Microwave Inductive Readout of EBL Nanobridge SQUIDs

Godfrey, Tom; Long, George; Gallop, John; Cox, D. C.; Polychroniou, Elias; Chen, Jie; Romans, E.J.; Líu, Hao

doi:10.1109/tasc.2020.2998374

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…In this paper we build upon our previous work [19] by embedding an array of rf nanobridge SQUIDs into superconducting co-planar waveguide (CPW) resonators to increase the nonlinear response and thus the flux sensitivity [20] [21]. Section II introduces the analytic theory of rf nanobridge SQUIDS embedded in CPW resonators, and Section III presents simulations showing the additional potential for exploiting parametric amplification.…”

Section: Introductionmentioning

confidence: 99%

Development of Flux-Tuneable Inductive Nanobridge SQUIDs for Quantum Technology Applications

Meti

Long

Godfrey

et al. 2023

IEEE Trans. Appl. Supercond.

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Niobium nanobridge SQUIDs have shown exceptional noise performance with potential applications in quantum information processing, weak signal detection and single spin detection where the nanobridge geometry should enable efficient electromagnetic coupling to implanted spins. Combining such devices with dispersive microwave readout circuitry allows the spin sensitivity to be further improved by overcoming the standard thermal limit. Here we report on the fabrication and dispersive microwave readout of an array of niobium nanobridge rf SQUIDs incorporated into a superconducting resonator, including the optimization of the nanobridge fabrication process by electron beam lithography. We show the measured flux-tuneability of the resonance is in good agreement with theory, and we also discuss how the nonlinearity of the weak-link in the resonator structure allows for the mediation of parametric effects to enhance performance.

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Section: Introductionmentioning

confidence: 99%

Development of Flux-Tuneable Inductive Nanobridge SQUIDs for Quantum Technology Applications

Meti

Long

Godfrey

et al. 2023

IEEE Trans. Appl. Supercond.

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RETRACTED: MSFGQ: Design of an efficient Multiparametric model for improving sub-field scheduling performance via novel GA & Q-Learning optimizations

Keswani,

Peshwe

2024

IFS

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This paper presents the design of a novel multiparametric model aimed at improving sub-field scheduling performance for lithographic processes. The proposed model incorporates various parameters such as sub-field locations, conflict analysis, critical dimensions, delay, current, voltage, dose, and depth of current for optimization of scheduling operations. To achieve this, we have utilized both Genetic Algorithm (GA) and Q-learning algorithms to optimize the scheduling performance in real-time lithographic processes. The need for this work stems from the increasing demand for high precision lithographic processes, which require efficient scheduling operations to achieve optimal results. The proposed model has been tested on real-time lithographic processes, and the results have been evaluated in terms of critical dimensions, scheduling performance, and scheduling efficiency. The results show that the proposed model has reduced critical dimensions by 8.5%, improved scheduling performance by 10.5%, and increased scheduling efficiency by 8.3% . These results demonstrate the efficacy of the proposed model in improving sub-field scheduling performance in lithographic processes. Based on the results it can be observed that this work presents a novel multiparametric model that utilizes GA and Q-learning algorithms to improve sub-field scheduling performance in lithographic processes.

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Microwave Inductive Readout of EBL Nanobridge SQUIDs

Cited by 2 publications

References 18 publications

Development of Flux-Tuneable Inductive Nanobridge SQUIDs for Quantum Technology Applications

Development of Flux-Tuneable Inductive Nanobridge SQUIDs for Quantum Technology Applications

RETRACTED: MSFGQ: Design of an efficient Multiparametric model for improving sub-field scheduling performance via novel GA & Q-Learning optimizations

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