This two-day training course will enable you to discover and practice quantum optimization techniques. You will learn how to formulate and solve combinatorial problems using Quantum Annealing and the Quantum Approximate Optimization Algorithm (QAOA).
On the agenda:
📢 Optimization with Quantum Annealing
- Formulation of a QUBO problem (Quadratic Unconstrained Binary Optimization)
- Ising model: searching for the ground state energy by minimizing a Hamiltonian
- Equivalence and translation between QUBO and Ising Hamiltonian
- Principle of Quantum Annealing and adiabatic theorem
- Ising Hamiltonian with Simulated Annealing (SA) and Simulated Quantum Annealing (SQA)
🚀 Optimization with QAOA
- Principle of VQA (Variational Quantum Algorithm)
- Introduction to QAOA and Ansatz
- Discussion on the advantages and limitations of QAOA
💡Practical workshops
- Implementation of simple combinatorial problems (maxcut, graph coloring, etc.)
- Solving QUBO problems with QAOA
🎯Target audience:
This training is intended for researchers, engineers, and developers who have already completed the Basics session and wish to deepen their skills in quantum optimization.