Quantum Optimization

The rapid evolution of quantum computing is creating new opportunities to address optimization problems that challenge existing classical methods. Consequently, optimization has become one of the most active domains for quantum algorithm research, with significant potential across science and industry.

Our work focuses on the development of novel quantum algorithms and on demonstrating their advantage over classical techniques. In addition, we explore the synergy between Quantum and AI, investigating how AI can accelerate quantum algorithm discovery and how their combination enables fundamentally new optimization methods leveraging both platforms.

To support these efforts, we study foundational algorithmic building blocks, establish rigorous benchmarking methodologies, and define clear metrics for comparing quantum and classical approaches. Through these initiatives, we aim to demonstrate practical quantum advantage and deliver transformative solutions for real-world optimization problems.