Course Identification

Title:

Introduction to Quantum Computing

Code:

20194271

Lecturers and Teaching Assistants

Lecturers:

Prof. Zvika Brakerski

TA's:

Dr. Itamar Vigdorovich, Venkata Koppula

Course Schedule and Location

Year:

2019

Semester:

First Semester

When / Where:

Wednesday, 16:15 - 18:00, Ziskind, Rm 1

First Lecture:

07/11/2018

Field of Study, Course Type and Credit Points

Mathematics and Computer Science: Lecture; Elective; 2.00 points

Comments

"There will be no class on November 14th and November 28th. Make-up classes are tentatively set for MONDAYs November 19th and November 26th, at the same time 16:15-18:00, in Ziskind 155. Note that this means there will be no class on the week of November 14th and two classes on Monday and Wednesday of the following week."

Prerequisites

1. Basic (undergraduate level) classical complexity theory: the boolean circuit model, probabilistic computation, analysis of algorithms, oracle machines.

2. Basic (undergraduate level) linear algebra: vectors, matrices, eigenvalues, unitary transformations, norms.

3. Basic (undergraduate level) probability theory.

4. Very basic algebra: familiarity with group terminology.

No background in physics or quantum mechanics is needed.

Restrictions

Participants:

100

Language of Instruction

English

Attendance and participation

Expected and Recommended

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

Interim:

20%

Final:

80%

Evaluation Type

Take-home exam

Scheduled date 1

Date / due date

N/A

Location

N/A

Time

-

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

4

Syllabus

This is a basic class in quantum computing, covering basic definitions and algorithms.

1. The quantum model: superposition, measurement, density matrices.

2. Quantum circuits and quantum gates.

3. Effects of quantum entanglement: teleportation, superdense coding, the CHSH game.

4. Quantum algorithms: Grover's algorithm, Shor's algorithm, hidden subgroup problems.

5. The dihedral coset problem: Definition, Kuperberg's algorithm, relation to lattice problems.

6. Quantum cryptography: key distribution, quantum one-time pad, and possibly other aspects.

Learning Outcomes

Upon successful completion of the course the students will be able to:

* Understand of the quantum computational model.

* Get familiarity with quantum algorithms.

Reading List

Most of the lectures will be based on lecture notes by de Wolf: https://homepages.cwi.nl/~rdewolf/qcnotes.pdf .

The main textbook for reference is "Quantum Computation and Quantum information" by Nielsen and Chuang.

A small fraction of the course material is not covered by these resources. Relevant paper citations will be given in class.

Website

N/A