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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS FIZ 3122 QUANTUM COMPUTATION AND QUANTUM COMPUTERS ELECTIVE 2 2 0 7

Offered By

Physics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ÜMIT AKINCI

Offered to

Physics

Course Objective

The aim of this course is to give basic information about quantum information theory, introduce quantum computing approaches and teach the working principles of quantum computers.

Learning Outcomes of the Course Unit

1   Being able to understand the basic principles of the quantum information theory 2   Being able to identify the basic principles of quantum computation 3   Being able to understand the basic quantum algorithms, quantum logic gates and circuits 4   Being able to identify the concept of entanglement 5   Being able to identify the physical realizations of the quantum computers

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction and overview 2 Brief overview of quantum mechanics 3 Spin and qubits 4 Entanglement and Bell s Inequality 5 Classical Logic, Gates, and Circuits 6 Quantum logic gates and circuits 7 Quantum Fourier transform I 8 Quantum Fourier transform II 9 Quantum Algorthms I: Deutsch s Algorithm and The Deutsch-Jozsa Algorithm 10 Quantum Algorthms II: Quantum search algorithm (Grover's Algorithm) 11 Quantum Algorthms III: Quantum factorization algorithm (Shor's algorithm) 12 Quantum Teleportation 13 Physical realizations of quantum computers I: Conditions for quantum computation 14 Physical realizations of quantum computers II: Harmonic oscillator quantum computer and Optical photon quantum computer

Recomended or Required Reading

1)Quantum Computation and Quantum Information Michael A. Nielsen, Isaac L. Chuang, Massachusetts Institute of Technology 2010 2)Quantum Computing for Everyone Chris Bernhardt, The MIT Press, Cambridge, Massachusetts 2019 Massachusetts Institute of Technology

Planned Learning Activities and Teaching Methods

Lectures, Question-Answer, Discussion, Tutorials

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 ASG ASSIGNMENT 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG * 0.25 + FIN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG * 0.25 + RST * 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

The student s performance will be evaluated by addition of final exam grade to midterm exams grades and homeworks.

Language of Instruction

Turkish

Course Policies and Rules

Attending at least 70 percent of lectures is mandatory.

Contact Details for the Lecturer(s)

umit.akinci@deu.edu.tr

Office Hours

will be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Tutorials 14 2 28 Preparations before/after weekly lectures 12 4 48 Preparation for midterm exam 1 20 20 Preparation for final exam 1 20 20 Preparing assignments 2 16 32 Midterm 1 2 2 Final 1 2 2 TOTAL WORKLOAD (hours) 180

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 PO.14 LO.1 4 1 3 3 3 4 LO.2 4 2 2 3 4 3 4 LO.3 5 4 3 2 3 4 LO.4 3 1 3 2 3 4 LO.5 3 1 3 3 3 4