Innovation in Quantum Software - Alán Aspuru-Guzik - AAAS Annual Meeting

This course focuses on accelerating the discovery of new chemicals and materials through the use of emerging technologies like quantum computing and machine learning. The learning outcomes include developing novel algorithms for quantum computers, executing them on current noisy quantum devices, and applying classical machine-learning techniques to quantum computing hardware discovery. The course teaches algorithms for near-term quantum computers, including variational quantum algorithms, and provides examples and discussions on experimental progress. The teaching method involves a combination of theoretical explanations, practical examples, and discussions. The intended audience for this course includes individuals interested in quantum software development, quantum computing, and machine learning applications in chemistry and materials science.