Fall | Undergraduate | Prereq: an introductory or advanced course in quantum information
This course reviews the history of quantum algorithms and presents state of the art methods for constructing new quantum algorithms. Topics include, Shor's algorithm, quantum phase estimation algorithm algorithms for quantum simulation, Grover's algorithm, and quantum linear systems algorithm, leading up to state of the art methods such as the quantum singular value transform. The course also covers algorithms for quantum machine learning, including quantum principal analysis and variational quantum algorithms, and presents a review of de-quantized or quantum-inspired classical algorithms. The last third of the course is project based: students will design their own quantum algorithms.