| 1. |
- Astner, Thomas, et al.
(författare)
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Vanadium in silicon carbide: telecom-ready spin centres with long relaxation lifetimes and hyperfine-resolved optical transitions
- 2024
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Ingår i: QUANTUM SCIENCE AND TECHNOLOGY. - : IOP Publishing Ltd. - 2058-9565. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- Vanadium in silicon carbide (SiC) is emerging as an important candidate system for quantum technology due to its optical transitions in the telecom wavelength range. However, several key characteristics of this defect family including their spin relaxation lifetime (T1), charge state dynamics, and level structure are not fully understood. In this work, we determine the T1 of an ensemble of vanadium defects, demonstrating that it can be greatly enhanced at low temperature. We observe a large spin contrast exceeding 90% and long spin-relaxation times of up to 25 s at 100 mK, and of order 1 s at 1.3 K. These measurements are complemented by a characterization of the ensemble charge state dynamics. The stable electron spin furthermore enables high-resolution characterization of the systems' hyperfine level structure via two-photon magneto-spectroscopy. The acquired insights point towards high-performance spin-photon interfaces based on vanadium in SiC.
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| 2. |
- Rinaldi, Enrico, et al.
(författare)
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Parameter estimation from quantum-jump data using neural networks
- 2024
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Ingår i: Quantum Science and Technology. - 2058-9565. ; 9:3
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Tidskriftsartikel (refereegranskat)abstract
- We present an inference method utilizing artificial neural networks for parameter estimation of a quantum probe monitored through a single continuous measurement. Unlike existing approaches focusing on the diffusive signals generated by continuous weak measurements, our method harnesses quantum correlations in discrete photon-counting data characterized by quantum jumps. We benchmark the precision of this method against Bayesian inference, which is optimal in the sense of information retrieval. By using numerical experiments on a two-level quantum system, we demonstrate that our approach can achieve a similar optimal performance as Bayesian inference, while drastically reducing computational costs. Additionally, the method exhibits robustness against the presence of imperfections in both measurement and training data. This approach offers a promising and computationally efficient tool for quantum parameter estimation with photon-counting data, relevant for applications such as quantum sensing or quantum imaging, as well as robust calibration tasks in laboratory-based settings.
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