Optimal Synthesis

Optimal synthesis focuses on finding the best possible design or solution within a given set of constraints, encompassing diverse applications from quantum computing to robotics and hardware design. Current research emphasizes efficient algorithms, including evolutionary algorithms, polynomial-based approaches, and deep learning models like Transformers and Graph Neural Networks, to tackle the computational complexity of these optimization problems. These advancements are improving the speed and quality of design processes across various fields, leading to more efficient and effective systems in areas like quantum circuit design, drone control, and hardware acceleration.