Quantum Computing

Objectives and outcomes

The time of quantum computers, the most complex creation of the human mind and technology, is yet to come. The aim of the course is to provide a comprehensive introduction to quantum computers by combining computer science, mathematics and quantum mechanics, focusing on the principles of quantum programming and the analysis and design of quantum algorithms. The course also tackles topics such as quantum cryptography and quantum machine learning. The completed course provides an understanding of quantum computers principles and provides a basis for the independent design of quantum algorithms and their practical implementation.

Lectures

 General introduction to quantum computers. Linear algebra in the context of quantum computers. Qubit, quantum gate, quantum circuit. Quantum assembler and Python libraries for quantum programming. Elementary quantum circuits and design of quantum algorithms. Quantum algorithms: superdense coding, quantum teleportation. Grover’s and Shor’s algorithm. Quantum cryptography: quantum key distribution, BB84, B92 and E91 protocols. Quantum machine learning, variational quantum classifier.

Practical classes

Overview of quantum circuit elements, programming languages, and software tools for quantum computing. Implementation of the algorithms covered in lectures: design of quantum circuits and writing of appropriate program code in quantum assembler and Python programming language and testing the program on the IBM quantum cloud.