ORCID Profile
0000-0003-1550-8483
Current Organisation
Heriot-Watt University
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Publisher: Springer Science and Business Media LLC
Date: 08-04-2021
DOI: 10.1038/S41534-021-00389-Z
Abstract: The characterization of quantum systems is both a theoretical and technical challenge. Theoretical because of the exponentially increasing complexity with system size and the fragility of quantum states under observation. Technical because of the requirement to manipulate and read out in idual atomic or photonic elements. Adaptive methods can help to overcome these challenges by optimizing the amount of information each measurement provides and reducing the necessary resources. Their implementation, however, requires fast-feedback and complex processing algorithms. Here, we implement online adaptive sensing with single spins and demonstrate close to photon shot noise limited performance with high repetition rate, including experimental overheads. We further use fast feedback to determine the hyperfine coupling of a nuclear spin to the nitrogen-vacancy sensor with a sensitivity of $$445\\,{\\mathrm{nT}}{\\sqrt{\\mathrm{Hz}}}^{- 1}$$ 445 nT Hz − 1 . Our experiment is a proof of concept that online adaptive techniques can be a versatile tool to enable faster characterization of the spin environment.
Publisher: IOP Publishing
Date: 22-05-2023
Abstract: Quantum sensors can potentially achieve the Heisenberg limit of sensitivity over a large dynamic range using quantum algorithms. The adaptive phase estimation algorithm (PEA) is one ex le that was proven to achieve such high sensitivities with single-shot readout (SSR) sensors. However, using the adaptive PEA on a non-SSR sensor is not trivial due to the low contrast nature of the measurement. The standard approach to account for the averaged nature of the measurement in this PEA algorithm is to use a method based on ‘majority voting’. Although it is easy to implement, this method is more prone to mistakes due to noise in the measurement. To reduce these mistakes, a binomial distribution technique from a batch selection was recently shown theoretically to be superior, as all ranges of outcomes from an averaged measurement are considered. Here we apply, for the first time, real-time non-adaptive PEA on a non-SSR sensor with the binomial distribution approach. We compare the mean square error of the binomial distribution method to the majority-voting approach using the nitrogen-vacancy center in diamond at ambient conditions as a non-SSR sensor. Our results suggest that the binomial distribution approach achieves better accuracy with the same sensing times. To further shorten the sensing time, we propose an adaptive algorithm that controls the readout phase and, therefore, the measurement basis set. We show by numerical simulation that adding the adaptive protocol can further improve the accuracy in a future real-time experiment.
Publisher: Springer Science and Business Media LLC
Date: 16-11-2015
Abstract: Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz(-1/2) over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.
Publisher: AIP Publishing
Date: 24-04-2023
DOI: 10.1063/5.0144684
Abstract: Grayscale lithography allows the creation of micrometer-scale features with spatially controlled height in a process that is fully compatible with standard lithography. Here, solid immersion lenses are demonstrated in silicon carbide using a fabrication protocol combining grayscale lithography and hard-mask techniques to allow nearly hemispherical lenses of 5μm radius to be etched into the substrate. Lens performance was benchmarked by studying the enhancement obtained in the optical collection efficiency for single quantum emitters hosted in silicon carbide. Enhancement by a factor of 4.4 ± 1.0 was measured for emitters not registered to the center of the lens, consistent with devices fabricated through other methods. The grayscale hard-mask technique is highly reproducible, scalable, and compatible with CMOS technology, and device aspect ratios can be tuned after resist patterning by controlling the chemistry of the subsequent dry etch. These results provide a reproducible, low-cost, high-throughput and industrially relevant alternative to focused ion beam milling for the creation of high-aspect-ratio, rounded microstructures for quantum technology, and microphotonic applications.
Publisher: American Physical Society (APS)
Date: 11-03-2019
Publisher: American Physical Society (APS)
Date: 30-05-2017
Publisher: The Optical Society
Date: 08-01-2019
DOI: 10.1364/OME.9.000441
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Cristian Bonato.