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10.2 Random Walks. Random Walk A random walk refers to the apparently random motion of an entity. This is often the best model of a physical process (Brownian.

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Presentation on theme: "10.2 Random Walks. Random Walk A random walk refers to the apparently random motion of an entity. This is often the best model of a physical process (Brownian."— Presentation transcript:

1 10.2 Random Walks

2 Random Walk A random walk refers to the apparently random motion of an entity. This is often the best model of a physical process (Brownian motion) or financial index (stock price), etc.

3 Aside: Fooled By Randomness HAMLET: Do you see yonder cloud that's almost in the shape of a camel? POLONIUS: By the mass, and 'tis like a camel, indeed. HAMLET: Methinks it is like a weasel. POLONIUS: It is backed like a weasel. HAMLET: Or like a whale. POLONIUS: Very like a whale. Hamlet Act 2, Scene 2

4 1973 2004 Aside: Fooled By Randomness

5 What’s the Trend?

6

7 Simulating Motion: Cellular Automata If all we have to work with is a grid of cells (spreadsheet), how can we simulate a random walk? Moving a value from one cell to an adjacent cell is simulated by changing the contents of the cells over time: time t time t +1

8 The Wave

9 Aside: The Wave/Particle Duality We tend to think of “true” motion as movement of an object from one location to another, and the wave phenomenon as an illusion of motion. But at the most fundamental level, energy and matter behave like both a particle (object) and a wave….

10 Aside: The Wave/Particle Duality Double-slit experiment (Young 1801): Light must be a wave, because interference produces more than two bands on screen. Photoelectric effect (Thomson 1899): Light must consist of particles, because light waves knock electrons out of a metal plate.

11 Cellular Automata A cellular automaton (plural automata) is a dynamical model discrete in space, time, and state (possible values, typically just 0 and 1). CA has a grid of cells, and a set of transition rules describing what happens to a cell based on its own state and the state of its neighbors. Simplest CA are one-dimensional….

12 1D Cellular Automata Sample rule: Look at a cell and its left and right neighbors. Change the cell according to the following table:

13 ExCellular Automata Each row is the state of the CA at a particular time step. First row has random values: = IF(RAND()>0.5, 1, 0) Subsequent rows have rule: =IF( OR (AND( A1=1,B1=1,C1=1), AND (A1=1,B1=0,C1=0), AND (A1=0,B1=0,C1=0)), 0, 1)

14 ExCellular Automata Drag second row, second column rightward to next-to-last Keep first and last columns (boundary conditions) constant Drag second row down 60 or 70 rows Use Conditional Formatting / Color Scales to color cells based on values Zoom out to view whole display Hit F9 key to restart with new initial conditions Experiment with other rules:

15 Cellular Automata in Nature

16 2D Cellular Automata

17 Cellular Automata as the Basis for Life, the Universe, and Everything

18 Algorithm for a Random Walk, With Diagonal Steps: seed random number generator let x, x 0, y, and y 0 be 0 let n be the number of steps let list be a list containing the origin do the following n times: let rand be a random 0 or 1 if rand is 0 increment x by 1 else decrement x by 1 do the same for y append point ( x, y ) onto list create and display graphics of walk report distance between first and last points,

19 Animation Tricky in Excel, but fortunately a download is available here.here

20 Average Distance Traveled Average distance traveled increases (but not monotonically) with time (# of steps n ):


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