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Solving Partial Differential Equations using the Fourier Transform: A Step-by-Step Guide

Course Description:

This course is designed to provide a comprehensive understanding of how the Fourier Transform can be used as a powerful tool to solve Partial Differential Equations (PDE). The course is divided into three parts, each building on the previous one, and includes bonus sections on the mathematical derivation of the Heisenberg Uncertainty Principle.

Part 1: In this part, we will start with the basics of the Fourier series and derive the Fourier Transform and its inverse. We will then apply these concepts to solve PDE's using the Fourier Transform. Prerequisites for this section are Calculus and Multivariable Calculus, with a focus on topics related to derivatives, integrals, gradient, Laplacian, and spherical coordinates.

Part 2: This section introduces the heat equation and the Laplace equation in Cartesian and polar coordinates. We will solve exercises with different boundary conditions using the Separation of Variables method. This section is self-contained and independent of the first one, but prior knowledge of ODEs is recommended.

Part 3: This section is dedicated to the Diffusion/Heat equation, where we will derive the equation from physics principles and solve it rigorously. Bonus sections are included on the mathematical derivation of the Heisenberg Uncertainty Principle.

Course Benefits:

  • Gain a thorough understanding of the Fourier Transform and its application to solving PDE's.

  • Learn how to apply Separation of Variables method to solve exercises with different boundary conditions.

  • Gain insight into the Diffusion/Heat equation and how it can be solved.

  • Bonus sections on the Heisenberg Uncertainty Principle provide a deeper understanding of the mathematical principles behind quantum mechanics.

Prerequisites:

  • Calculus and Multivariable Calculus with a focus on derivatives, integrals, gradient, Laplacian, and spherical coordinates.

  • Prior knowledge of ODEs is recommended.

  • Some knowledge of Complex Calculus and residues may be useful.

Who is this course for?

  • Students and professionals with a background in Mathematics or Physics looking to gain a deeper understanding of solving PDE's using the Fourier Transform.

  • Those interested in the mathematical principles behind quantum mechanics and the Heisenberg Uncertainty Principle.

Bạn sẽ học được gì

How to use the Fourier Trasforms to tackle the problem of solving PDE's

Fourier Transforms in one and multiple dimensions

Method of separation of variables to solve the Heat equation (with exercises)

Method of separation of variables to solve the Laplace equation in cartesian and polar coordinates (with exercises)

How to apply the Fourier Transform to solve 2nd order ODE's as well

concept of streamlines

Mathematical tricks

How to derive Heisenberg Uncertainty Principle using concepts of Probability Theory

Yêu cầu

  • Calculus (especially: derivatives, integrals)
  • Multivariable Calculus (especially: the Jacobian, the Laplacian, etc.)
  • Complex Calculus (basics of Fourier series and residues could help)
  • Some notions of probability theory (distributions, mean, variance)
  • Complex numbers

Nội dung khoá học

19 sections

Fourier Transform and its inverse

6 lectures
Fourier series
03:09
Fourier Transforms
06:13
How to interpret improper integrals of sinusoids
18:53
Dirac delta
09:47
Multiple Fourier Transforms
08:41
Why the Dirac delta helps derive the Inverse Fourier Transform
13:08

Solution of a PDE equation

5 lectures
Gradient and Laplacian: quick summary
00:55
Example of pde
03:25
Solution to the pde part 1
09:49
Solution to the pde part 2
08:57
Solution to the pde part 3
06:48

Some more physics behind the pde

2 lectures
Physics behind the equation part 1
10:25
Physics behind the equation part 2
10:35

Solving the Diffusion/Heat equation by Fourier Tranform

8 lectures
Setup of the diffusion problem
03:38
Integral equation satisfied by the function f(x,t)
11:03
Diffusion equation
16:59
Some possible boundary conditions of the diffusion equation
09:34
Solution of the diffusion equation part 1
19:10
Solution of the diffusion equation part 2
18:44
Solution of the diffusion equation part 3
10:25
Solution of the diffusion equation part 4
15:03

2nd order ODE solved via Fourier Transform

1 lectures
2nd order non-homogeneous ODE solved via Fourier Transform
37:41

PDE solved with the method of characteristics

1 lectures
Non linear first order PDE solved with the method of characteristics
08:02

Heat equation solution via Separation of Variables

3 lectures
Separation of variables to solve the heat equation (part 1)
21:59
Separation of variables to solve the heat equation (part 2)
07:29
Separation of variables to solve the heat equation (part 3)
26:41

Laplace Equation solved via the method of Separation of Variables

6 lectures
Laplace Equation in Cartesian Coordinates (exercise)
28:32
Laplace Equation in Polar coordinates (exercise 1)
23:13
Laplace Equation in Polar coordinates (exercise 2)
17:57
Laplace Equation in Polar coordinates (exercise 3)
15:01
Laplace Equation in Polar coordinates (exercise 4)
16:27
Concept of streamlines (with exercise)
15:37

Nonhomogeneous Heat Equation

3 lectures
Nonhomogeneous Heat Equation: Exercise 1
25:00
Nonhomogeneous Heat Equation: Exercise 2
08:01
Nonhomogeneous Heat Equation: Exercise 3
29:39

Wave Equation (Exercises)

4 lectures
Nonhomogeneous Wave Equation (Exercise 1)
28:55
Nonhomogeneous Wave Equation: D'Alambert formula
47:21
Solving a wave equation using D'Alambert formula (exercise)
03:27
Energy conservation law for the wave equation
02:57

Bi-dimensional problems (heat and wave equation)

3 lectures
Bi-dimensional heat equation: exercise 1
32:00
Bi-dimensional heat equation: exercise 2
09:57
Bi-dimensional wave equation: exercise 1
16:14

Derivation of the Navier-Stokes equations and their solution in a 2D case

2 lectures
Mathematical derivation of Navier Stokes equations part 1
08:48
Mathematical derivation of Navier Stokes equations part 2
15:16

How Einstein mastered Navier-Stokes equations in his PhD dissertation

6 lectures
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 1
15:07
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 2
19:41
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 3
12:39
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 4
21:08
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 5
26:25
How Einstein mastered Navier-Stokes equations in hid PhD dissertation Part 6
30:27

Stokes law obtained from Navier-Stokes equations

2 lectures
derivation of Stokes law from Navier Stokes part 1
51:12
derivation of Stokes law from Navier Stokes part 2
37:01

Appendix on PDE's

1 lectures
Derivation of the incompressible fluid equation
11:08

Bonus section: Introduction to the Heisenberg Uncertainty Principle

5 lectures
Mathematical summary of how to prove the uncertainty principle
16:54
Introduction to the short course on the Heisenberg Uncertainty Principle
04:47
Probability that a particle exists at a certain time
18:10
Probability that a particle has a certain_energy
14:52
Uncertainty in the localization in time and in the energy of the particle
08:34

Bonus Section: Uncertainty Principle derivation

3 lectures
Derivation of the uncertainty principle part 1
05:24
Derivation of the uncertainty principle part 2
10:40
Derivation of the uncertainty principle part 3
13:55

Bonus Section: Consequences of the Uncertainty principle

2 lectures
Probability that particles come into existence with high energy
19:08
Distribution for which we have the minimum uncertainty
13:36

Appendix

1 lectures
Derivation of some formulas used in previous lectures
12:12

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