Scalable and high-sensitivity readout of silicon quantum devices
Simon Schaal
Quantum computing is predicted to provide unprecedented enhancements in computational power. A quantum computer requires implementation of a well-defined and controlled quantum system of many interconnected qubits, each defined using fragile quantum states. The interest in a spin-based quantum computer in silicon stems from demonstrations of very long spin-coherence times, high-fidelity single spin control and compatibility with industrial mass-fabrication. Industrial scale fabrication of the silicon platform offers a clear route towards a large-scale quantum computer, however, some of the processes and techniques employed in qubit demonstrators are incompatible with a dense and foundry-fabricated architecture. In particular, spin-readout utilises external sensors that require nearly the same footprint as qubit devices. In this thesis, improved readout techniques for silicon quantum devices are presented and routes towards implementation of a scalable and high-sensitivity readout architecture are investigated. Firstly, readout sensitivity of compact gate-based sensors is improved using a high-quality factor resonator and Josephson parametric amplifier that are fabricated separately from quantum dots. Secondly, an integrated transistor-based control circuit is presented using which sequential readout of two quantum dot devices using the same gate-based sensor is achieved. Finally, a large-scale readout architecture based on random-access and frequency multiplexing is introduced. The impact of readout circuit footprint on readout sensitivity is determined, showing routes towards integration of conventional circuits with quantum devices in a dense architecture, and a fault-tolerant architecture based on mediated exchange is introduced, capable of relaxing the limitations on available control circuit footprint per qubit. Demonstrations are based on foundry-fabricated transistors and few-electron quantum dots, showing that industry fabrication is a viable route towards quantum computation at a scale large enough to begin addressing the most challenging computational problems.
•Jan 28, 2020•0 citations