Time-Dependent Differential Equations: Numerical Methods and Stability Analysis, Lecture notes of Differential Equations

Numerical methods for solving differential equations, including ordinary differential equations and partial differential equations. It covers first and second order ODEs, as well as the heat equation. The Euler method and finite-difference schemes are introduced as numerical methods. The Lax equivalence theorem is also briefly discussed. examples and questions related to accuracy, stability, and efficiency of the methods.

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2021/2022

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chapter 7 :time-dependentdi↵erential equations
ordinary di↵erential equations
Let x(t) be the position of a particle moving on the x-axis at time t.
1st order ODE
dx
dt =f(x):velocityisafunctionofposition
x(0) : initial position
The problem is to find the position x(t)fort>0.
ex
1. dx
dt =x, x(0) = 1 )x(t)=et
2. dx
dt =x2,x(0) = 1 )x(t)= 1
1t
3. dx
dt =sinx, x(0) = 1 )x(t)=? 26
Thurs
4/18
The simplest numerical method is Euler’s method.
choose t:timestep
define wn: numerical solution at time tn=nt
wn+1 wn
t=f(wn))wn+1 =wn+tf(wn)
given w0, compute w1,w
2,...
questions :accuracy,stability,efficiency
2nd order ODE
d2x
dt2=f(x) : acceleration is a function of position (Newton’s equation)
x(0) ,x
0(0) : initial position , velocity
wn+1 2wn+wn1
(t)2=f(wn))wn+1 =2wnwn1+(t)2f(wn)
given w0and w1, compute w2,w
3,...
pf3
pf4

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chapter 7 : time-dependent di↵erential equations

ordinary di↵erential equations

Let x(t) be the position of a particle moving on the x-axis at time t.

1st order ODE dx dt =^ f^ (x)^ :^ velocity is a function of position x(0) : initial position

The problem is to find the position x(t) for t > 0. ex

  1. dxdt = x , x(0) = 1 ) x(t) = e t
  2. dxdt = x 2 , x(0) = 1 ) x(t) = (^1) ^1 t
  3. dxdt = sin x , x(0) = 1 ) x(t) =? (^26) Thurs The simplest numerical method is Euler’s method.^4 /^18

choose t : time step

define w (^) n : numerical solution at time t (^) n = nt w (^) n+1 w (^) n t =^ f^ (w^ n^ )^ )^ w^ n+1^ =^ w^ n^ +^ tf^ (w^ n^ )

given w 0 , compute w 1 , w 2 ,...

questions : accuracy , stability , eciency

2nd order ODE

d 2 x dt 2 =^ f^ (x)^ :^ acceleration is a function of position (Newton’s equation) x(0) , x 0 (0) : initial position , velocity w (^) n+1 2 w (^) n + w (^) n 1 (t) 2 =^ f^ (w^ n^ )^ )^ w^ n+1^ = 2w^ n^ ^ w^ n^1 + (t)^

(^2) f (w (^) n )

given w 0 and w 1 , compute w 2 , w 3 ,...

partial di↵erential equations ex : heat equation u(x, t) : temperature of a metal rod at position x and time t @u @t =^ 

@ 2 u @x 2 ,^ ^ : coecient of thermal expansion initial condition : u(x, 0) = f (x) , boundary conditions : u(0, t) = u(1, t) = 0 The simplest numerical method is a finite-di↵erence scheme. choose x : space step , t : time step define w nj : numerical solution at position x (^) j = jx and time t (^) n = nt w (^) jn +1 w (^) jn t =^ 

w nj+1 2 w (^) jn + w (^) jn 1 (x) 2 )^ w^

n j +1= w (^) jn + t (x) 2 (w^ jn+1 ^2 w^ nj +^ w^ nj 1 ) case 1 :  = 1 , x = 0. 05 , t = 0. 0013

(^00) 0.5 1

1 t=

(^00) 0.5 1

1 1 time step

(^00) 0.5 1

1 25 time steps

(^00) 0.5 1

1 50 time steps

case 2 :  = 1 , x = 0. 05 , t = 0. 0012

(^00) 0.5 1

1 t=

(^00) 0.5 1

1 1 time step

(^00) 0.5 1

1 25 time steps

(^00) 0.5 1

1 50 time steps

explanation : the method is stable , (^) (xt) 2  (^12 ) Tues Lax equivalence theorem (Peter Lax)^4 /^23 Given a well-posed initial/boundary value problem and a consistent finite-di↵erence scheme, stability is necessary and sucient for convergence.

ex : wave equation

u(x, t) : displacement of a string at position x and time t

@ 2 u @t 2 =^ c^

2 @^2 u @x 2 c : wave speed

w (^) in +1 2 w (^) in + w ni (t) 2 =^ c^

2 w^ in+1 ^2 w^ ni +^ w^ ni 1 (x) 2

) w n i +1= 2w ni w n i ^1 + c xt

! 2 (w ni+1 2 w (^) in + w (^) in 1 ) , stable ,

ct x

^1