Checking date: 28/04/2023

Course: 2023/2024

Laboratory on quantum computing
Master in Quantum Technologies and Engineering (Plan: 476 - Estudio: 379)

Coordinating teacher: PUEBLA ANTUNES, RICARDO

Department assigned to the subject: Physics Department

Type: Compulsory
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
- Quantum computation - Matrix quantum mechanics - Wave quantum mechanics
CB6. To possess and understand concepts and ideas that provide a basis or opportunity to be original in the development and/or application of ideas, often in a research context. CB9. That students know how to communicate their conclusions and the ultimate knowledge and reasons that support them to specialized and non-specialized audiences in a clear and unambiguous manner. CB10. That students possess the learning skills that will enable them to continue studying in a manner that will be largely self-directed or autonomous. CG2. Knowledge of scientific and technical subjects that enable them to learn new methods and technologies, as well as to be highly versatile in adapting to new situations. CG4. Ability to solve scientific and technological problems that may arise within the framework of the applications of quantum technologies in various fields of physics and engineering. CG6. Ability to develop new products and services based on the use and exploitation of new quantum technologies. CG7. Ability and knowledge to enable the enrolment in specialized studies at the PhD level, either in related fields of physics or in the various branches of engineering. CE6. Knowledge of the principles of quantum computing and its basic elements: qubits, gates and circuits, as well as knowledge and ability to handle various quantum algorithms. CE7. Ability to generate codes that implement simple quantum algorithms, to identify the kind of problems that can be advantageously solved with them and to identify the potential physical implementations of a quantum computer.
Skills and learning outcomes
Description of contents: programme
1. Introduction to python and Qiskit 2. Single qubit - Bloch sphere - Quantum gates 3. Multiple qubits - Quantum circuits - Two-qubit gates - Quantum gate equivalence - Simulators vs quantum computers 3. Quantum algorithms - Grover - Quantum Fourier Transform - Shor 4. Density matrix
Learning activities and methodology
AF1. Theoretical classes. AF2. Practical classes. AF3. Computational practical sessions. AF4. Group work. AF5. Student individual work. AF6. Midterm and final exam. MD1. Class presentations by professor using electronic and audiovisual resources to convey the main key concepts of the subject, providing relevant bibliography to complement the learning by the students. MD3. Resolution of practical cases in an individual or group manner. MD4. Class presentation and discussion, chaired by the professor, of topics related to the subject. MD5. Individual or group work and reports.
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

Basic Bibliography
  • M. A. Nielsen and I. L. Chuang. Quantum computation and quantum information. Cambridge. 2010
Recursos electrónicosElectronic Resources *
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The course syllabus may change due academic events or other reasons.