SDP programs

Summary

This repository contains a Jupyter Notebook (SDP_Bell.ipynb) that demonstrates how to use semidefinite programming (SDP) to find the maximum quantum violation of the CHSH Bell inequality. This maximum value is famously known as Tsirelson's bound ($2\sqrt{2}$).

The notebook uses cvxpy to construct and solve the optimization problem.

Authors

• Jhoan Eusse

Execution

Execute the notebook SDP_Bell.ipynb:

To run this notebook, you will need Python 3 and the following libraries:

• cvxpy
• numpy
• sympy
• qiskit

You can install them using pip:

pip install cvxpy numpy sympy qiskit