Half a year ago, I introduced the PyRules project aiming to develop, through Steem, a full program to be used for state-of-the-art particle physics research.

_{[image credits: Domenico Salvagnin (CC BY 2.0)]}

Very briefly, the idea consisted in building a Python framework that reads in a particle physics model (an equation given in the quantum field theory language) to be provided by a user.
After some systematic and textbook manipulations, the program then rewrites the model under a standard format to be used by various other particle physics packages, including particle collider simulators and dark matter calculators.
This project therefore aims to streamline the connection between a particle physics models and numerical calculations, through the development of an open access platform in Python by Steem users. For more information, please have a look to the kick-off post.
The project started well (see the GitHub repository of the project).

It includes a generic command-line interface (an extension of the Python cmd library).
The internal data format contains a class able to deal with parameters (the master equation above-mentioned contains many parameters).

It then moved on with a three-month hibernation stage because of too-full agendas… I would like, with this post, to try to resurrect it in a smooth way by proposing a few task developments (i.e. a few baby-steps towards our final goal). Those steps do not require any knowledge in particle physics, and only necessitate to check a few (already coded) files to get updated on what has been done a few months ago.

Parameters - the status

As promised above, we do not need any particle physics knowledge for now. It is sufficient to remember that the master equation behind any particle physics model depends on parameters, and that we focus only on the latter for today. They could be external (their numerical value is an input) or internal (they are given as a formula depending on other parameters).

_{[image credits: Laura Gilchrist (CC BY 2.0)]}

In a model implementation (provided by the user), parameters are introduced with different properties (name, value, type, indices, etc.).
For more information, I refer to the two examples available in the examples subdirectory of the program. For the meaning of these different attributes, one can also check out this post.
The PyRules program so far consists in a command-line interface that can be started by typing in a shell

bin/pyrules

from the directory where the program has been unpacked. The interface allows for basic commands (EOF, exit, help, history, quit, shell) and understands what a parameter is (see src/parameter/parameter.py). This last file contains the definition of the PyRulesParameter format that is the internal way parameters are dealt with.

Parameters - task list

_{[image credits: geralt (CC0)]}

In this post, we require the development of a few commands to be added to the interface. The new files will have to be pushed in src/interpreter.
For, we need to implement a way to link the parameter objects provided by the user and handle them within the internal PyRulesParameter format. One PyRulesParameter object has to be instantiated for each declared parameter. This thus requires:

An import commands allowing to import a directory containing the model implementation (that consists only in parameters for now).
A display command allowing to display information about a specific parameter given as an argument.
A set command allowing to change the numerical value of an external parameter. Internal parameters cannot be modified and any other option is not allowed to be modified.

Moreover, it is necessary to develop a few extra commands in a src/toolbox directory so that we can actually test stuff related to the parameters.

A series of boolean methods checking whether a parameter is a scalar or a tensor quantity (ScalarQ, TensorQ), whether it is a unitary, orthogonal or Hermitian matrix (UnitaryQ, OrthogonalQ, HermitianQ).
A NumericalValue method taking as input a valid Python formula (depending on the model parameters) and evaluating it.

In the aim of re-starting the project baby-step by baby-step, we will solely focus for now on this light list of tasks.
If you are interested in helping with one, two or even more of these tasks, feel free to try it out and join the project. For any question, please comment this post or reach me out on the SteemSTEM discord server.
Good luck and thanks in advance for participating to this project that could be seen as a one of a kind!

SteemSTEM

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