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2021 Faculty Courses School of Computing Department of Mathematical and Computing Science Graduate major in Mathematical and Computing Science

Quantum Computation and Quantum Information

Academic unit or major
Graduate major in Mathematical and Computing Science
Instructor(s)
Ryuhei Mori
Class Format
Lecture
Media-enhanced courses
-
Day of week/Period
(Classrooms)
5-6 Tue / 5-6 Fri
Class
-
Course Code
MCS.T413
Number of credits
200
Course offered
2021
Offered quarter
3Q
Syllabus updated
Jul 10, 2025
Language
English

Syllabus

Course overview and goals

With the progress of quantum information technology in recent years, learning the fundamentals of quantum information processing has become increasingly important. This course deals with the fundamentals of quantum mechanics based on linear algebra and information processing using quantum mechanics. Students learn the fundamentals of computation and communication based on quantum mechanics.

Course description and aims

The followings are student learning outcomes.
(1) Fundamentals of quantum mechanics based on linear algebra.
(2) Understanding of quantum mechanics based on nonlocality.
(3) Basic quantum information processing such as quantum teleportation.
(4) Fundamentals of quantum computation using quantum circuits.
(5) Basic quantum algorithms such as phase estimation, Shor's algorithm, Grover's algorithm etc.

Keywords

Quantum computation, quantum information

Competencies

  • Specialist skills
  • Intercultural skills
  • Communication skills
  • Critical thinking skills
  • Practical and/or problem-solving skills

Class flow

Lecture Videos are uploaded to YouTube. All documents used in the lectures are uploaded to GitHub. Students can communicate with lecturer on Slack. Assignments are given in each class.

Course schedule/Objectives

Course schedule Objectives
Class 1

Quantum theory: Quantum states and quantum measurements, Bell test

Exercises on formulation of quantum theory

Class 2

Single qubit: Bloch sphere, unitary operators, universality of single qubit gate

Calculations of unitary operation on single qubit

Class 3

Two and more qubits: Tensor product, entanglement, Schmidt decomposition

Calculations of unitary operation on two and more qubits

Class 4

Spectral decomposition, purification and superdense coding

Exercises on spectral decomposition and purification

Class 5

Quantum teleportation

Exercises on partial measurement of quantum state in joint system

Class 6

Nonlocality: Bell's inequality, GHZ paradox, XOR games

Calculations of the winning probability of XOR games

Class 7

Discrimination of quantum states: Holevo--Helstrom theorem, trace norm

Calculation of trace norm

Class 8

Quantum cryptography: BB84, bit commitment

Exercises on quantum cryptography

Class 9

Quantum circuit: Deutch--Josza algorithm

Calculations of the output state of quantum circuits

Class 10

Universality of quantum circuit 1

Design of quantum circuits

Class 11

Universality of quantum circuit 2

Design of quantum circuits

Class 12

Quantum phase estimation

Analysis of quantum phase estimation

Class 13

Shor's algorithm

Derivation of eigenvector of unitary operators

Class 14

Grover's algorithm and its optimality

Proofs on generalizations of Grover's algorithm

Study advice (preparation and review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

None required.

Reference books, course materials, etc.

Michael A. Nielsen and Isaac L. Chuang, "Quantum Computation and Quantum Information," 10th Anniversary edition, Cambridge University Press 2010.

Evaluation methods and criteria

Assignments: 40%, Online final exam: 60%

Related courses

  • MCS.T203 : Linear Algebra and Its Applications

Prerequisites

There is no condition for taking this class. But, it requires sufficient understanding of linear algebra.