An efficient machine learning algorithm to decompose an arbitrary single-qubit gate into a sequence of gates from a finite universal set. Reference: https://doi.org/10.1103/PhysRevLett.125.170501
In this example code the universal gate set is chosen to be the braiding operations of the Fibonacci anyon model.
To train a model from scratch:
python3 main.py
To test a pretrained model on randomly generated matrices:
python3 test.py
Sorry that I haven't provided any convenient tools for customizing the model yet. In order to decompose a particular quantum gate, or training a new model, you can just clone the source code and edit the corresponding parts.