Programming and implementation of quantum algorithms

The purpose of quantum computers is to take advantage of the quantum properties of qubits and to be able to execute quantum algorithms that use superposition and entanglement to offer a much higher processing capacity than classical algorithms. It is important to point out that the real paradigm shift does not consist of doing the same thing that digital or classical computers do, but that quantum algorithms allow performing certain operations in a totally different way that in many cases turns out to be more efficient, i.e., in much less time or using much less computational resources. This course presents a series of quantum algorithms that provide computational advantages over the best equivalent classical algorithms. Although some of these algorithms have no direct practical application or their implementation is infeasible on current quantum computers, they are a clear example of the possibilities that quantum computation offers for dealing with classically unsolvable problems.

This course is designed for students to learn in the laboratory relevant aspects of quantum programming of algorithms seen previously.

As a result of the learning the students who take this course will be able to:

CON_03: Know the physical bases that allow coding and processing information. Understanding of the new rules imposed by Quantum Mechanics for its processing.
CON_04: Have knowledge of quantum computing, algorithms, circuits, programming in different languages and accessible platforms.

1- Introduction to "classical" quantum algorithms
2- Quantum parallelism
3- Quantum oracles
4- "Classical" quantum algorithms:
a. Deutsch and Deutsch-Jozsa algorithms.
b. Bernstein-Vazirani algorithm.
c. Simon's periodicity algorithm
5- Grover's search algorithm: amplitude amplification
6- Quantum Fourier transform
7- Quantum Phase Estimation Algorithm
8- Shor Factorization Algorithm

Basic:
- Lecture Notes
- Various authors, Qiskit textbook: Quantum protocols and quantum algorithms, Available online at: https://qiskit.org/learn/course/quantum-protocols-and-quantum-algorithm…

Supplementary:
- Thomas G. Wong. Introduction to Classical and Quantum Computing, chapter 7, Rooted Grove, 2022.
- Noson S. Yanofsky and Mirco A. Mannucci. Quantum computing for computer scientists, chapter 6, Cambridge University Press, 2008.
- M.A. Nielsen and I.L. Chuang: Quantum Computation and Quantum Information, chapters 4-6, Cambridge, 2010.

Students taking this subject will acquire the skills and abilities of critical and creative thinking, communication and collaborative work that are indicated in the degree's verification report (HD0, HD1, HD2, HD3).

In addition to the basic (CB1-CB5), general (CG1-CG4) and transversal (CT1-CT8) competences specified in the verification report of the degree, students will acquire the following specific competences of this course

Specific Competences:

CE_7: Acquire and know how to apply the basic principles of quantum computing: analyze, understand and implement quantum algorithms, mastering the appropriate computer languages as well as understanding the quantum circuit paradigm.

The classes will be face-to-face and will be transmitted synchronously to the other campuses.

- Lectures: the programmed contents will be explained and any doubts that may arise will be answered.
- Practical classes: exercises and problems will be proposed that students will have to solve in the laboratory and in their own work time. Students will be given the opportunity to present their results. Sharing of doubts.
- Laboratory practice: practical sessions in computer rooms dedicated to solving the proposed problems.
- Autonomous work: during this time, students will study the subject and solve the proposed tasks.

There will be a virtual platform where essential and supplementary formative and informative material will be available.

The evaluation of the subject will be a combination of different aspects. The weighting will be fixed and announced each course within the margins approved in the verification memory.

Ordinary opportunity:
1 - Partial and/or final exams and/or tests.
Weighting: 40%.

2- Continuous evaluation: attendance and participation in lectures and interactive classes, delivery of exercises and solved problems, voluntary exposition of results.
Weighting: 60%.

Opportunity of recovery (July) and extraordinary:
The evaluation will be the same as in the ordinary opportunity. Students who did not hand in the proposed assignments throughout the term must hand them in before the date of the theoretical exam.

Condition for a grade of "No Show": not submitting any practical and not taking the exam.

Lectures: 10 hours
Practical classes: 5 hours
Laboratory practicals: 10 hours
Individual Tutoring: 3 hours
Students' personal work: 47 hours.

Total: 75 hours