Loss estimation using Energy Participation Ratio in KQCircuits
ORAL
Abstract
With the introduction of pyEPR, users may with ease estimate qubit parameters, such as, energy levels and effects of material losses. Adding on top of existing automated simulations provided by KQC, pyEPR is seamlessly integrated into the workflow. A design from KQC can be exported to a pyEPR-compatible format and used in optimising the design.
In this work we study the contribution of two-level system losses in various interfaces to the quality factor of superconducting resonators and compare to measurements in order to extract scaling behaviour. We further apply the results to analyse real-world qubit geometries, demonstrating how this tool can facilitate the further development of high-coherence superconducting quantum devices.
[1] J. Heinsoo et al., ‘KQCircuits’. IQM Finland, Jun. 2021. GPLv3. doi: 10.5281/zenodo.4944796.
[2] Z. K. Minev et al., ‘pyEPR’. May. 2021. BSD. doi: 10.5281/zenodo.4744448.
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Publication: N. Savola, 'Design and modelling of long-coherence qubits' [Unpublished M.Sc. thesis], Aalto University, Espoo, Finland, 2023.
Presenters
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Niko Savola
IQM Quantum Computers, IQM Finland Oy
Authors
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Niko Savola
IQM Quantum Computers, IQM Finland Oy
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Alessandro Landra
IQM Quantum Computers, IQM Finland Oy
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Jukka Räbinä
IQM, IQM Quantum Computers, IQM Finland Oy
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Eelis Takala
IQM Quantum Computers
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Janne Kotilahti
IQM Quantum Computers, IQM Finland Oy
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David Janzso
IQM Quantum Computers, IQM Finland Oy
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Pavel Smirnov
IQM Quantum Computers, IQM Finland Oy
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Vladimir Milchakov
IQM Quantum Computers
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Kristinn Juliusson
IQM Quantum Computers
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Sinan Inel
IQM Quantum Computers
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Máté Jenei
IQM Quantum Computers, IQM
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Johannes Heinsoo
IQM Quantum Computers, IQM Finland Oy, IQM
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Caspar Ockeloen-Korppi
IQM Quantum Computers, IQM Finland Oy