Quantum Network Probability Distribution Project

This project aims to analyze and generate probability distributions for a given quantum network using neural network methodologies.

Project Structure

• Quantum Network Code: Code for obtaining the probability distribution of a given quantum network.

  • Path: code/experience/quantum_network/

• Neural Network Probability Distribution Generation: Code for generating probability distributions based on target distributions using neural networks.

  • Path: code/experience/neural_network/nn_pytorch/

• Neural Network Models: The neural network models used in the project.

  • Path: code/experience/neural_network/nn_pytorch/model/

• Model Results: Results of the models, including the Euclidean distance to the target distribution.

  • Path: code/experience/neural_network/resultat_pytorch/

• Utility Functions: All functions used throughout the project.

  • Path: code/module/

• Project Report: The final report detailing the project.

  • Root directory of the project "Rapport Bachelor Mohammad Massi RASHIDI.pdf"

Viewing Plots and Graphical Outputs

If you encounter issues with viewing plots in Python scripts, particularly errors related to the Matplotlib backend, here are some tips:

Ensure GUI Backend Installation: For interactive plots, Matplotlib requires a GUI backend. Install Tkinter (for the TkAgg backend) by running sudo apt-get install python3-tk on Debian/Ubuntu systems, or brew reinstall python on macOS.