Noise Optimization for MKIDs with Different Design Geometries and Material Selections

Pan, Zhaodi; Dibert, Karia; Zhang, Jianjie; Barry, Pete; Anderson, A. J.; Bender, Amy N.; Benson, Bradford A.; Cecil, Thomas W.; Chang, Clarence L.; Gualtieri, Riccardo; Li, J.; Lisovenko, Margarita; Novosad, Valentine; Rouble, Maclean; Wang, Gensheng; Yefremenko, Volodymyr

doi:10.1109/tasc.2023.3250167

Noise Optimization for MKIDs with Different Design Geometries and Material Selections

Conference · 01 August 2023

DOI:https://doi.org/10.1109/tasc.2023.3250167· OSTI ID:2427371

Pan, Zhaodi; Dibert, Karia; Zhang, Jianjie; Barry, Pete; Anderson, A. J.; Bender, Amy N.; Benson, Bradford A.; Cecil, Thomas W.; Chang, Clarence L.; Gualtieri, Riccardo; Li, J.; Lisovenko, Margarita; Novosad, Valentine; Rouble, Maclean; Wang, Gensheng; Yefremenko, Volodymyr

The separation and optimization of noise components is critical to microwave-kinetic inductance detector (MKID) development. We analyze the effect of several changes to the lumped-element inductor and interdigitated capacitor geometry on the noise performance of a series of MKIDs intended for millimeter-wavelength experiments. We extract the contributions from two-level system noise in the dielectric layer, the generation-recombination noise intrinsic to the superconducting thin-film, and system white noise from each detector noise power spectrum and characterize how these noise components depend on detector geometry, material, and measurement conditions such as driving power and temperature. We observe a reduction in the amplitude of two-level system noise with both an elevated sample temperature and an increased gap between the fingers within the interdigitated capacitors for both aluminum and niobium detectors. We also verify the expected reduction of the generation-recombination noise and associated quasiparticle lifetime with reduced inductor volume. This study also iterates over different materials, including aluminum, niobium, and aluminum manganese, and compares the results with an underlying physical model.

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Research Organization:: Argonne National Laboratory (ANL)

Sponsoring Organization:: USDOE Office of Science - Office of Basic Energy Sciences; USDOE Office of Science - Office of High Energy Physics

DOE Contract Number:: AC02-06CH11357

OSTI ID:: 2427371

Conference Information:: 2022 Applied Superconductivity Conference, 10/23/22 - 10/28/22, Honolulu, HI, US

Country of Publication:: United States

Language:: English

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