Quantum Hardware and its Applications with Quantum Inspire
Dear learners,
Welcome to the final part of the Program Quantum 301: Quantum Computing with Semiconductor Technology.
Now that you have concretely seen how to use machine learning to improve semiconductor-based quantum devices, we now focus on germanium-based devices. This course introduces you to a variety of topics on germanium-based quantum technologies and their applications, from constructing a single spin qubit and scaling spin-qubit-based quantum computers to single and two-qubit gates, and finally to practical quantum algorithms. The course also includes some perspectives on quantum simulations and quantum machine learning. Qubits are the fundamental unit for any quantum computer, and this course begins with an introduction to spin qubits in germanium platforms. You will explore all the building blocks for a spin-qubit-based quantum computer: creating a spin qubit, scaling the number of spin qubits, tuning of spin qubits, single and multi-qubit quantum gates, quantum error correction and also electronics to control these quantum devices. You will finally learn about the potential applications of these technologies, including the execution of quantum algorithms, quantum machine learning, and simulations based on quantum annealing.
Please note: this is an advanced course. We expect you to have followed the previous courses offered by QuTech Academy, namely:
If you have already followed some other courses about Quantum Computing, you can check the Syllabus and make sure that your prior knowledge is sufficient to follow the course. If you don’t feel confident about some of the topics, join the previous courses and come back later!
The course is a journey of discovery, so we encourage you to bring your own experiences, insights and thoughts via the forum. Our Community TAs will be available during working days to support you. We aim to answer all your questions within 48 hours.
We hope you enjoy the course with us!
Kind Regards,
The Course Team
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