Information
We will offer this course again in 2021 Spring semester.
Course information  2019 Spring

Lecturers: András Pályi, Zoltán Zimborás

Responsible lecturer: András Pályi

Language: English

Location: F3212

Time: Wednesdays, 12:1513:45
Details

One goal is to provide an introduction to basic concepts of quantum information theory and computing. Another goal is to provide handson experience in programming an actual quantum computer. That is, the basic concepts, gadgets, algorithms, etc., should be implemented and run by the students themselves during the course and as homework. We will use the quantum computers of the IBM Quantum Experience project, which are available via the cloud for anyone.

Lectures will combine conventional, frontal presentation, and programming exercises. Therefore, the location is a computer lab. Of course, students are welcome to use there own laptop computers.

The main resource used for the course is the online documentations of (1) the quantum computers available through the IBM Quantum Experience project [1], and (2) the Qiskit quantum computing framework [2].

Evaluation: There is an exam at the end of the semester. You'll get a few exercises that you have to solve on the spot on your own in a 90minute time frame. Using online resources is allowed. The exercises will be similar to those on the exercise sheets published in the "Course material" table below. We suggest that you solve all exercises before the exam as a preparation. You'll get a grade based on the quality and quantity of the solutions you prepare during the exam, and based on your competence revealed at a short discussion after the exercise session.
Course material
Complete course material as a zip file.

Basics: quantum information, python, qiskit

The BernsteinVazirani quantum algorithm

Decoherence 1: the density matrix

Decoherence 2: qubit relaxation

Decoherence 3: quantum state tomography

DeutschJozsa and Grover algorithms

Quantum Fourier Transform, Phase Estimation

Shor's algorithm

Quantum Simulation

Classical Error Correction

Quantum Error Correction

Bell inequalities
List of topics

Basics: quantum information, python, and qiskit (Lecture 1, AP)

BernsteinVazirani algorithm (Lecture 2, ZZ)

Density matrix. State tomography.
Process Tomography. Relaxation. Dephasing. Decoherence. (Lectures 35, AP).

Quantum algorithms: Deutsch, Grover, Shor, quantum simulation (Lectures 69, ZZ)

Classical, hybrid, and quantum error correction using the repetition code. (Lectures 1011, AP)

Bell inequalities. Quantum teleportation. (Lecture 12, ZZ)