Course Details

COMPUTAZIONE QUANTISTICA

MF0615

Course
COMPUTAZIONE QUANTISTICA
Code
MF0615
Academic Year
2023/2024
Curriculum Year
2021/2022
Degree Programme
BIOLOGY
Curriculum
000 - CORSO GENERICO
Course coordinator
Lecturers
Credits
3
Lecture Hours
24
Scientific Disciplinary Sector (SSD)
FIS/02 - Theoretical Physics, Mathematical Models and Methods
Course Type
Single-subject learning activity
Course Delivery
OPZ - Opzionale
Year
3
Teaching period
Secondo Semestre
Campus
ALESSANDRIA
Teaching language
Italian
Course Contents
The course provides an introduction to the theoretical ground and
experimental techniques in quantum computation.
Reference Texts
M.A. Nielsen, I.L. Chuang, "Quantum computation and quantum
information", CUP (2000);
J. Preskill, Lecture Notes for Phys. 229, Quantum information and
computation, http://theory.caltech.edu/~preskill/ph219/;
Lecture notes
Learning Outcomes
Acquisition of basic theoretical knowledge and experimental techniques
for quantum computation.
Prerequisites
Linear algebra and calculus, introductory physics.
Teaching Methods
Frontal lessons, take home exercises, practice in quantum programming
with online quantum computers (IBM Q-experience)
Additional Information
Lecture notes will be available on the site of the course
Assessment Methods
Oral exam. Exercises in the classroom.
Detailed Syllabus
1. Introduction. Complex numbers, Taylor's formula, Euler's formula.
Matrices and their operations.
2. Recap of linear algebra: vector spaces, linear operators, scalar
product. The basic rules of quantum mechanics.
3. Quantum bits, Bloch sphere, multiple qubits, single qubit gates and

Programma
esteso/Content

1. Introduzione. Numeri complessi, formula di Taylor, formula di Eulero.
Matrici e loro operazioni.
2. Ripasso sintetico di algebra lineare: spazi vettoriali, operatori, prodotto
scalare. Le regole di base della Meccanica Quantistica.
3. Quantum bits, sfera di Bloch, qubits multipli, porte a singolo qubit e
porte a qubits multipli.
4. Circuiti quantistici. Stati intrecciati. Algoritmi quantistici. Cenni alla
teoria dell' informazione quantistica.
5. Crittografia quantistica. Teletrasporto.
6. Algoritmo di Deutsch-Josza. Trasformata di Fourier Quantistica.
Algoritmo di Shor
per la fattorizzazione di numeri interi. Algoritmo di Grover per la
ricerca in un database.

Risultati di
apprendimento
attesi/Intended
learning objectives

Acquisizione dei principi di base della computazione quantistica, e
capacità di applicarli alla programmazione di calcolatori quantistici.

Obiettivi per lo sviluppo sostenibile

Codice Descrizione

multiple qubit gates.
4. Quantum circuits. Entangled states. Quantum algorithms. Notions of
quantum information.
5. Quantum cryptography. Quantum teleportation.
6. Deutsch-Josza algorithm. Quantum Fourier Transform. Shor's algorithm
for factorization. Grover's algorithm
for searching non structured databases.
Expected Learning Outcomes
Understanding of the basic principles of quantum computation, and
ability to apply them in programming quantum computers.
Last update:09-09-2026 00:14:31