This course is aimed at first year undergraduates to experienced researchers looking for an overview of quantum computing and a more detailed understanding of quantum error correction, with specific focus on the type of quantum error correction successfully demonstrated in 2024 at Google. Questions and projects are provided to build familiarity with the theory and software tools used in the field. The course starts with an overview of various quantum computing technologies, followed by detailed sections on quantum states and circuits, quantum errors and error detection, the mathematical formalism of stabilizers and the surface code, and finally the software tools Stim and Crumble, both of which are actively used by researchers in the field.
Hands-on quantum error correction with Google Quantum AI
Instructor: Dr. Austin Fowler
11,381 already enrolled
(73 reviews)
Recommended experience
Details to know
December 2024
8 assignments
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There is 1 module in this course
By the end of this course, you'll have implemented the surface code, a leading error correcting code in quantum computing. Additionally, you'll have used our library Stim to simulate your code many times, and used the results to estimate the theoretical hardware error rate required to achieve robust error correction.
What's included
9 videos9 readings8 assignments2 ungraded labs
Instructor
Offered by
Recommended if you're interested in Algorithms
Fractal Analytics
University of Maryland, College Park
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Reviewed on Dec 14, 2024
The fundamental principles of quantum error correction (QEC) are presented with remarkable clarity and precision. Let's hope for a future module on "Magic state cultivation" as a Christmas gift ;)
Reviewed on Dec 16, 2024
AWESOME COURSE MATERIAL. Wish more and more like this in future which more closer to practical quantum computing applications.
Reviewed on Dec 16, 2024
Very good overview of how error detection works in the quantum world.
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