STM_BNSIC

Solving coefficient Poisson equation for binary neutron stars on irregular domain.

Run a demo simulation

The simplest way to run the code is to run it directly in a python environment:

$ python3

The code requires libraries including numpy, matplotlib, scipy

To try a demo code, run the main.py file:

python3 main.py

In the demo code, first create a inputconfig class that initializes all inputs:

test_inputconfig = inputconfig()

Call the source term method in the source_term_method.py file

stm.stm_coef_Neumann(test_inputconfig)

Use plot1d_error to make a plot of the relative error along the x-axis or use plot2d_error to make a comparison plot of the result and the theory

Changing the configuration

The configuration is initialized in the file main.py in the class inputconfig The code requires

1. N_grid : the size of the grid
2. maxIt_ : the maximum iteration allowed for the source term method
3. it_multiple_ : the maximum iteration multiple (multiply by N_grid ^ 2) allowed for the jacobi iteration method.
4. eta_ : the minimum convergence rate for termination
5. rlx_ : the relaxation constant
6. theory_ : the theoretical value for Phi
7. boundary_ : the boundary condition for Phi_n
8. S_zeta_ : the source (right hand side) for the coefficient Poisson equation
9. rho_ : the density that defines the level set
10. num_grid_dr : the number of grid points for the separation
11. zeta_ : the coefficient for the Poisson equation

Details about the files

1. The file main.py contains an inputconfig class for configuring the input.
2. The file source_term_method.py contains the source term method that solves the coefficient Poisson equation.
3. The file mesh_helper_functions.py contains helper function of vector calculus and level set operations for source_term_method.py.
4. The file mesh_helper_functions_3d.py contains helper function of vector calculus and level set operations in 3d. It is currently only helpful for plotting purposes.