Change: Dynamical Systems Difference equation: describes change (denoted by ∆) equivalently: change = future value – current value change=future value-present value  = x n+1 – x n

36. … consider a sequence A={a 0, a 1, a 2,…} The set of first differences is  a 0 = a 1 – a 0,  a 1 = a 2 – a 1,  a 2 = a 3 – a 1, … where in particular the nth first difference is  a n+1 = a n+1 – a n.

37. Homework Assignment 1.1 Problems 1-4, 7-8.

38. Homework Assignment 1.1 Problems 1-4, 7-8. Example (3a) By examining the following sequences, write a difference equation to represent the change during the n th interval as a function of the previous term in the sequence.

39. Example 3(a) (3a) By examining the following sequences, write a difference equation to represent the change during the n th interval as a function of the previous term in the sequence.

40. Example 3(a) (3a) By examining the following sequences, write a difference equation to represent the change during the n th interval as a function of the previous term in the sequence. We’re looking for a description of this sequence in terms of the differences between terms:  a n = change = new – old = x n+1 – x n

41. Example 3(a) (3a) By examining the following sequences, write a difference equation to represent the change during the n th interval as a function of the previous term in the sequence. We’re looking for a description of this sequence in terms of the differences between terms:  a n = change = new – old = x n+1 – x n (1)Find implicit relation for a n+1 in terms of a n (2)Solve  an = a n+1 – a n

42. Example 3(a) (3a) By examining the following sequences, write a difference equation to represent the change during the n th interval as a function of the previous term in the sequence. We’re looking for a description of this sequence in terms of the differences between terms:  a n = change = new – old = x n+1 – x n a n+1 = a n +2 (1)Find implicit relation for a n+1 in terms of a n (2)Solve  an = a n+1 – a n  a n = 2

43. More Examples of Implicit Relations I.a k+1 = a k ∙ a k II.a k = 5 III.a k+2 = a k + a k+1 Constant Sequence Fibonacci Sequence Find the difference equation description of each.

44. Related: “Markov Chain” A markov chain is a dynamical system in which the state at time t+1 only depends upon the state of the system at time t. Such a dynamical system is said to be “memory-less”. (This is the ‘Markov property’.) Counter-example: Fibonacci sequence

45. Class Project: Dynamical System in Excel In groups of 3, we’ll create a dynamical system using the “fill down” function in Excel. I.In groups, decide on an interesting dynamical system that is described by a simple rule for the state at time t+1 that only depends upon the current state. (Markov Chain) Describe your system to the class. II.Model your dynamical system in Excel by producing the states of the system in a table where columns describe different states and rows correspond to different times. (You may need to modify your system in order to implement it in Excel.)