Quantum Computing
1- Understand various quantum gates and apply them to generate quantum states
2- Prove the quantum advantage using fundamental algorithms like Deutsch-Jozsa, Bernstein-Vazirani, and Grover search.
3- Convert quantum algorithms into Qiskit 2.x codes to run on IBM quantum computers through a free cloud service.
4- Characterize and compare different quantum computers based on noise in quantum processes.
Qubits, Quantum Measurements, Single Qubit Gates, Multiple Qubit Gates, Phase Kickback, Quantum Circuit Model of Computation, Introduction to QISKIT, Bloch and Q Spheres, Entanglement, Qubit Teleportation, Deutsch—Jozsa, Bernstein—Vazirani, and Simon’s algorithms demonstrating quantum advantage, Quantum Oracles, Programming IBM’s Quantum Computer, Grover’s Search Algorithm, Error Mitigation, Benchmarking Quantum Computers
Quantum computers are the computers of the future because they seem to be much faster than the current computers for many tasks. Many companies like IBM, Google, and Microsoft are investing heavily to develop quantum computers and are making them available in the cloud at the initial stage. This course will be your first introduction and hands-on interaction with quantum computers. We will learn to design quantum algorithms and implement them on actual quantum computers. The course is specifically designed for a broader group of students to introduce quantum computer programming without requiring any previous knowledge of quantum physics. We will study algorithms to solve practical problems like searching a database, factoring prime numbers, optimization, etc., and demonstrate the quantum advantage over currently used classical computers. The algorithms will be implemented using the QISKIT package in Python, and students will learn to write the programs and run them on IBM’s quantum computers.
