B8542 - QUANTUM COMMUNICATIONS E COMPUTING LM

Learning outcomes

The student acquires the knowledge of the fundamental concepts and technologies for quantum information engineering, specifically the protocols and algorithms for quantum communications and computing: qubits, entanglement, quantum gates, quantum information processing, quantum algorithms, error correction, quantum protocols for the secure distribution of cryptographic keys. At the end of the course the student is able to design basic quantum protocols and algorithms, and to test them on quantum computers accessible via cloud.

Course contents

Prerequisites
The course is intended for Master’s students in electronic engineering, telecommunications engineering, computer engineering, biomedical engineering, and automation engineering. In order to follow the lectures effectively, the knowledge acquired in a Bachelor’s degree programme concerning complex numbers, linear algebra, and probability is sufficient.

Course contents
Principles of quantum mechanics: quantum states, evolution, Schrödinger equations, Hamiltonian, energy, stationary states, qubits, composite quantum systems, measurements, and quantum operations. Entanglement, the EPR paradox, Bell’s theorem, the CHSH game, and the no-cloning theorem. Continuous variables, wave function, Heisenberg limit, and quantum harmonic oscillator.

Quantum computing: one- and two-qubit gates, universal gate sets.

Quantum algorithms: quantum Fourier transform, period-finding algorithm, Shor’s factorization algorithm, breaking RSA cryptography with Shor’s algorithm, and Grover’s search algorithm.

Quantum error correction: stabilizer codes and surface codes.

Quantum communication: purification and teleportation, quantum key distribution, the BB84 protocol, and the Quantum Internet.

Additional topics, covered at an introductory level, include applications to security and sensing, quantum machine learning and quantum neural networks, and quantum simulation.

Readings/Bibliography

Lecture notes distributed by the instructors.

For further reading:

Michael A. Nielsen, Isaac L. Chuang, Quantum Computation and Quantum Information, Cambridge University Press, 2010.

John Preskill, Quantum Computation (lecture notes).

M. M. Wilde, Quantum Information Theory, Cambridge University Press, 2013.

E. G. Rieffel, W. H. Polak, Quantum Computing: A Gentle Introduction, MIT Press, 2011.

N. D. Mermin, Quantum Computer Science: An Introduction, Cambridge University Press, 2007.

Teaching methods

The course, which takes place in the second semester, is taught in Italian and consists of 60 hours of teaching, including at least 12 hours of laboratory activities.

It is structured into classroom lectures, in which the theoretical aspects of the topics covered are presented, and interactive, hands-on laboratory sessions, where a real quantum computer accessible via the cloud will be used, with guided exercises designed to enhance the learning experience.

The exercises, which will take place both in the classroom and in the laboratory, are scheduled so that, within each session, students can practically implement solutions to the problems introduced in theoretical form during the lectures.

Assessment methods

The examination consists of two parts:

• preparation of a project, which may consist either in the development of an application related to one or more topics covered in the course, or in a report presenting the contents of a scientific paper on quantum information, including a critical analysis of the proposed approach and of its potential application impact. Submission of the project documentation, including the developed software in the case of a programming project, is required in order to take the oral examination;

• an oral examination consisting of the discussion of the project.

The final grade, expressed on a scale of 30, takes into account the assessments of both parts.

Teaching tools

For the implementation of quantum circuits and the development of quantum algorithms, both cloud-accessible quantum computers and simulators are used. Dedicated programming languages, as well as Python with the Qiskit SDK, are employed through code development in a notebook environment.

Office hours

See the website of Marco Chiani

See the website of Lorenzo Valentini