Ordinary Differential Equations I
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1 Ordinary Differential Equations I CS 205A: Mathematical Methods for Robotics, Vision, and Graphics Justin Solomon CS 205A: Mathematical Methods Ordinary Differential Equations I 1 / 27
2 Theme of Last Three Weeks The unknown is an entire function f. CS 205A: Mathematical Methods Ordinary Differential Equations I 2 / 27
3 New Twist So far: f (or its derivative/integral) known at isolated points CS 205A: Mathematical Methods Ordinary Differential Equations I 3 / 27
4 New Twist So far: f (or its derivative/integral) known at isolated points Instead: Optimize properties of f CS 205A: Mathematical Methods Ordinary Differential Equations I 3 / 27
5 Example Problems Approximate f 0 with f but make it smoother (or sharper!) CS 205A: Mathematical Methods Ordinary Differential Equations I 4 / 27
6 Example Problems Approximate f 0 with f but make it smoother (or sharper!) Simulate a particle system obeying a physical law CS 205A: Mathematical Methods Ordinary Differential Equations I 4 / 27
7 Example Problems Approximate f 0 with f but make it smoother (or sharper!) Simulate a particle system obeying a physical law Approximate f 0 with f but transfer properties of g 0 CS 205A: Mathematical Methods Ordinary Differential Equations I 4 / 27
8 Today: Initial Value Problems Find f(t) : R R n Satisfying F [t, f(t), f (t), f (t),..., f (k) (t)] = 0 Given f(0), f (0), f (0),..., f (k 1) (0) CS 205A: Mathematical Methods Ordinary Differential Equations I 5 / 27
9 Most Famous Example F = ma Newton s second law CS 205A: Mathematical Methods Ordinary Differential Equations I 6 / 27
10 Most Famous Example F = ma Newton s second law n particles = simulation in R 3n CS 205A: Mathematical Methods Ordinary Differential Equations I 6 / 27
11 Protein Folding CS 205A: Mathematical Methods Ordinary Differential Equations I 7 / 27
12 Gradient Descent min x E( x) = d x dt = E( x) CS 205A: Mathematical Methods Ordinary Differential Equations I 8 / 27
13 Crowd Simulation CS 205A: Mathematical Methods Ordinary Differential Equations I 9 / 27
14 Examples of ODEs y = 1 + cos t: solved by integrating both sides CS 205A: Mathematical Methods Ordinary Differential Equations I 10 / 27
15 Examples of ODEs y = 1 + cos t: solved by integrating both sides y = ay: linear in y CS 205A: Mathematical Methods Ordinary Differential Equations I 10 / 27
16 Examples of ODEs y = 1 + cos t: solved by integrating both sides y = ay: linear in y y = ay + e t : time and position-dependent CS 205A: Mathematical Methods Ordinary Differential Equations I 10 / 27
17 Examples of ODEs y = 1 + cos t: solved by integrating both sides y = ay: linear in y y = ay + e t : time and position-dependent y + 3y y = t: multiple derivatives of y CS 205A: Mathematical Methods Ordinary Differential Equations I 10 / 27
18 Examples of ODEs y = 1 + cos t: solved by integrating both sides y = ay: linear in y y = ay + e t : time and position-dependent y + 3y y = t: multiple derivatives of y y sin y = e ty : nonlinear in y and t. CS 205A: Mathematical Methods Ordinary Differential Equations I 10 / 27
19 Reasonable Assumption Explicit ODE An ODE is explicit if can be written in the form f (k) (t) = F [t, f(t), f (t), f (t),..., f (k 1) (t)]. CS 205A: Mathematical Methods Ordinary Differential Equations I 11 / 27
20 Reasonable Assumption Explicit ODE An ODE is explicit if can be written in the form f (k) (t) = F [t, f(t), f (t), f (t),..., f (k 1) (t)]. Otherwise need to do root-finding! CS 205A: Mathematical Methods Ordinary Differential Equations I 11 / 27
21 Reduction to First Order d dt g 1 (t) g 2 (t). g k 1 (t) g k (t) = g 2 (t) g 3 (t). g k (t) F [t, g 1 (t), g 2 (t),..., g k 1 (t)] CS 205A: Mathematical Methods Ordinary Differential Equations I 12 / 27
22 Example y = 3y 2y + y CS 205A: Mathematical Methods Ordinary Differential Equations I 13 / 27
23 Example y = 3y 2y + y d dt y z w = y z w CS 205A: Mathematical Methods Ordinary Differential Equations I 13 / 27
