## Admission requirements

Not applicable.

## Description

The course consists of regular lecturers in which we look at Quantum Computing through the eyes of a computer scientist. This means that after the presentation of some necessary basic knowledge, several topics are addressed like architecture, algorithms, programming languages, cryptography, and hardware. This results in knowledge of an exiting research field, of which it is clear that despite the progress made, many hurdles still have to be taken.

Introduction

Cbits and Qbits

General features and some examples

Quantum annealing and the universal quantum computer

Breaking RSA encryption

Searching with a quantum computer

Quantum teleportation

Quantum error correction

Protocols with a few Qbits

Quantum artificial neural networks

The prerequisites for the course are 1) being well versed in designing and understanding algorithms and 2) a successful completion of a course on basic linear algebra. In exceptional cases the latter can be a corequisite – contact the instructor prior to the start of the semester in case you lack the necessary background.

## Course objectives

In the course, the students will understand how to leverage the power of quantum computers and learn about simulated physics. Why are QC more powerful than classical computers? By understanding when they are not powerful, we are learning how to efficiently write classical algorithms for certain quantum systems. Furthermore, there exists a remarkable harmony between physics and mathematics, but what about computer science? In the course we will walk through quantum algorithms, and will, as a consequence, approach the ultimate limits of computation. By comparing real and complex analysis we will discuss if there will be a similar shift from classical to quantum computers. What if today someone shows that P does not equal NP for a classical computer? Would we really be happy that the intractability of NP- complete problems had been shown?

QC opens an entire bag of worrying about the foundations of computational complexity.

## Timetable

The most recent timetable can be found at the students' website.

## Mode of instruction

Lectures and assignments.

## Course load

Hours of study: 84 (= 3 EC)

Lectures 26:00 hrs

Practical work 6:00 hrs

Examination 3:00 hrs

Self-study: 49 hrs

## Assessment method

Exam and assignments

The course grade will be determined by your work on the assignments and the final exam grade (details will be provided on the first day of class).

## Reading list

References:

Eleanor Rieffel and Wolfgang Polak, Quantum Computing, the MIT Press, 2011, isbn 978-0-262-01506-6

Michael A. Nielsen and Isaac L. Chung, Quantum Computing and Quantum Information, reprinted 2012, Cambridge University Press, isbn 978-1-10700-217-3

Quantum Computer Science: An Introduction” by David N. Mermin, 2007, Cambridge University Press.

Adiabatic Quantum Computation and Quantum Annealing: Theory and Practice, by Catherine C. McGeoch

Handouts

## Registration

You have to sign up for courses and exams (including retakes) in uSis. Check this link for information about how to register for courses.

Please also register for the course in Blackboard as soon as the lectures has made it available.

## Contact information

Lecturer: dr. Florian Neukart

Website: Blackboard