Quantum Systems: Working with Noisy Systems
This course is part of Quantum Computer Systems Design.
This comprehensive course explores the fundamental design principles of modern quantum computer systems, focusing on practical skills for quantum software development. Students will learn to use IBM Qiskit software tools to write Python-based quantum programs and execute them on actual cloud-accessible quantum hardware. The curriculum covers critical topics including systems research in quantum computing, Bloch Sphere representation, sequential and parallel execution of quantum gates, EPR pairs, the no-cloning theorem, and quantum teleportation. The course places special emphasis on medium-size algorithms for NISQ (near-term intermediate scale quantum) computers, quantum processor microarchitecture with classical and quantum control elements, quantum program compilation techniques, and effective qubit memory management strategies. By completing this course, students will develop unique skills in quantum software development, understand software-hardware integration principles for quantum systems, and learn specialized techniques to improve quantum hardware reliability and performance.
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What you'll learn
Understand the design principles of full-stack quantum software systems
Master techniques to improve quantum hardware reliability and performance
Apply classical software techniques to make quantum systems more reliable
Design quantum systems with integrated software and hardware components
Write quantum programs using IBM Qiskit and execute them on cloud hardware
Work with NISQ (near-term intermediate scale quantum) algorithms
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Desktop, Mobile, Tablet
Limited Access access
Shareable certificate
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There are 3 modules in this course
This course provides a comprehensive exploration of quantum computing systems with a focus on working with noisy quantum hardware. Students will learn how to use IBM's Qiskit framework to program quantum computers and execute their code on cloud-based quantum processors. The course covers fundamental quantum computing concepts like the Bloch Sphere, Feynman Path Sum, EPR pairs, and quantum teleportation. Students will explore quantum processor microarchitecture, including both classical and quantum control elements. Special attention is given to medium-size algorithms suitable for NISQ (near-term intermediate scale quantum) computers. The course also covers critical software aspects such as quantum program compilation, circuit optimization techniques, and qubit memory management strategies. Throughout the course, students will develop practical skills to address real-world challenges in quantum computing, including techniques to improve reliability and performance of noisy quantum systems.
Intro to Quantum Computation and Programming
Module 1
Principles of Quantum Architecture
Module 2
Working with Noisy Systems
Module 3
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Quantum Computer Systems Design
Payment options
Financial Aid
Instructors
4 Courses
Quantum Computing Expert
Fred Chong is the Seymour Goodman Professor of Computer Architecture at the University of Chicago and Chief Scientist at Super.tech. He leads the EPiQC Project, an NSF Expedition in Computing focused on enabling practical-scale quantum computing. Chong has a Ph.D. from MIT and extensive experience in computer architecture, quantum computing, and sustainable computing. He has received numerous awards, including the Intel Outstanding Researcher Award, NSF CAREER award, and recognition as an ACM and IEEE Fellow. His research spans emerging technologies for computing, multicore architectures, computer security, and quantum systems design.
4 Courses
Quantum Computing Researcher
Jonathan Baker is a Ph.D. candidate at the University of Chicago, advised by Prof. Fred Chong. He holds dual B.S. degrees in Chemistry, Mathematics, and Computer Science from the University of Notre Dame. His research focuses on quantum compilation, logic synthesis, and architectural design for fault-tolerant and near-term quantum computers. Recognized with two IEEE Micro Top Picks awards, Baker has contributed significantly to advancing quantum systems and has been supported by the McCormick Fellowship.
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