24 Autonomous ODE y = F [ y] No dependence of F on t CS 205A: Mathematical Methods Ordinary Differential Equations I 14 / 27
25 Autonomous ODE y = F [ y] No dependence of F on t g (t) = ( f (t) ḡ (t) ) = ( F [f(t), ḡ(t)] 1 ) CS 205A: Mathematical Methods Ordinary Differential Equations I 14 / 27
26 Two Visualizations Slope field Phase space CS 205A: Mathematical Methods Ordinary Differential Equations I 15 / 27
27 Existence and Uniqueness dy dt = 2y/t Two cases: y(0) = 0, y(0) 0 CS 205A: Mathematical Methods Ordinary Differential Equations I 16 / 27
28 Existence and Uniqueness Theorem: Local existence and uniqueness Suppose F is continuous and Lipschitz, that is, F [ y] F [ x] 2 L y x 2 for some L. Then, the ODE f (t) = F [f(t)] admits exactly one solution for all t 0 regardless of initial conditions. CS 205A: Mathematical Methods Ordinary Differential Equations I 17 / 27
29 Linearization of 1D ODEs y = F [y] CS 205A: Mathematical Methods Ordinary Differential Equations I 18 / 27
30 Linearization of 1D ODEs y = F [y] y = ay + b CS 205A: Mathematical Methods Ordinary Differential Equations I 18 / 27
31 Linearization of 1D ODEs y = F [y] y = ay + b ȳ = aȳ CS 205A: Mathematical Methods Ordinary Differential Equations I 18 / 27
32 Model Equation y = ay CS 205A: Mathematical Methods Ordinary Differential Equations I 19 / 27
33 Model Equation y = ay = y(t) = Ce at CS 205A: Mathematical Methods Ordinary Differential Equations I 19 / 27
34 Three Cases y = ay, y(t) = Ce at 1. a = 0: Stable CS 205A: Mathematical Methods Ordinary Differential Equations I 20 / 27
35 Three Cases y = ay, y(t) = Ce at 1. a = 0: Stable 2. a < 0: Stable; solutions get closer CS 205A: Mathematical Methods Ordinary Differential Equations I 20 / 27
36 Three Cases y = ay, y(t) = Ce at 1. a = 0: Stable 2. a < 0: Stable; solutions get closer 3. a > 0: Unstable; mistakes in initial data amplified CS 205A: Mathematical Methods Ordinary Differential Equations I 20 / 27
37 Multidimensional Case y = A y, A y i = λ i y i y(0) = i c i y i CS 205A: Mathematical Methods Ordinary Differential Equations I 21 / 27
38 Multidimensional Case y = A y, A y i = λ i y i y(0) = i c i y i = y(t) = i c i e λ it y i CS 205A: Mathematical Methods Ordinary Differential Equations I 21 / 27
39 Multidimensional Case y = A y, A y i = λ i y i y(0) = i c i y i = y(t) = i c i e λ it y i Stability depends on max i λ i. CS 205A: Mathematical Methods Ordinary Differential Equations I 21 / 27
40 Integration Strategies Given y k at time t k, generate y k+1 assuming y = F [ y]. CS 205A: Mathematical Methods Ordinary Differential Equations I 22 / 27
41 Forward Euler y k+1 = y k + hf [ y k ] Explicit method O(h 2 ) localized truncation error O(h) global truncation error; first order accurate CS 205A: Mathematical Methods Ordinary Differential Equations I 23 / 27
42 Model Equation y = ay y k+1 = (1 + ah)y k For a < 0, stable when h < 2 a. CS 205A: Mathematical Methods Ordinary Differential Equations I 24 / 27
43 Backward Euler y k+1 = y k + hf [ y k+1 ] Implicit method O(h 2 ) localized truncation error O(h) global truncation error; first order accurate CS 205A: Mathematical Methods Ordinary Differential Equations I 25 / 27
44 Model Equation y = ay y k+1 = 1 1 ah y k Unconditionally stable! CS 205A: Mathematical Methods Ordinary Differential Equations I 26 / 27
45 Model Equation y = ay y k+1 = 1 1 ah y k Unconditionally stable! But this has nothing to do with accuracy. CS 205A: Mathematical Methods Ordinary Differential Equations I 26 / 27
46 Model Equation y = ay y k+1 = 1 1 ah y k Unconditionally stable! But this has nothing to do with accuracy. Good for stiff equations. CS 205A: Mathematical Methods Ordinary Differential Equations I 26 / 27
47 Forward and Backward Euler on Linear ODE y = A y Forward Euler: y k+1 = (I + ha) y k Backward Euler: y k+1 = (I ha) 1 y k Next CS 205A: Mathematical Methods Ordinary Differential Equations I 27 / 27
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