First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
Course unit
INP9086478, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2019/20

Information on the course unit
Degree course Second cycle degree in
IN0527, Degree course structure A.Y. 2008/09, A.Y. 2019/20
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination QUANTUM INFORMATION AND COMPUTING
Department of reference Department of Information Engineering
Mandatory attendance No
Language of instruction English
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Teacher in charge GIUSEPPE VALLONE FIS/03

Course unit code Course unit name Teacher in charge Degree course code

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines ING-INF/05 Data Processing Systems 6.0

Course unit organization
Period First semester
Year 1st Year
Teaching method frontal

Type of hours Credits Teaching
Hours of
Individual study
Lecture 6.0 48 102.0 No turn

Start of activities 30/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2008 course timetable

Examination board
Board From To Members of the board
1 A.A. 2019/2020 01/10/2019 15/03/2021 VALLONE GIUSEPPE (Presidente)
VILLORESI PAOLO (Membro Effettivo)

Prerequisites: Linear algebra.
Target skills and knowledge: Notion of qubits and quantum measures
Notion of entanglement and use in Bell's inequalities
Comparison between classical and quantum information
Knowledge on quantum information applications such as Dense coding, Quantum teleportation, Quantum Key distribution, Quantum random number generators and Quantum Metrology
Comparison between classical and quantum computing
Notion of QFT
Knowledge of quantum algorithms, such as the Shor algorithm, the Quantum Database Search, Quantum simulations
Data analysis of quantum optis experiments
Examination methods: It will be defined by the teacher.
Assessment criteria: The student evaluation will be based on homework, laboratory reports and oral exam.

The homework and laboratory reports weigh 30% on the final grade.

In the homework the ability to solve the problems related to the studied concepts will be evaluated.

Laboratory reports will be evaluated on the ability to synthesise and analyze laboratory experiences.

During the oral exam the assessment is based on the understanding of the topics covered in class and on the ability to expose them in a clear and exhaustive manner.
Course unit contents: PART I: general concepts
What is a qubit: introduction to quantum mechanics
Hilbert spaces, operators and projectors
Quantum measurements
Time evolution, decoherence
Entanglement: definition, generation and detection
Quantum state tomography
Bell Inequalities

PART II: Quantum Information
Classical Information versus Quantum Information
Quantum channels and no cloning
Dense coding
Quantum Key distribution
Quantum Random Number Generators
Quantum Metrology

PART III: Quantum Computation
Classical Computation versus Quantum Computation
From FFT to QFT
Shor’s algorithm
Quantum Database Search
Quantum Simulations
Physical Implementations
Planned learning activities and teaching methods: The teaching takes place through frontal lessons on the blackboard or with slides, as it is believed that this method allows to keep high the students' attention, with the possibility of interaction and involvement.
Some results are illustrated using the computer with a large screen display.
In addition there are exercises in the classroom, both carried out by students in the classroom in groups of 2/3 people, both by the teacher at the blackboard.

There are also homework to be done at home and laboratory experiences to deepen and experiment some concepts seen in class.
Additional notes about suggested reading: All course topics are presented in the classroom.
Class notes can be integrated with textbooks.
On the moodle platform a list of the topics covered lesson by lesson will be made available.
Textbooks (and optional supplementary readings)
  • Nielsen, Michael A., Chuang, Isaac L., Quantum computation and quantum information.. --: Cambridge: Cambridge university press, --. Cerca nel catalogo
  • G. Benenti, G. Casati, and G. Strini, Principles of quantum computation and information.. --: New Yersey: World Scientific, 2004. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Interactive lecturing
  • Working in group
  • Questioning
  • Problem solving
  • Use of online videos
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Latex
  • Matlab

Sustainable Development Goals (SDGs)
Quality Education Industry, Innovation and Infrastructure