This notebook demonstrates the formulation of Quadratic Unconstrained Binary Optimization (QUBO) problems as ground state problems and their solution using Variational Quantum Eigensolvers (VQE).
The notebook implements a VQE solver for the Max-Cut problem using
Qiskit's EfficientSU2 ansatz and GSLS optimizer. The QUBO problem
is formulated as a ground state problem and solved using variational
quantum algorithms.
The following Python packages are required to run this notebook:
numpy(for numerical operations)qiskit(for quantum circuit construction and VQE implementation)qiskit-optimization(for QUBO problem formulation)
Note: The numpy package is included in the top-level
requirements.txt. The Qiskit packages (qiskit and
qiskit-optimization) are optional dependencies that will be
automatically installed by the notebook if not already present. If you
prefer to install them beforehand, you can run:
pip install qiskit qiskit-optimizationAlternatively, if you have set up the base environment as described in the main README, the notebook will handle the installation of Qiskit packages automatically when executed.
Copyright (C) 2024 Mohammadreza Khellat GNU GPL v3+
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.