Quantum Algorithms

Catalog description

This course is the second in series of Quantum Computing (QC) courses. Covers unique features of QC machines, terminology, comparison of quantum algorithms to classic algorithms, quantum algorithm design to take advantage of superposition quantum parallelism, entanglement, non-locality, and quantum interference. Master well-known quantum algorithms to include Deutsch-Josza’, Simon’s, HHL, and Shor’s algorithms. Explore in depth Grovers’ Algorithm for search of unsorted lists and to solve 3-SAT problems. Introduction to Quantum Variational Eigensolver (VQE), Quantum Unconstrained Binary Optimization (QUBO), Quantum Machine Learning (QML), and Quantum Approximation Optimization Algorithm (QAOA). Students will write programs in Python on an actual quantum computer. Prerequisite(s): Graduate level CS 6200 Minimum Grade of C