Skip to content

Latest commit

 

History

History
133 lines (87 loc) · 6.08 KB

README.md

File metadata and controls

133 lines (87 loc) · 6.08 KB
Raw

This is a demo of programming assignments developed using Q#, Azure Quantum Development Kit, and Azure Quantum that can be used to teach an "Introduction to Quantum Computing and Quantum Programming" course.

These assignments have been created and tested with Modern QDK, version 1.8.0.

Table of contents

List of programming assignments

This preview contains examples of the programming assignments included in the curriculum.

Example syllabus

Here is the syllabus of the course taught at Northeastern University in 2020.

Course Structure

  • One three-hour session per week (lecture + lab time combined); 14 weeks.
  • Weekly programming homework assignments during the first part of the course.
  • Final project during the second part of the course.

Course Outline

Week 1. Fundamentals, part 1.

  • Motivation: Why quantum computing?
  • Quick review: complex numbers, matrices and vectors, tensor product.
  • The qubit, superposition, Dirac notation, single-qubit quantum gates, entanglement.

Week 2. Fundamentals, part 2.

  • Multi-qubit quantum gates, Dirac notation for gates representation.
  • Comparison of different notations: matrix, Dirac, circuit, Q# code.
  • Measurements: single-qubit, multi-qubit, partial measurement of multi-qubit system.
  • No-cloning theorem.

Week 3. Simple algorithms.

  • Teleportation.
  • Superdense coding.
  • Quantum oracles (phase oracles).
  • Deutsch, Deutsch-Jozsa and Bernstein-Vazirani algorithms.

Week 4. Reversible computing.

  • Reversible Boolean logic.
  • Reversible circuit synthesis: converting classical functions to quantum circuits, exercises.
  • Toffoli simulator.
  • Quantum oracles: marking oracles, converting marking oracles to phase oracles.
  • Example: building oracle for SAT problems.

Week 5. Grover's search algorithm.

  • Search problem.
  • Unitary transformations used in Grover's search algorithm, their representation as reflections.
  • Grover's search algorithm, its visualization.
  • Practical aspects of using Grover's search algorithm.

Week 6. Quantum Fourier transform.

  • Definition and circuit implementation of quantum Fourier transform.
  • Examples of QFT effect on various states.

Week 7. Quantum phase estimation.

  • Linear algebra review: eigenvalues and eigenvectors.
  • Eigenvalues and eigenphases of quantum operations: properties and examples.
  • Single-bit phase estimation, measuring an operator.
  • Quantum phase estimation.
  • Application: quantum counting.

Week 8. Integer factoring (Shor's algorithm).

  • RSA review.
  • Order finding problem.
  • Integer factoring (Shor's algorithm).

Week 9. Error correction.

  • Problem description, comparison of classical and quantum information, inherent challenges of error correcting quantum information.
  • Joint measurements.
  • Simple error correction codes: bit-flip, sign-flip, Shor's code.
  • Fault-tolerant quantum computation.

Week 10. Applications overview.

  • True random number generation.
  • Quantum cryptography, quantm key distribution, example: BB84 protocol.
  • Quantum machine learning, example: quantum perceptron.
  • Quantum simulation.

Week 11. Building a full-stack quantum computer.

  • Software and hardware stack necessary to build a viable quantum computing system.

The last week(s) are used for students' presentations of their final projects.

Use Azure Quantum in your course

Microsoft offers several credits programs to support using Azure Quantum in the classroom.

Experience reports

The first version of the curriculum relying on this kind of assignments was piloted in a University of Washington course taught by Microsoft Quantum team in 2019. You can read about this experience in the paper "Teaching Quantum Computing through a Practical Software-driven Approach: Experience Report" by Mariia Mykhailova, Krysta M. Svore.

Later, similar programming assignments have been used in Northeastern University courses in 2020-2024. You can read about this experience in the paper "Teaching Quantum Computing using Microsoft Quantum Development Kit and Azure Quantum" by Mariia Mykhailova.

We shared our curriculum with multiple university partners who used the materials to teach their own versions of this course. You can read more about the experience of one of our partners, University of Montevideo, in the paper "Quantum Computing for Undergraduate Engineering Students: Report of an Experience" by Laura Gatti, Rafael Sotelo.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.