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
2,853 already enrolled
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Skills you'll gain
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
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Recommended if you're interested in Algorithms
Stanford University
Vanderbilt University
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