Physics-inspired Computing and Neuromorphic Algorithms

This lecture explores the design of physics-inspired computing and neuromorphic algorithms, focusing on using nature as a computer. It delves into analog computing, optical computing, and spin waves as ideal waves for physics-based computing. The need for beyond-Moore computing developments is highlighted, showcasing the potential of machine learning in designing physics-based devices. The lecture also discusses the end of Moore's Law and the emergence of new information technology eras. Various examples of ancient magnetic computers and nanomagnet logic are presented, along with the application of spin waves in super-efficient transmission. The lecture concludes with insights into wave-based, optical computing and the utilization of parametric oscillators in building entire computers.