The Quantum Computing (QC) course is a mandatory course belonging to the Master Degree in Quantum Engineering, available also for other courses; it is taught in the first semester of the second year, and it is taught in English. The main goal of the course is to provide the students with a knowledge of the software applications of quantum computing, by means of integrated business hw/sw platforms. The purpose is to show what it is actually possible to do with a quantum computer. During the course, will be provided contributions from companies with whom Politecnico di Torino is involved for research and development projects, such as IBM, Intesa Sanpaolo, TIM, Pasqal, Fondazione Links.

- Basic knowledge of software platforms for quantum computers - Detailed knowledge of IBM platform - Detailed knowledge of D-Wave platform - Knowledge of Pasqal platform - Knowledge of main applications of quantum computing in finance, optimization, and telecommunications

- basic knowledge in computer sciences - basic knowledge in Python programming and high level programming languages - knowledge of the quantum gates from a hardware point of view - knowledge of the main quantum algorithms (e.g. Shor)

- Introduction to software platforms for quantum computing (0,5 credits) - IBM platform (1,5 credits) - D-Wave platform (1,5 credits) - Pasqal platform (1,5 credits) - Applications (finance, optimization, telecommunications) (1 credit) - Laboratory exercises will be done, most of the course will be hands-on. Please note that topics are subject to partial change, due to the fast changes in this subject

- Class lectures (also hands-on): 50% of the course duration; - Extensive Class exercise time: 30% of the course duration; - Assisted laboratories: 20% of the course duration. Students are highly invited to interact with Lecturers, at lecture, exercise, and laboratory slots. Students are invited to take always with themselves their notebook for hands-on activities.

• Learn Quantum Computing with Python and IBM Quantum Experience: A hands-on introduction to quantum computing and writing your own quantum programs with Python - Robert Loredo - Packt Publishing (28 settembre 2020) - ISBN-10 ‏ : ‎ 1838981004 - ISBN-13 ‏ : ‎ 978-1838981006 • Quantum Machine Learning: An Applied Approach: The Theory and Application of Quantum Machine Learning in Science and Industry – Santanu Ganguly - Apress (29 luglio 2021) - ISBN-10 ‏ : ‎ 1484270975 - ISBN-13 ‏ : ‎ 978-1484270974 • Quantum Machine Learning and Optimisation in Finance: On the Road to Quantum Advantage - Antoine Jacquier (Autore), Oleksiy Kondratyev (Autore), Alexander Lipton (Avanti), Marcos Lopez de Prado (Avanti) - Packt Publishing (31 ottobre 2022) - ISBN-10 ‏ : ‎ 1801813574 - ISBN-13 ‏ : ‎ 978-180181357 The three books are freely available for Politecnico di Torino students in the university library in digital format.

Slides; Libro di testo;

E' possibile sostenere l’esame in anticipo rispetto all’acquisizione della frequenza

Modalità di esame: Prova scritta (in aula); Prova orale facoltativa; Elaborato progettuale in gruppo;

Exam: Written test; Optional oral exam; Group project;

... The examination is composed of two parts, a written part and an assignment. Written examination: The written exam is composed of questions and exercises on the course content. It lasts for 1h. The maximum score for this part is 30/30. A sufficient mark is >= 18. Assignment: Students will be asked to deliver a group assignment (usually 2 persons per group) to be developed at the end of the semester. The maximum score for this part is 30/30. A sufficient mark is >= 18. The final grade is the arithmetic mean of the two parts, provided that both of them are sufficient (>=18) An optional oral examination can be asked to the teacher, in order to improve a mark of 30 and reach the 30 cum laude. The teacher will also be able to ask for an oral exam independently of marks obtained in the written part and assignment or even in substitution of them in particular conditions.

Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.