Computational Tools

1.1. Wave-Function Modeling:
Computational Tools, built in python and rust, that enable the wave-function modeling of all aspects of subatomic particle and photon systems.

1.2. Physics Modeling:
An open source software package that could be used to set up and solve various problems in physics, such as charge distribution in dielectrics, heat transfer, and wave propagation.

1.3. Sub-Quantum Modeling:
A powerful software tool for modeling in M.A.R.T. is under construction.


1.1. Wave-Function Modeling

As part of the ongoing work to determine the correct mathematical framework for describing physical phenomena, we have been developing several software based tools to aid in the computation and visualisation of results. This work is being lead by Innes Anderson-Morrison and currently comprises of two software libraries supporting programs / scripts built using them.

  • arpy – a python library and command line tool for interactive computation. arpy was originally developed to aid in comparing different metrics and configurations of the elements within the AR algebra which makes it particularly powerful for comparing results of calculations under different systems.
  • arthroprod – originally a rewrite of the python code from arpy to improve performance, this is now the main project being worked on for active research into the AR algebra and verification of results. Given the research based nature of the project and its use of as-yet unpublished results to vastly simplify calculation, the main project is currently private. If you would like to view or contribute to the project please get in touch.

1.2. Physics Modeling

An open source software package that could be used to set up and solve various problems in physics, such as charge distribution in dielectrics, heat transfer, and wave propagation. This work is being lead by Mayank Drolia and currently comprises the three software libraries linked below.

Technical Notes:
A FORTRAN based numerical solver. It uses input files from GMSH to extract geometrical information such as space discretization and boundary points, and automatically calculates useful data such as memory requirements for the solver, direction of perpendicular vectors to the boundaries, etc. The initial and boundary conditions are set up by configuring a purpose built input file. Robin, Dirichlet, and Neuman boundary conditions are supported. Semi-discrete approach is used for a hybrid Finite Element Finite Difference scheme to solve Partial Differential Equations (PDEs). Three categories of PDEs are supported, i.e. elliptic, parabolic, and hyperbolic, via separate instances of the package namely ElliFEM, ParaFEM, and HypFEM respectively. LinPACK is used for matrix operations. The solutions are output in a format readable in Techplots or Paraview. The components of output, such as time steps at which to produce outputs, are completely configurable by modifying the source code. Other mathematical optimizations (and experiments), such as changing the solution anzats and varying the order of time integration, can be conducted as well. The code, at the moment, is restricted to solving 2D (in space) problems, but can be extended to 3D, with enough time spent.

LINKS:
ElliFEM: https://github.com/md861/ElliFEM 
ParaFEM: https://github.com/md861/ParaFEM 
HypFEM: https://github.com/md861/HypFEM


1.3. Sub-Quantum Modeling

Watch this space…


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