ID:
509533
Durata (ore):
36
CFU:
3
SSD:
Indefinito/Interdisciplinare
Anno:
2024
Dati Generali
Periodo di attività
Secondo Semestre (03/03/2025 - 13/06/2025)
Syllabus
Obiettivi Formativi
a) Understand the key differences between quantum and classical physical and logical systems
b) Utilize quantum circuits to represent, manipulate, and measure single/multi-qubit quantum states
c) Be able to model computation and communication tasks in the quantum model
b) Utilize quantum circuits to represent, manipulate, and measure single/multi-qubit quantum states
c) Be able to model computation and communication tasks in the quantum model
Prerequisiti
Basic previous knowledge of quantum physics is required and, from the mathematical point of view, only a good command of basic linear algebra is assumed. Some familiarity with the python programming language would be helpful, but is not required either.
Metodi didattici
Lectures will be implemented via notes given at the blackboard and using slides. The module also includes training session in which the teacher and the students will use python to implement problems and exercises connected with the lectures’ topics. Attendance and interaction with the teacher during the entire course are strongly recommended.
Verifica Apprendimento
The final test consists in an oral exam to establish the student knowledge of the concepts presented in the course. The main part of the exam will be the description of a project that deepens some aspect of quantum information processing via analytical or numercial methods. Each student will independently choose, or agree with the teacher, the subject of the project.
Testi
B. Schumacher and M. Westmoreland – Quantum Processes Systems, and Information 2010 Cambirdge University Press (ISBN 978-0-521-87534-9)
Lectures Notes on Quantum Computation, John Watrous https://cs.uwaterloo.ca/~watrous/QC-notes/QC-notes.pdf
Quantum Computation and Quantum Information: 10th Anniversary Edition, Michael A. Nielsen, Isaac L. Chuang. Cambridge University Press, 2011
Learn Quantum Computation using Qiskit, Abraham Asfaw et al. https://qiskit.org/textbook/preface.html
Lectures Notes on Quantum Computation, John Watrous https://cs.uwaterloo.ca/~watrous/QC-notes/QC-notes.pdf
Quantum Computation and Quantum Information: 10th Anniversary Edition, Michael A. Nielsen, Isaac L. Chuang. Cambridge University Press, 2011
Learn Quantum Computation using Qiskit, Abraham Asfaw et al. https://qiskit.org/textbook/preface.html
Contenuti
Quantum computing is capturing growing attention as research field in computer science and physics departments worldwide. The physics community first boosted and promoted the idea of "quantum computers", as witnessed over the years by several dedicated journals, conferences on the subject and theoretical and experimental labs focusing on this goal. At first it was scientists interested in the fundamental aspects of quantum mechanics that started to investigate quantum systems as possible carriers of information, posing the basis for a profound understanding of key quantum resources as non-locality and entanglement. This process resulted in quantum information and computation theory bringing new prospects for using quantum systems in synergy with the classical ones for accomplishing computational and communication tasks, opening up opportunities in cryptography and introducing novel protocols as quantum teleportation.
In this course we will introduce from scratch the basic ideas at the basis of quantum information processing taking the quantum circuit model (qubits, gates and measures) as reference point. We will use quantum circuits to highlight the features that distinguish quantum systems by classical ones, and to study some of the most relevant quantum algorithms and protocols, including those that can be implemented with a few qubits (BB84, quantum teleportation, superdense coding...) as well as those that require multi-qubit systems (Deutsch-Jozsa, Grover, Shor..). We will also look at some of the most recent applications of quantum computing in the fields of optimization and simulation (quantum annealing, the quantum approximate optimization algorithm and the variational quantum eigensolver).
Syllabus:
1) Probability Theory and Quantum Mechanics: quantum states, gates and measurements
2) Quantum circuits
3) Single-qubits states (states discrimination) and multi-qubit states (entanglement)
4) Mixed states (density matrix) and von Neumann entropies
5) Monogamy of entanglement, entanglement swapping, steering of states
6) Superdense-coding an teleportation
7) No cloning, no-information without disturbance and quantum key distribution
8) Non-local games: CHSH game
9) Algorithms: Deutsch-Jozsa, Grover search, Shor factoring
10) Simulation: annealing, quantum eigensolver
In this course we will introduce from scratch the basic ideas at the basis of quantum information processing taking the quantum circuit model (qubits, gates and measures) as reference point. We will use quantum circuits to highlight the features that distinguish quantum systems by classical ones, and to study some of the most relevant quantum algorithms and protocols, including those that can be implemented with a few qubits (BB84, quantum teleportation, superdense coding...) as well as those that require multi-qubit systems (Deutsch-Jozsa, Grover, Shor..). We will also look at some of the most recent applications of quantum computing in the fields of optimization and simulation (quantum annealing, the quantum approximate optimization algorithm and the variational quantum eigensolver).
Syllabus:
1) Probability Theory and Quantum Mechanics: quantum states, gates and measurements
2) Quantum circuits
3) Single-qubits states (states discrimination) and multi-qubit states (entanglement)
4) Mixed states (density matrix) and von Neumann entropies
5) Monogamy of entanglement, entanglement swapping, steering of states
6) Superdense-coding an teleportation
7) No cloning, no-information without disturbance and quantum key distribution
8) Non-local games: CHSH game
9) Algorithms: Deutsch-Jozsa, Grover search, Shor factoring
10) Simulation: annealing, quantum eigensolver
Lingua Insegnamento
INGLESE
Corsi
Corsi
ARTIFICIAL INTELLIGENCE
Laurea
3 anni
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