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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2024/2025
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Welcome page > Faculty of Information Technology > Department of Applied Mathematics > Quantum algorithms and programming

Quantum algorithms and programming

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Code Completion Credits Range Language
BI-QAP KZ 5 1P+2C Czech
Garant předmětu:
Ivo Petr
Lecturer:
Tomáš Kalvoda, Ivo Petr
Tutor:
Tomáš Kalvoda, Ivo Petr
Supervisor:
Department of Applied Mathematics
Synopsis:

Course aims at giving students hands-on experience with quantum computers and their programming. We focus on fundaments of quantum mechanics, on which quantum technologies are based, and algorithms showing advantages and limitations of quantum computing. During tutorials students work in open-source software development kit Qiskit, which is based on Python language.

Knowledge of linear algebra at the level of BI-LA1 and BI-LA2 (or BI-LIN) is necessary. Previous completion of BI-MA2 or BI-VMM and experience with Python might be an advantage. No previous knowledge of physics is assumed.

Requirements:

Knowledge of linear algebra at the level of BI-LA1 and BI-LA2 (or BI-LIN) is necessary. Previous completion of BI-MA2 or BI-VMM and experience with Python might be an advantage. No previous knowledge of physics is assumed.

Syllabus of lectures:

1.Motivation for quantum technologies, difference between classical and quantum mechanics, first contact with Qiskit software development kit

2.State of quantum system, probablistic and quantum bits, superposition

3.Measurement, state of quantum system, Bloch sphere, unitarity of time evolution

4.One-qubit gates as rotations, measurement in general basis, quantum key distibution and protocol BB84

5.Two-qubit quantum register, entanglement, Bell (EPR) states

6.Two-qubit gates and their composition, no-cloning theorem

7.Superdense coding, general quantum register and gates, quantum teleportation

8.Quantum circuits, universal quantum computer

9.Simple quantum algorithms (Deutsch–Jozsa)

10.Quantum Fourier Transform

11.Quantum Phase Estimation

12.Variational methods and solution of linear systems of equations, quantum technologies and machine learning

Syllabus of tutorials:

Tutorials follow lectures and consist of solving tasks using Qiskit.

Study Objective:
Study materials:

1.M. A. Nielsen, I. L. Chuang, Quantum computation and quantum information, Cambridge Univ. Press, 2013.

2.Learn Quantum Computation using Qiskit: https://qiskit.org/textbook

Note:
Further information:
http://courses.fit.cvut.cz/BI-QAP/
Time-table for winter semester 2024/2025:
Time-table is not available yet
Time-table for summer semester 2024/2025:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2024-06-16
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