Allenator / qnlp-ansaetze

Exploring ansaetze for Quantum Natural Language Processing (QNLP) applications

Encoding Opposition With Variational Quantum Compositional Models: Supplementary Code

Allen Mi - January 2022

How-To-Run

The project is developed under x86-64 Linux. The system dependencies are as follows:

• conda: Anaconda or Miniconda, for managing the appropriate Python virtual environment

To install the Python dependencies, run

conda env create -f requirements.yml

at the root directory of the folder, followed by

conda activate qnlp

to activate the virtual environment.

Project structure

• corpus/: corpus-related files
  • corpus.pickle: pickled 40-sentence corpus
• data/: saved training data
  • all_results.pickle: pickled training results used in the notebooks
  • sweep.pickle: pickled parameter sweep results used in the notebooks
• figures/: paper figures
  • omitted
• ansaetze.py: implementations for the variational ansaetze
• utils.py: utility code for training and testing the model
• training-and-testing.ipynb: Jupyter notebook for implementing, training and testing the model
• make-figures.ipynb: Jupyter notebook for generating the paper figures
• requirements.yml: conda virtual environment specifications
• README.md: this Markdown file