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Germanium Quantum Technology

01 /What can CMOS technology do for quantum computing? 02 /Semiconductor devices and scaling with industrial approach 03 /Semiconductor foundry facilities: the good and the bad for qubits 04 /IMEC's latest qubit developments 05 /Summary and outlook 06 /Semiconductors for spin qubits 07 /Germanium quantum wells on silicon 08 /Germanium quantum wells on silicon-germanium 09 /Growth methods 10 /Characterization techniques 11 /Electrical characterization of germanium quantum wells 12 /Fabrication of H-FET 13 /Semiconductor qubits: vision and challenges 14 /Quantum materials 15 /Quantum dot qubits and their operation 16 /Types of quantum dot qubits 17 /Qubit Readout 18 /Qubit Control 19 /Qubit Coherence and Fidelity 20 /Multi-qubit control and quantum algorithms 21 /Quantum links and scaling 22 /Physics of holes 23 /Hole spin qubits 24 /Introduction to electronics for quantum computing 25 /Room temperature electronics 26 /Cryogenic qubit chip carriers 27 /Contribution to IGNITE 28 /Quantum Control Stack for Spin Qubits 29 /Auto-tuning a quantum computer 30 /Tuning and operation of arrays 31 /Finding operation points example 32 /What is auto-tuning? 33 /Neural network tuning 34 /Navigating charge stability diagrams 35 /Experimental implementation 36 /Towards universal quantum algorithms 37 /Classical error correction 38 /Quantum error correction 39 /Progress and challenges 40 /Introduction to quantum algorithms 41 /The first algorithms 42 /Quantum annealing 43 /Quantum Machine Learning

What is auto-tuning?

This video introduces a concept of automated tuning of quantum devices and gives overview of different stages of tuning.

Prerequisite knowledge

Since you are following this course, you are probably comfortable with the concept of a quantum dot. But if you need extra refresher, you can watch this short lecture by Menno Veldhorst: https://www.qutube.nl/courses-10/quantum-computer-12/capturing-a-single-electron-334 

Main takeaways

  • Tuning, on theoretical level, always translates into optimization problem 
  • This optimization problem can manifest differently for different stages of tuning 
  • Generally tuning of quantum dots can be categorized into the following stages: initial tune-up, quantum dot configuration, charge-state calibration, fine tuning. 

Further thinking

Which of the following is NOT a desired property of an auto-tuning algorithm:

a. Can be numerical, analytical, or both
b. Requires human input.
c. Automatically adjusts controllable parameters.
d. Continuously tunes up quantum gate.

Solution

Further reading

Very nice general overview of quantum dot tuning by Justyna Zwolak and Jake Taylor https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.95.011006