Solition problems with Matlab (12 PDE with 8 variables))

In summary, the speaker is a master student studying high energy physics at USM in Malaysia. They are unsure whether their problem should be placed on a differential forum or a high energy physics forum. Their current study focuses on monopole instanton solutions in a static form using the Lagrangian to generate 12 equations of motion with 8 variables. They are using Matlab with the Optimization toolbox and the trusted reflective region algorithm, as well as the finite difference method, but have not been able to achieve convergence. They have tried to reproduce a paper by Jutta Kunz on monopole solutions with 6 equations and have successfully obtained the Higgs field. The speaker's professor has indicated that their system is overdetermined, with more equations
  • #1
tiantsai
6
0
Hi, I am a master student comes from USM in Malaysia. I don't know my problem should placed on differential forum or high energy physics forum. Anywhere, My current study is high energy physics subject and my main study is focus on monopole instanton solution in static form which did not include time, i using the Lagrangian to generate out the 12 set equations of motion with 8 variables, the software that i use is Matlab with Optimization toolbox- the algorithm that i use inside the package is trusted reflective region and the numerical method that i used is finite difference method. However, it did not converge. I have tried to reproduce the Jutta Kunz paper-monopoles solution with 6 set of partial differential equation with 6 variables and its work well and i also obtain the Higgs field [itex]\Phi(r,\theta)[/itex] of monopole successfully. The variables that in the set of equations of motion is in r and [itex]\theta[/itex] form which means as A(r,[itex]\theta[/itex]). So any suggestion for using Matlab to solve the 12 set equations of motion (PDE form) with 8 variables.
 
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  • #2
I am very intriqued how you managed to "generate" more equations than unknown functions.
 
  • #3
My professor say its is a overdetermined system with because the number of partial equations is more than the variables and suppose it can give us a fine numerical solution for each variables but my program still cannot converge...
 
  • #4
Well i am using the ansatz which include gauge and Higgs variable that in the form of spherical coordinate (also include internal and external space), so putting inside the Lagrangian and its generate out 12 equations of motion with 8 variables.
 
  • #5
what do you mean by "variables"?
 

1. What is Matlab and how is it used to solve PDE problems?

Matlab is a programming language and numerical computing environment that is commonly used in scientific and engineering applications. It has built-in functions and tools specifically designed for solving partial differential equations (PDEs), making it a powerful tool for tackling complex PDE problems. Matlab uses numerical methods and algorithms to approximate solutions to PDEs, allowing researchers and scientists to model and simulate various physical phenomena.

2. What is a PDE and how is it different from an ODE?

A PDE (partial differential equation) is a mathematical equation that involves multiple independent variables and their partial derivatives. It is commonly used to describe physical phenomena, such as heat transfer, fluid dynamics, and electromagnetic fields. In contrast, an ODE (ordinary differential equation) only involves one independent variable and its derivatives. PDEs are more complex and require different techniques and methods for solving compared to ODEs.

3. Can Matlab handle PDEs with multiple variables?

Yes, Matlab can handle PDEs with multiple variables. In fact, it is one of the most common uses of Matlab in scientific and engineering research. Matlab has built-in functions and tools that allow users to specify and solve PDEs with any number of independent variables. These functions use numerical methods, such as finite difference, finite element, and spectral methods, to approximate solutions to the PDEs.

4. What is the process for solving PDEs with Matlab?

The process for solving PDEs with Matlab typically involves the following steps:

  1. Define the PDE problem, including the dependent and independent variables, boundary conditions, and initial conditions.
  2. Use Matlab's built-in functions to set up the PDE problem and specify the numerical method to be used for solving.
  3. Solve the PDE problem using the specified numerical method, which will provide an approximate solution.
  4. Analyze and refine the solution, if necessary, to improve accuracy.

5. What are some common challenges when solving PDEs with Matlab?

Some common challenges when solving PDEs with Matlab include:

  • Choosing the appropriate numerical method for the specific PDE problem
  • Ensuring the accuracy and stability of the solution
  • Dealing with complex boundary conditions and/or initial conditions
  • Handling large and complex PDE systems with multiple equations and variables
  • Interpreting and analyzing the results of the solution

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