Teaching plan for the course unit

 

 

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General information

 

Course unit name: Quantum Computing

Course unit code: 574647

Academic year: 2021-2022

Coordinator: Bruno Julia Diaz

Department: Department of Quantum Physics and Astrophysics

Credits: 3

Single program: S

 

 

Estimated learning time

Total number of hours 75

 

Face-to-face and/or online activities

26

 

-  Lecture

Face-to-face and online

 

20

 

-  Lecture with practical component

Face-to-face and online

 

6

Independent learning

49

 

 

Recommendations

 


  1. Solid background on Quantum mechanics

  2. Solid background on Quantum information theory

 

 

Competences to be gained during study

 


  1. Basic principles of Universal models of Quantum computation

  2. Analysis tools to classify problems according to Complexity theory

 

 

 

 

Learning objectives

 

Referring to knowledge


  1. To obtain a detailed view of Quantum Algorithmic design

  2. To obtain a general view of Complexity theory

 

 

Teaching blocks

 

1. Classical Computation

*  Introduction to classical computation models

Automata and languages

Turing Machines

Decidability

Introduction to complexity Theory

Complexity classes

2. Introduction to Quantum Computation

*  Models of Quantum Computation

Quantum circuits and Quantum gates

Adiabatic Quantum Computation

Measurement Based Quantum Computation

Universality

3. Quantum Algorithms

*  Deutsch-Jozsa Algorithm

Grover search algorithm

Fast Fourier Transform

Period Finding and Shor Factoring

Quantum complexity

4. Noisy-Intermediate-Size-Quantum devices

*  Hybrid architectures

Variational methods for QuantumChemistry

QAOA

5. Simulation of Quantum circuits on classical devices

*  Programming techniques for HPC simulation on a supercomputer

Approximation to Quantum Computation with Tensor Network methods.

 

 

Teaching methods and general organization

 


  1. Lectures where theoretical contents of the subject are presented. 

  2. Practical exercise classes in which students may participate. 

  3. Activities related to the subject suggested by the teaching staff.

 

 

Official assessment of learning outcomes

 


  1. A final written examination on the entire course content

 

 

Reading and study resources

Consulteu la disponibilitat a CERCABIB

Book

Michael Nielsen and Isaac Chuang. Quantum Computation and Quantum Information. Tenth Anniversary Edition. Cambridge University Press 2010.

An Introduction to Quantum Computing, Michele Mosca; Raymond Laflamme; Phillip Kaye, Oxford University Press 2007.

Article

Adiabatic quantum computation, Tameem Albash and Daniel A. Lidar, Rev. Mod. Phys. 90, 015002 (2018).

Measurement-based quantum computation, H. J. Briegel, D. E. Browne, W. Dür, R. Raussendorf & M. Van den Nest, Nature Physics volume 5, pages 19–26 (2009).

Web page

Caltech Computer Science 219, Quantum Computation http://theory.caltech.edu/~preskill/ph229/