Source Code and Data for the Figures of Nonlinearity of the Fidelity in Open Qudit Systems

Description

This project provides the source code and data used for simulating, analysing and generating the results presented in the paper "Nonlinearity of the Fidelity in Open Qudit Systems: Gate and Noise Dependence in High-dimensional Quantum Computing" (https://arxiv.org/abs/2406.15141).

DOI for the latest version of this project hosted on Zenodo:

Installation

1. Clone the Repository

Clone this repository to your local machine:

bash git clone https://git.unistra.fr/stras_qudits/source-code-and-data-for-the-figures-of-nonlinearity-of-the-fidelity-in-open-qudit-systems.git cd source-code-and-data-for-the-figures-of-nonlinearity-of-the-fidelity-in-open-qudit-systems

Prerequisites

• Python 3.8 or higher: Make sure Python is installed on your system.
• pip: For installing necessary packages.
• Jupyter Notebook: For executing the code and generating the results.
• Git: To clone the repository and manage versions.
• pdflatex For formatting the figures.
• VS Code (Optional): Recommended for integrated development and ease of use.

2. Run the Setup Script

Run the setup.sh script to create and activate a virtual environment, install dependencies, and configure Jupyter Notebook:

bash ./setup.sh

3. Run the Workflow

To automate the setup, notebook execution, and environment cleanup, use the run_workflow.py script:

bash python run_workflow.py

4. Closing the Environment

To manually deactivate the virtual environment, run the close_env.sh script:

bash ./close_env.sh

Usage

1. Navigate to the project directory.
2. Check the file requirements.txt, and run the setup script to initialize the environment if necessary.
3. Launch the notebook (paper_figures.ipynb) manually or using the provided Python script (run_workflow.py).
4. Run the Setup section to import required packages and set the matplotlib plotting style.
5. Use the numbered cell headings for each Figure.
6. Deactivate the virtual environment when done using the closing script.

Using VS Code

• Open the Project in VS Code: Open the project directory in Visual Studio Code.
• Select Python Interpreter: Use the Command Palette (Ctrl+Shift+P) and select "Python: Select Interpreter" to choose the virtual environment.
• Run Jupyter Notebooks: Use the integrated Jupyter support within VS Code.
• Automate Workflow: Use VS Code tasks configured in .vscode/tasks.json to run the entire workflow.

Support

For questions, issues, or suggestions, please contact the corresponding author.

Authors and acknowledgment

Thanks to all authors who contributed to this project.

License

This project is licensed under the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Project status

This project is complete and primarily serves to store and provide access to the code and data used in the related publication. While the main development phase has concluded, minor revisions may still occur.