Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 74 tok/s
Gemini 2.5 Pro 55 tok/s Pro
GPT-5 Medium 19 tok/s Pro
GPT-5 High 24 tok/s Pro
GPT-4o 109 tok/s Pro
Kimi K2 212 tok/s Pro
GPT OSS 120B 464 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Reducing charge noise in quantum dots by using thin silicon quantum wells (2209.07242v1)

Published 15 Sep 2022 in cond-mat.mes-hall

Abstract: Charge noise in the host semiconductor degrades the performance of spin-qubits and poses an obstacle to control large quantum processors. However, it is challenging to engineer the heterogeneous material stack of gate-defined quantum dots to improve charge noise systematically. Here, we address the semiconductor-dielectric interface and the buried quantum well of a ${28}$Si/SiGe heterostructure and show the connection between charge noise, measured locally in quantum dots, and global disorder in the host semiconductor, measured with macroscopic Hall bars. In 5 nm thick ${28}$Si quantum wells, we find that improvements in the scattering properties and uniformity of the two-dimensional electron gas over a 100 mm wafer correspond to a significant reduction in charge noise, with a minimum value of 0.29$\pm$0.02 $\mu$eV/sqrt(Hz) at 1 Hz averaged over several quantum dots. We extrapolate the measured charge noise to simulated dephasing times to cz-gate fidelities that improve nearly one order of magnitude. These results point to a clean and quiet crystalline environment for integrating long-lived and high-fidelity spin qubits into a larger system.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube