Towards Si finFET quantum devices with reproducible behavior
ORAL
Abstract
Hole spin qubits in Si finFETs show great promise for a quantum computing platform exhibiting fast and all electrical qubit control, even when operated at temperatures above 1K. While charge noise affects all platforms, disorder is one of the main limitations in current Si-MOS qubit technology.
Here, we present our work towards reducing disorder and trapped charges by investigating material stacks utilizing Hall bar and percolation density measurements. Additionally, fabricating quantum dot devices with ultra-small gate length and pitch will enable a path towards mitigating disorder. We show Si finFET quantum dot devices exhibiting sub 20 nm gate lengths with a small pitch, fabricated with high-resolution e-beam lithography. The reproducibility of quantum dot formation is assessed through transport measurements, RF gate reflectometry, and charge sensing. From these results we draw conclusions on gate stack and fin shape optimization.
Here, we present our work towards reducing disorder and trapped charges by investigating material stacks utilizing Hall bar and percolation density measurements. Additionally, fabricating quantum dot devices with ultra-small gate length and pitch will enable a path towards mitigating disorder. We show Si finFET quantum dot devices exhibiting sub 20 nm gate lengths with a small pitch, fabricated with high-resolution e-beam lithography. The reproducibility of quantum dot formation is assessed through transport measurements, RF gate reflectometry, and charge sensing. From these results we draw conclusions on gate stack and fin shape optimization.
*This work was supported as a part of NCCR SPIN, a National Centre of Competence (or Excellence) in Research, funded by the Swiss National Science Foundation (grant number 51NF40-180604). Additionally, this work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 899018.
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Presenters
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Matthias Mergenthaler
- IBM Research Europe - Zurich