What you will learn.

Explore quantum computing to enable calculations that are not possible with traditional computing technology.

  • What is quantum computing?

  • Classical vs Quantum Computing

  • Linear Algebra Crash Course

  • Superposition

  • Entanglement

  • Classical problems in quantum solutions

  • Quantum algorithms

  • Quantum algorithms

  • Shor’s algorithm

  • Basic quantum programming

About the Course

In this introductory course undergraduates will learn about the exciting interdisciplinary field of Quantum Computing. Students will be introduced to the foundations of quantum computing, including quantum mechanics, quantum circuits, and quantum algorithms and protocols.

This course will serve as an introduction to quantum computing. The course will not be as in-depth as a quantum computing course one could typically find within a graduate program, nor will it be as in-depth as a quantum computing course with a long list of prerequisites. This course is designed for undergraduate computer science students and will approach the subject in a way that makes it understandable for students who haven’t had extensive backgrounds in physics or math. This course will introduce you to basic quantum computing concepts, the physics behind them (including math), how quantum computers differ from classical computers, and possible ways it can change the world of computing. This course will also introduce you to basic programming with quantum computers. Grading Breakdown: Regular Assignments: 50% Tests/Quizzes: 30% Programming assignment(s): 10% Final project: 10%

Prerequisites

You may come from any field: physics, maths, computer science, electrical engineering. Strong hold on subject specific topics will be appreciated, but not necessary as we will covering all of them here-

  • Physics: Good at Quantum mechanics. At more advanced levels, various aspects of quantum information overlap with AMO, condensed matter and high energy.

  • Math: Good at linear algebra and probability.At more advanced level group and representation theory, random matrix theory and functional analysis etc. W e emphasize that most fields of math have some overlap with quantum computing.

  • Computer Science: Most theory topics are relevant although are less crucial at first: i.e. algorithms, cryptography, information theory, error-correcting codes, optimization, complexity, machine learning. If you haven't had any CS theory exposure, undergrad algorithms is a good place to start because it will show you CS-theory ways of thinking, including ideas like asymptotic analysis.

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