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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

Finding operation points example

In this video, we discuss a particular example, where we try to use the features of a charge stability diagram to find operation points where the gate voltages can be set to, to perform quantum operations. One such operation may involve crossing a particular transition line to load electrons into the array. Another such operation may bring two of the electrons together by flattening the shape of the potential well, such that they interact and a quantum gate is performed. We will see that in our example, these actions boil down to finding the boundaries of the charge stability diagram, which can be simplified using ML and optimization techniques.

Prerequisite knowledge

  • Spin qubits
  • Qubit decoherence
  • Quantum dot qubits
  • Operations on spin qubits
  • Capturing a Single Electron

Main takeaways

Combined with fast measurement, a computer can autonomously navigate a potential landscape and decide where to take the next measurements.

Instead of deciding on the next point to measure using heuristics, a computer can decide based on where the most information gain can occur. This can help make the tuning process faster, especially when taking measurements is expensive time-wise.