Incorrect boundary conditions

Oct 13, 2025 by orovajewels.com 15 views

Introduction

Solving partial differential equations (PDEs) is a crucial task in various fields of science and engineering. Mathematica is a powerful computational software that provides an efficient way to solve PDEs. However, when dealing with very complicated coupled second-order PDEs, the kernel may quit unexpectedly or produce a solution that is zero everywhere. In this article, we will discuss the possible reasons behind this issue and provide some strategies to overcome it.

Understanding the Problem

The problem we are trying to solve is Schrodinger's equation, a fundamental equation in quantum mechanics. It is a coupled second-order PDE that describes the time-evolution of a quantum system. The equation is given by:

iℏ(∂ψ/∂t) = -ℏ²/2m (∂²ψ/∂x² + ∂²ψ/∂y²) + V(x,y)ψ

where ψ is the wave function, i is the imaginary unit, ℏ is the reduced Planck constant, m is the mass of the particle, V(x,y) is the potential energy, and x and y are the spatial coordinates.

Mathematica Code

The Mathematica code to solve this equation is given by:

(* Define the potential energy *)
V[x_, y_] = x^2 + y^2;
(* Define the wave function *)
ψ[x_, y_, t_] = Exp[I (kx x + ky y - ω t)];
(* Define the parameters *)
kx = 1;
ky = 1;
ω = 1;
m = 1;
ℏ = 1;
(* Define the PDE *)
pde = I ℏ (D[ψ[x, y, t], t] == -ℏ^2/2 m (D[ψ[x, y, t], {x, 2}] + D[ψ[x, y, t], {y, 2}]) + V[x, y] ψ[x, y, t]);
(* Solve the PDE *)
sol = NDSolve[pde, ψ[x, y, t], {x, -10, 10}, {y, -10, 10}, {t, 0, 10}];

Kernel Quitting Issue

When we run this code, the kernel may quit unexpectedly or produce a solution that is zero everywhere. This issue can be caused by several reasons:

Insufficient memory: The kernel may run out of memory when trying to solve the PDE. This can be caused by the large size of the solution or the complexity of the PDE.
Numerical instability: The numerical method used to solve the PDE may be unstable, leading to a solution that is zero everywhere.
Incorrect boundary conditions: The boundary conditions may be incorrect, leading to a solution that is zero everywhere.

Strategies to Overcome the Issue

To overcome the kernel quitting issue, we can try the following strategies:

Increase the memory: We can increase the memory available to the kernel by using the MemoryConstrained function.
Use a more stable numerical method: We can use a more stable numerical method, such as the FiniteElement method, to solve the PDE.
Check the boundary conditions: We can check the boundary conditions to ensure that they are correct.
Use a different solver: We can use a different solver, such as the NDSolve function with the Method option set to {"MethodOfLines", "SpatialDiscretization" -> {"FiniteElement"}}, to solve the PDE.

Example Code

Here is an example code that uses the FiniteElement method to solve the PDE:

(* Define the potential energy *)
V[x_, y_] = x^2 + y^2;
(* Define the wave function *)
ψ[x_, y_, t_] = Exp[I (kx x + ky y - ω t)];
(* Define the parameters *)
kx = 1;
ky = 1;
ω = 1;
m = 1;
ℏ = 1;
(* Define the PDE *)
pde = I ℏ (D[ψ[x, y, t], t] == -ℏ^2/2 m (D[ψ[x, y, t], {x, 2}] + D[ψ[x, y, t], {y, 2}]) + V[x, y] ψ[x, y, t]);
(* Solve the PDE using the FiniteElement method *)
sol = NDSolve[pde, ψ[x, y, t], {x, -10, 10}, {y, -10, 10}, {t, 0, 10}, Method -> {"MethodOfLines", "SpatialDiscretization" -> {"FiniteElement"}}];

Conclusion

Solving PDEs is a crucial task in various fields of science and engineering. However, when dealing with very complicated coupled second-order PDEs, the kernel may quit unexpectedly or produce a solution that is zero everywhere. In this article, we discussed the possible reasons behind this issue and provided some strategies to overcome it. By using the FiniteElement method and checking the boundary conditions, we can overcome the kernel quitting issue and obtain a correct solution.

References

[1] "Mathematica Documentation Center." Wolfram Research, Inc.
[2] "Finite Element Method." Wolfram Research, Inc.
[3] "NDSolve." Wolfram Research, Inc.

Future Work

Q: What are the possible reasons behind the kernel quitting issue when solving a very complicated coupled second-order PDE in Mathematica?

A: The kernel quitting issue can be caused by several reasons, including:

Insufficient memory: The kernel may run out of memory when trying to solve the PDE. This can be caused by the large size of the solution or the complexity of the PDE.
Numerical instability: The numerical method used to solve the PDE may be unstable, leading to a solution that is zero everywhere.
Incorrect boundary conditions: The boundary conditions may be incorrect, leading to a solution that is zero everywhere.

Q: How can I increase the memory available to the kernel when solving a PDE in Mathematica?

A: You can increase the memory available to the kernel by using the MemoryConstrained function. For example:

MemoryConstrained[NDSolve[pde, ψ[x, y, t], {x, -10, 10}, {y, -10, 10}, {t, 0, 10}], 10^9]

This will allocate 1 GB of memory to the kernel.

Q: What is the difference between the `FiniteElement` method and the `MethodOfLines` method in Mathematica?

A: The FiniteElement method and the MethodOfLines method are two different numerical methods used to solve PDEs in Mathematica. The FiniteElement method is a more advanced method that uses a mesh to discretize the domain, while the MethodOfLines method uses a finite difference method to discretize the domain.

Q: How can I check the boundary conditions when solving a PDE in Mathematica?

A: You can check the boundary conditions by using the Plot function to visualize the solution at the boundary. For example:

Plot[sol[ψ[x, y, t]], {x, -10, 10}, {y, -10, 10}]

This will plot the solution at the boundary.

Q: What is the difference between the `NDSolve` function and the `FiniteElement` function in Mathematica?

A: The NDSolve function and the FiniteElement function are two different functions used to solve PDEs in Mathematica. The NDSolve function is a more general function that can be used to solve a wide range of PDEs, while the FiniteElement function is a more specialized function that is specifically designed to solve PDEs using the finite element method.

Q: How can I use the `FiniteElement` function to solve a PDE in Mathematica?

A: You can use the FiniteElement function to solve a PDE in Mathematica by using the following syntax:

FiniteElement[NDSolve[pde, ψ[x, y, t], {x, -10, 10}, {y, -10, 10}, {t, 0, 10}]]

This will solve the PDE using the finite element method.

Q: What are some common pitfalls to avoid when solving PDEs in Mathematica?

A: Some common pitfalls to avoid when solving PDEs in Mathematica include:

Incorrect boundary conditions: Make sure that the boundary conditions are correct and consistent with the PDE.
Insufficient memory: Make sure that the kernel has enough memory to solve the PDE.
Numerical instability: Make sure that the numerical method used to solve the PDE is stable and accurate.

Q: How can I troubleshoot issues when solving PDEs in Mathematica?

A: You can troubleshoot issues when solving PDEs in Mathematica by:

Checking the boundary conditions: Make sure that the boundary conditions are correct and consistent with the PDE.
Increasing the memory: Make sure that the kernel has enough memory to solve the PDE.
Using a more stable numerical method: Try using a more stable numerical method, such as the FiniteElement method.
Plotting the solution: Plot the solution to visualize the results and identify any issues.