Course information  2023 Spring semester

Lecturers: András Pályi, Zoltán Zimborás

Responsible lecturer: András Pályi

Language: English

Location: F building, 2nd floor, lecture hall 13 (F3213)

Time: Wednesdays, 8:3010:00  first lecture: Mar 1 Wednesday.
Details

Handson quantum computing. One goal is to introduce 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, partly during the lectures, partly as homework. We will use the quantum computers of the IBM Quantum Experience project, which are available via the cloud for anyone.

Lectures. Lectures will combine conventional, frontal presentation, and programming exercises.

Assignments. At each lecture, a number of programming exercises are assigned. You will have to submit your solution (pdf version of your jupyter notebook) until the Sunday following the lecture via Teams. These assignments are mandatory, but they do NOT count in your final evaluation (see below).

Resources. The main resources used for the course are the online documentations of (1) the quantum computers available through the IBM Quantum Experience project, https://quantumcomputing.ibm.com, and (2) the Qiskit quantum computing framework, https://qiskit.org.

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 the exercises assigned at the lectures. 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 of 2019 as a zip file. This is just for orientation, major updates in 2023 might follow.

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

Quantum Key Distribution
Further topics
May be covered, time permitting: readout error mitigation, superdense coding, quantum teleportation, etc.