Emerging Technologies
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Quantum Computer Systems Design II: Principles of Quantum Architecture

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Course Features

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Duration

4 weeks

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Effort

12 hours per week

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Teaching Type

Self Paced

Course Description

This quantum computing course explores the basic design principles of today's quantum computer systems. In this course, students will learn to work with the IBM Qiskit software tools to write simple programs in Python and execute them on cloud-accessible quantum hardware. Topics covered in this course include:

  • Introduction to systems research in quantum computing
  • Fundamental rules in quantum computing, Bloch Sphere, Feynman Path Sum
  • Sequential and parallel execution of quantum gates, EPR pair, no-cloning theorem, quantum teleportation
  • Medium-size algorithms for NISQ (near-term intermediate scale quantum) computers
  • Quantum processor microarchitecture: classical and quantum control
  • Quantum program compilation and qubit memory management

Keywords: quantum computing, computer science, linear algebra, compiler, circuit optimization, python, qiskit, quantum algorithms, quantum technology, superposition, entanglement, qubit technology, superconducting qubit, transmon qubit, ion-trap qubit, photonic qubit, real quantum computers

Course Overview

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International Faculty

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Post Course Interactions

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Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Introduction to Quantum Computing for Everyone (Part 1 and Part 2)

Module I (Intro to Quantum Computation and Programming)

What You Will Learn

Develop unique skills to be more competitive in seeking a position in quantum software development

Learn examples of how classical software techniques can be applied to make quantum systems more reliable and efficient

Learn how to apply several classical software techniques to improve quantum hardware reliability and performance

Learn how to think about the overall design of a quantum system and how the software and hardware work together

Understand design principles of full-stack quantum software design

Understand several examples of quantum system inefficiencies

Course Instructors

Casey Duckering

Co-Instructor

Casey Duckering is a Ph.D. student at the University of Chicago advised by Prof. Chong. Casey has received B.S. degrees in Electrical Engineering and Computer Science (EECS) and Mechanical Engineerin...

Fred Chong

Seymour Goodman Professor of Computer Architecture

Fred Chong is the Seymour Goodman Professor in the Department of Computer Science at the University of Chicago and the Chief Scientist at Super.tech. He is also Lead Principal Investigator for the EP...

Jonathan Baker

Co-Instructor

Jonathan Baker is a graduating Ph.D. student at the University of Chicago advised by Prof. Chong. Previously Baker received a B.S. in Chemistry and Mathematics and a B.S. in Computer Science from Uni...

Yongshan Ding

Assistant Professor of Computer Science

Yongshan Ding is an Assistant Professor of Computer Science at Yale University. Ding received his Ph.D. from the University of Chicago and his B.Sc. from Carnegie Mellon University. His research focu...
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