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Introduction to Quantum Computing

Learn how quantum systems are represented, measured, and interpreted.

This course introduces the foundational concepts of quantum computing by connecting classical physics with quantum state representations. You will explore polarization, photons, and qubits through interactive lessons.

Discover the Course
Quantum computing laboratory with a superconducting quantum processor, a qubit state |ψ⟩ = α|0⟩ + β|1⟩, and a Bloch sphere representation

Why This Course Matters

"This course is designed to help you build an intuitive and mathematical understanding of quantum systems. By the end, you will be able to interpret quantum states and understand how measurement works in simple systems."

Who Is This Course For?

"This course is designed for undergraduate students in Physics or Computer Science who are beginning their journey into quantum computing. It is especially suited for learners who have some familiarity with basic linear algebra and classical physics, and who want to build an intuitive understanding of how quantum systems are represented, measured, and interpreted."

Learning Objectives

What you'll achieve by the end of this module.

1

Vectors & Polarization

Represent polarization states as vectors in a given basis, drawing connections to 2D geometry.

2

State Vector Interpretation

Explain the relationship between state vectors and measurement outcomes in physical terms.

3

Measurement Probabilities

Calculate measurement probabilities mathematically using vector inner products and projections.

4

Bloch Sphere & Qubits

Interpret basic qubit states using concepts analogous to the Bloch sphere representation.

Course Structure

Module Outline

Polarization, Photons, State Vectors, and Qubits

  • 1
    Real Vectors in the Plane
  • 2
    Linear Polarization
  • 3
    Photons and Quantum Mechanics
  • 4
    Circular Polarization

About This Course

Course Author

This course was designed and developed by Milena Páez-Silva, a graduate student in the Master of Arts in Educational Innovation, Technology, and Entrepreneurship program at UNC–Chapel Hill, with a background in physics education and the integration of artificial intelligence into learning environments.

Content Sources

The instructional content in this course is based on established materials in quantum mechanics, including lecture notes and course resources from Dr. Jonathan Engel (UNC–Chapel Hill), as well as selected textbook references adapted for instructional purposes, such as Quantum Computer Science (Mermin, 2007) and Quantum Computing: A Gentle Introduction (Rieffel & Polak, 2011).

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