Difference between revisions of "BSTE:IntroductionToQuantumProgramming"

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==== Topics covered in this section: ====
 
==== Topics covered in this section: ====
   
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* Метод главных компонент на QPU
* TODO
 
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* Метод опорных вектором на QPU
   
 
==== What forms of evaluation were used to test students’ performance in this section? ====
 
==== What forms of evaluation were used to test students’ performance in this section? ====

Revision as of 12:50, 11 October 2021

Introduction to Quantum Programming

  • Course name: Introduction to Quantum Programming
  • Course number: N/A

Course Characteristics

What subject area does your course (discipline) belong to?

Quantum computing

Key concepts of the class

  • Quantum computer
  • Quantum circuit
  • Quantum optimization

What is the purpose of this course?

The goal of the course is to equip students with the skills to develop quantum algorithms using modern development tools for simulators and real computing systems. These skills include, but are not limited to, the qiskit programming language and its libraries, and universal quantum notation.

After mastering the course the student should be aware of ways to develop quantum algorithms, should be able to develop simple quantum circuits from scratch and integrate them into classical software, should be able to compose sequences of quantum circuits that solve computational and machine learning problems.

Course objectives based on Bloom’s taxonomy

- What should a student remember at the end of the course?

By the end of the course, the students should be able to remember and recognize

  • basics of quantum computing
  • definition of quantum state and quantum gate
  • basic quantum gates
  • basic quantum subprograms

- What should a student be able to understand at the end of the course?

By the end of the course, the students should be able to describe and explain

  • terms of quantum computing
  • solving applied problems in quantum computer

- What should a student be able to apply at the end of the course?

By the end of the course, the students should be able to

  • write an algormithm in qiskit progamming language
  • run an algorithm in simulator
  • run an algorithm in real quantum computer

Course evaluation

Course grade breakdown
Proposed points
Labs/seminar classes 0
Interim performance assessment 20
Assessments 60
Exams 20

If necessary, please indicate freely your course’s features in terms of students’ performance assessment:

Students pass 3 homeworks 20 points each. 20 points are given for in-class performance (solving the labs and whiteboard examples). 20 points go to the exam.

Grades range

Course grading range
Proposed range
A. Excellent 80-100
B. Good 65-79
C. Satisfactory 50-64
D. Poor 0-49

Resources and reference material

Main textbook:

Other reference material:

Course Sections

The main sections of the course and approximate hour distribution between them is as follows:

Course Sections
Section Section Title Teaching Hours
1 Single qubit 12
2 2 qubit operations 8
3 quantum data representation 10
4 quantum building blocks 4
5 quantum optimization and machine learning 6

Section 1

Section title:

Single Qubit

Topics covered in this section:

  • Кубит, суперпозиция и квантовые состояния, однокубитные операции, кубит, вектор квантового состояния, кет-нотация, однокубитные гейты NOT, READ, WRITE, HADAMARD, ROT, PHASE


What forms of evaluation were used to test students’ performance in this section?

Yes/No
Development of individual parts of software product code 1
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 1
Oral polls 0
Discussions 0

Typical questions for ongoing performance evaluation within this section

  1. TODO
  2. TODO

Typical questions for seminar classes (labs) within this section

  1. TODO

Test questions for final assessment in this section

  1. TODO

Section 2

Section title:

2 qubit operations

Topics covered in this section:

  • многокубитные операции CNOT, Toffoli, CPHASE, CZ, SWAP


What forms of evaluation were used to test students’ performance in this section?

Yes/No
Development of individual parts of software product code 1
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 0
Oral polls 0
Discussions 0

Typical questions for ongoing performance evaluation within this section

  1. TODO
  2. TODO

Typical questions for seminar classes (labs) within this section

  1. TODO

Test questions for final assessment in this section

  1. TODO
  2. TODO

Section 3

Section title:

Quantum data representation

Topics covered in this section:

  • Квантовая память
  • Кодирование векторов
  • Кодирование матриц

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Development of individual parts of software product code 1
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 0
Oral polls 0
Discussions 0

Typical questions for ongoing performance evaluation within this section

  1. TODO

Typical questions for seminar classes (labs) within this section

  1. TODO

Test questions for final assessment in this section

  1. TODO

Section 4

Section title:

Quantum programming building blocks

Topics covered in this section:

  • Квантовая телепортация
  • Арифметика QPU
  • Усиление комплексной амплитуды
  • Квантовое преобразование Фурье
  • Квантовая оценка фазы
  • Алгоритм Гровера
  • Алгоритм Шора

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Development of individual parts of software product code 1
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 0
Oral polls 0
Discussions 0

Typical questions for ongoing performance evaluation within this section

  1. TODO

Typical questions for seminar classes (labs) within this section

  1. TODO

Test questions for final assessment in this section

  1. TODO

Section 5

Section title:

Quantum optimization and machine learning

Topics covered in this section:

  • Метод главных компонент на QPU
  • Метод опорных вектором на QPU

What forms of evaluation were used to test students’ performance in this section?

Yes/No
Development of individual parts of software product code 1
Homework and group projects 1
Midterm evaluation 0
Testing (written or computer based) 0
Reports 0
Essays 0
Oral polls 0
Discussions 0

Typical questions for ongoing performance evaluation within this section

  1. TODO

Typical questions for seminar classes (labs) within this section

  1. TODO

Test questions for final assessment in this section

  1. TODO