„Kvantuminformatika” változatai közötti eltérés

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* 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.
 
* 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 [https://quantumexperience.ng.bluemix.net/qx/experience], and (2) the Qiskit quantum computing framework [https://qiskit.org/].
 
* The main resource used for the course is the online documentations of (1) the quantum computers available through the IBM Quantum Experience project [https://quantumexperience.ng.bluemix.net/qx/experience], 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. 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.
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* 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 90-minute 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 submit.
  
 
==Course material==
 
==Course material==

A lap 2019. február 26., 13:51-kori változata

Tartalomjegyzék

Quantum Information Processing

Course Information, 2019 Spring

  • Lecturers: András Pályi, Zoltán Zimborás
  • Responsible lecturer: András Pályi
  • Language: English
  • Location: F3212
  • Time: Wednesdays, 12:15-13:45

Details

  • One goal is to provide an introduction to basic concepts of quantum information theory and computing. Another goal is to provide hands-on 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 90-minute 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 submit.

Course material

# Lecture Exercises Solutions Homework Solutions
01 Basics: quantum information, python, qiskit ExercisesLecture01.pdf SolutionsLecture01.pdf SolutionsLecture01-QX.pdf
02 The Bernstein-Vazirani quantum algorithm
03 Decoherence 1: the density matrix ExercisesLecture03.pdf SolutionsLecture03.pdf
04 ... ... ... ...

List of topics

  • Basics: quantum information, python, and qiskit (Lecture 1, AP)
  • Bernstein-Vazirani algorithm (Lecture 2, ZZ)
  • Density matrix. State tomography. Process Tomography. Relaxation. Dephasing. Decoherence. (Lectures 3-5, AP).
  • Quantum algorithms: Deutsch, Grover, Shor, quantum simulation (Lectures 6-9, ZZ)
  • Classical, hybrid, and quantum error correction using the repetition code. (Lectures 10-11, AP)
  • Bell inequalities. Quantum teleportation. (Lecture 12, ZZ)