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Quantum sensing of weak radio-frequency signals by pulsed Mollow absorption spectroscopy.

ABSTRACT: Quantum sensors-qubits sensitive to external fields-have become powerful detectors for various small acoustic and electromagnetic fields. A major key to their success have been dynamical decoupling protocols which enhance sensitivity to weak oscillating (AC) signals. Currently, those methods are limited to signal frequencies below a few MHz. Here we harness a quantum-optical effect, the Mollow triplet splitting of a strongly driven two-level system, to overcome this limitation. We microscopically understand this effect as a pulsed dynamical decoupling protocol and find that it enables sensitive detection of fields close to the driven transition. Employing a nitrogen-vacancy center, we detect GHz microwave fields with a signal strength (Rabi frequency) below the current detection limit, which is set by the center's spectral linewidth [Formula: see text]. Pushing detection sensitivity to the much lower 1/T ₂ limit, this scheme could enable various applications, most prominently coherent coupling to single phonons and microwave photons.Dynamical decoupling protocols can enhance the sensitivity of quantum sensors but this is limited to signal frequencies below a few MHz. Here, Joas et al. use the Mollow triplet splitting in a nitrogen-vacancy centre to overcome this limitation, enabling sensitive detection of signals in the GHz range.

SUBMITTER: Joas T

PROVIDER: S-EPMC5645369 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Quantum sensing of weak radio-frequency signals by pulsed Mollow absorption spectroscopy.

Joas T T Waeber A M AM Braunbeck G G Reinhard F F

Nature communications 20171017 1

Quantum sensors-qubits sensitive to external fields-have become powerful detectors for various small acoustic and electromagnetic fields. A major key to their success have been dynamical decoupling protocols which enhance sensitivity to weak oscillating (AC) signals. Currently, those methods are limited to signal frequencies below a few MHz. Here we harness a quantum-optical effect, the Mollow triplet splitting of a strongly driven two-level system, to overcome this limitation. We microscopicall ...[more]

PMID: 29042543

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Project description:BackgroundMolecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diagnostic techniques prevent their widespread use intraoperatively. With the unique advantages of ultrasound, this study developed a rapid intraoperative molecular diagnostic method based on ultrasound radio-frequency signals.MethodsWe built a brain tumor ultrasound bank with 169 cases enrolled since July 2020, of which 43483 RF signal patches from 67 cases with a pathological diagnosis of glioma were a retrospective cohort for model training and validation. IDH1 and TERT promoter (TERTp) mutations and 1p/19q co-deletion were detected by next-generation sequencing. We designed a spatial-temporal integration model (STIM) to diagnose the three molecular biomarkers, thus establishing a rapid intraoperative molecular diagnostic system for glioma, and further analysed its consistency with the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5). We tested STIM in 16-case prospective cohorts, which contained a total of 10384 RF signal patches. Two other RF-based classical models were used for comparison. Further, we included 20 cases additional prospective data for robustness test (ClinicalTrials.govNCT05656053).FindingsIn the retrospective cohort, STIM achieved a mean accuracy and AUC of 0.9190 and 0.9650 (95% CI, 0.94-0.99) respectively for the three molecular biomarkers, with a total time of 3 s and a 96% match to WHO CNS5. In the prospective cohort, the diagnostic accuracy of STIM is 0.85 ± 0.04 (mean ± SD) for IDH1, 0.84 ± 0.05 for TERTp, and 0.88 ± 0.04 for 1p/19q. The AUC is 0.89 ± 0.02 (95% CI, 0.84-0.94) for IDH1, 0.80 ± 0.04 (95% CI, 0.71-0.89) for TERTp, and 0.85 ± 0.06 (95% CI, 0.73-0.98) for 1p/19q. Compared to the second best available method based on RF signal, the diagnostic accuracy of STIM is improved by 16.70% and the AUC is improved by 19.23% on average.InterpretationSTIM is a rapid, cost-effective, and easy-to-manipulate AI method to perform real-time intraoperative molecular diagnosis. In the future, it may help neurosurgeons designate personalized surgical plans and predict survival outcomes.FundingA full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Dataset Information

Quantum sensing of weak radio-frequency signals by pulsed Mollow absorption spectroscopy.

Publications

Quantum sensing of weak radio-frequency signals by pulsed Mollow absorption spectroscopy.

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