Corspedia | Quantum 301: Quantum Computing with Semiconductor Technology

Overview

In the race towards a fault-tolerant quantum computer, the semiconducting qubit platform is, thus far, the only one that has been shown to be scalable. Germanium qubits are a new type of semiconducting qubits, and their progress has been exceptionally fast since the development of the material in 2018.

The program “Quantum 301: Quantum Computing with Semiconductor Technology” is a combination of two advanced level courses about semiconducting quantum technologies. You will learn about the physics behind Germanium qubits, their advantages, and challenges compared to other qubit platforms, and the electrical components that are needed to control them. In addition, you will familiarize yourself with different companies from the semiconducting industry, their fabrication facilities, and the latest developments in the field. You will gain insight into how to embed machine learning into Germanium and other semiconductor qubit tuning and control workflows. You will be able to develop basic machine learning control algorithms and know how to embed them into experimental quantum computing workflow.

To benefit fully from this program, prior knowledge about different fabrication methods, in addition to the previous courses on Edx.org is recommended:

Fundamentals of Quantum Information
The Hardware of a Quantum Computer

This program is a collaboration between several parties, all of whom have state-of-the-art facilities for fabrication, control, or application of Germanium qubits. By taking this course you will have the opportunity to learn about Germanium qubits and artificial intelligence assisted qubit control from professionals in the field who are conducting innovative research that is not being done elsewhere.

Syllabus

Courses under this program:
Course 1: Machine Learning for Semiconductor Quantum Devices

Learn how to deploy artificial intelligence to control and calibrate semiconductor quantum computing chips

Course 2: Development and Applications of Germanium Quantum Technology

Unravel the physics behind Germanium qubits, their fabrication process, control, and applications. Learn how to apply machine learning for auto-tuning, and how to perform quantum error correction and quantum algorithms.

Courses

Quantum computing is a fast-growing technology and semiconductor chips are one of the most promising platforms for quantum devices.
The current bottleneck for scaling is the ability to control semiconductor computing chips quickly and efficiently.

This course, aimed at students with experience equivalent to a master’s degree in physics, computer science or electrical engineering introduces hands-on machine learning examples for the application of machine learning in the field of semiconductor quantum devices. Examples include coarse tuning into the correct quantum dot regime, specific charge state tuning, fine tuning and unsupervised quantum dot data analysis.

After the completion of the course students will be able to
1. assess the suitability of machine learning for specific qubit tuning or control task and
2. implement a machine learning prototype that is ready to be embedded into their experimental or theoretical quantum research and engineering workflow.
In the race towards a fault-tolerant quantum computer, the semiconducting qubit platform is the only one that has, thus far, been shown to be scalable. Germanium qubits are a new type of semiconducting qubits, and their progress has been exceptionally fast since the development of the material in 2018.
You will learn about the physics behind Germanium qubits, their advantages, and challenges compared to other qubit platforms, and the electrical components that are needed to control them. In addition, you will familiarize yourself with different companies from the semiconducting industry, the fabrication facilities, and the latest developments in the field.

This course is a collaboration between several parties, all of whom have state-of-the-art facilities for fabrication, control, or applications using Germanium qubits. By taking this course you will have the opportunity to learn about Germanium qubits from professionals in the field who are conducting innovative research that is not being done elsewhere.

The course is a journey of discovery, so we encourage you to bring your own experiences, insights, and thoughts via the forum!

Quantum 301: Quantum Computing with Semiconductor Technology

Brought by: edX

Overview

Syllabus

Courses

Machine Learning for Semiconductor Quantum Devices

Development and Applications of Germanium Quantum Technologies

Taught by

Quantum 301: Quantum Computing with Semiconductor Technology

Brought by: edX