Solving Optimization Challenges with Quantum Algorithms
This course explores how Quantum Computing can address complex optimisation challenges that are difficult to solve with classical approaches. Participants will discover the foundations of landmark Quantum Algorithms, with a strong focus on practical Quantum Optimization techniques and their potential business impact. The course covers the current state of Quantum Computing devices, Hybrid Quantum-Classical algorithms, and key Optimization approaches such as the Quantum Approximate Optimisation Algorithm (QAOA). Through practical examples and real-world use cases, participants will learn how Quantum Optimization can be applied to areas such as logistics, finance, and resource allocation. The course also introduces essential techniques for improving the reliability of Quantum Computations on today’s hardware, including Error Suppression, Error Mitigation, Error Discovery, and Error Correction. By the end of the course, participants will understand how to evaluate Quantum Optimization problems, select appropriate Quantum Algorithms, and identify opportunities where Quantum Computing can deliver future value.
What you will learn
- The current state of Quantum Computing hardware, including the capabilities and limitations of today’s Quantum Devices.
- The most important landmark Quantum Algorithms and the problems they are designed to solve.
- Practical Quantum Algorithms that can be explored and applied on current Quantum platforms.
- The principles behind Variational Quantum Algorithms and the different families of Variational Quantum approaches.
- How Hybrid Quantum-Classical Algorithms combine classical optimization techniques with Quantum Circuits.
- The Quantum Approximate Optimization Algorithm (QAOA), including its concepts, design principles, and practical applications.
- How to identify suitable use cases for Quantum Optimization and assess the potential value of Quantum Approaches.
- How to select the most appropriate Quantum Algorithm based on the characteristics of a given problem.
Programme
- An overview of famous landmark Quantum Algorithms
- An overview of rather practical Quantum Algorithms.
- The state of the art of the current Quantum Computing devices
- Quantum Algorithms for Chemistry
- Quantum Algorithms for Machine Learning
- Quantum Algorithms Optimization
- The Quantum Approximate Optimization Algorithm
- Practical examples and use cases
- Overview of Error Suppression, Mitigation, Discovery and Correction techniques