University of Technology Sydney

41174 Quantum Algorithms

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UTS: Information Technology: Computer Science
Credit points: 6 cp

Subject level:

Undergraduate

Result type: Grade and marks

Requisite(s): 41076 Methods in Quantum Computing

Description

Students will develop an understanding of the most famous quantum algorithms, including Shor’s efficient quantum algorithm for integer factorisation and Grover’s search algorithm. Students will also be introduced to algorithms based on quantum walks, an analog of random walks, algorithms for simulating quantum systems, and quantum algorithms for solving systems of linear equations. Further applications of these algorithms to optimisation and machine learning will be discussed.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Write algorithms in the quantum circuit model. (D.1)
2. Apply the quantum algorithms learned to new problems and describe solutions. (C.1)
3. Demonstrate and communicate limitations of quantum algorithms. (E.1)

Course intended learning outcomes (CILOs)

This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):

  • Design Oriented: FEIT graduates apply problem solving, design and decision-making methodologies to develop components, systems and processes to meet specified requirements. (C.1)
  • Technically Proficient: FEIT graduates apply abstraction, mathematics and discipline fundamentals, software, tools and techniques to evaluate, implement and operate systems. (D.1)
  • Collaborative and Communicative: FEIT graduates work as an effective member or leader of diverse teams, communicating effectively and operating within cross-disciplinary and cross-cultural contexts in the workplace. (E.1)

Teaching and learning strategies

There will be 2 hours per week of lecture, interspersed with simple problems for the students to answer for further discussion. One hour per week will be spent in tutorial. The tutorial will begin with a short quiz to check understanding. The quiz will then be discussed. The rest of the time in tutorial will be spent working in groups on the weekly problem set. Working in groups will allow students to practise explaining their ideas to others. The instructor will go around and provide assistance in this time, and bring the class together for further discussion of any issues that come up. The problem sets will be turned in the following week. Feedback will be given both through the quiz and grading of the problem sets.

The last 3 weeks of class, students will work in groups on a project. For this project they will pick a topic from a given list, or choose their own with approval. This topic will cover a quantum algorithm not discussed in lecture, but for which the course has prepared them to understand with the necessary background. Students will work in groups to prepare a written report that explains this algorithm in their own words and gives a full analysis of its complexity.

Content (topics)

  1. Review of quantum circuits
  2. Fourier Transform
  3. Shor’s integer factorisation algorithm
  4. Extension of Shor to the hidden subgroup problem
  5. Grover’s search algorithm
  6. Quantum query complexity
  7. Lower bound techniques (polynomial and adversary methods)
  8. Quantum walks
  9. Hamiltonian simulation
  10. Quantum algorithms for solving systems of linear equations
  11. Quantum complexity theory

Assessment

Assessment task 1: Tutorial Quiz

Intent:

Quizzes will be given online and will consist of simple questions to ensure that students can benchmark their understanding of concepts.

Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

1 and 2

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

C.1 and D.1

Type: Quiz/test
Groupwork: Individual
Weight: 30%
Length:

15 minutes

Assessment task 2: Problem Sets

Intent:

Encourage students to engage in the topics more deeply by giving more in-depth and open-ended problems for them to solve.

Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

1, 2 and 3

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

C.1, D.1 and E.1

Type: Exercises
Groupwork: Group, individually assessed
Weight: 30%
Length:

3-5 problems, with 100-200 words describing the solution approach for each problem

Assessment task 3: Project Report

Intent:

To allow students to apply their knowledge to a new scenario.

Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

1, 2 and 3

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

C.1, D.1 and E.1

Type: Report
Groupwork: Group, individually assessed
Weight: 40%
Length:

2000 words

Minimum requirements

To pass this subject, students must achieve an overall mark of 50% or greater.

Recommended texts

Lecture notes of Andrew Childs: https://www.cs.umd.edu/~amchilds/qa/

Lecture notes of Ronald de Wolf: https://homepages.cwi.nl/~rdewolf/qcnotes.pdf