(Invited) Predictive analytics for cryogenic CMOS in future quantum computing systems

This paper presents predictive techniques that suggest a path to accelerated analysis and optimization of the yield of ultra-low power analog/mixed signal designs operating at cryogenic temperatures for use in future quantum computing applications. Analysis of 6σ variation is accelerated using mixtu...

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Bibliographic Details
Published in2023 60th ACM/IEEE Design Automation Conference (DAC) pp. 1 - 4
Main Authors Joshi, Rajiv V., Chakraborty, Sudipto
Format Conference Proceeding
LanguageEnglish
Published IEEE 09.07.2023
Subjects
6σ analysis
CMOS technology
cryogenic CMOS
Cryogenics
High dynamic range
mixture important sampling
Monte Carlo methods
Quantum computing
quantum controller
spurious levels
System-on-chip
ultra-low power
Uncertainty
yield
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DOI10.1109/DAC56929.2023.10247978

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Summary:This paper presents predictive techniques that suggest a path to accelerated analysis and optimization of the yield of ultra-low power analog/mixed signal designs operating at cryogenic temperatures for use in future quantum computing applications. Analysis of 6σ variation is accelerated using mixture importance sampling (MixIS) techniques, with key studied specifications being compliance to spurious tone requirements at the quantum state controller output and optimization of design power consumption, both in the context of the high levels of modeling and matching uncertainties associated with cryogenic circuit design.
DOI:10.1109/DAC56929.2023.10247978