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arXiv:2302.06310 · IEEE Transactions on Industrial Electronics

Efficient Real-Time Spin Readout of Nitrogen-Vacancy Centers Based on Bayesian Estimation

Jixing Zhang, Tianzheng Liu, Heng Yuan, Sigang Xia, Guodong Bian, Pengcheng Fan, Mingxin Li, Sixian Wang, X. Q. Li, Chen Zhang, Shaoda Zhang

Published Jan 24, 2024• 6 citations
arXivHTMLPDF

Abstract

This article introduces a real-time Bayesian estimation algorithm aimed at enhancing the spin readout efficiency of the nitrogen vacancy (NV) center ensemble in the diamond. By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementation of the NV center dynamics model, we offered an innovative solution to surpass the Cramer–Rao lower bound of the readout variance and improve the readout efficiency. The proposed real-time Bayesian estimation readout algorithm was experimentally realized by combining high-performance acquisition and processing hardware, and the Rabi oscillation experiments divulged that the signal-to-noise ratio of our approach was improved by 28.6%. This research illustrates the potential of the Bayesian estimation readout to enhance the NV ensemble's sensing capabilities and support the development of compact and scalable quantum sensors devices on a monolithic platform.

DOI
10.1109/tie.2023.3347837

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This article introduces a real-time Bayesian estimation algorithm aimed at enhancing the spin readout efficiency of the nitrogen vacancy (NV) center ensemble in the diamond. By integrating both the prior probability distribution and the fluorescence likelihood function, stemming from the implementation of the NV center dynamics model, we offered an innovative solution to surpass the Cramer–Rao lower bound of the readout variance and improve the readout efficiency. The proposed real-time Bayesian estimation readout algorithm was experimentally realized by combining high-performance acquisition and processing hardware, and the Rabi oscillation experiments divulged that the signal-to-noise ratio of our approach was improved by 28.6%. This research illustrates the potential of the Bayesian estimation readout to enhance the NV ensemble's sensing capabilities and support the development of compact and scalable quantum sensors devices on a monolithic platform.
Abstract In this work, a spin readout method using fluorescence dynamics is proposed based on maximum likelihood estimation (MLE) for improving the pulsed spin readout accuracy of nitrogen vacancy (NV) center. This estimation method can saturate the Cramér–Rao bound and enhance the photon-shot-noise-limited spin readout accuracy by 20% compared with conventional photon summation method. By employing a rate equation model of the NV center, the exact solution for the fluorescence dynamics is obtained. Additionally, according to the rate equation model’s relationship with fluorescence dynamics, spin, and pumping light power, a practical MLE readout scheme is furnished, which is able to distinguish spin readout information and classical noise. Compared with the conventional method, the classical noise suppression capability can be improved by 300 times. It is anticipated that the MLE method will effectively benefit sensing capability based on the NV centers even other scalable defect complexes in solid systems.
For quantum sensing, it is vital to develop an efficient technique for determining the quantum state of the sensor. We optimize the weighting of the photoluminescence intensity for readout of the spin state of the nitrogen-vacancy (NV) center in diamond. We find that adopting a physical model that considers the optical transitions and relaxations of the NV center allows for an efficient readout. Our method improves the signal-to-noise ratio of the readout by 5.4% in a short time of 3 s, while the existing methods typically require 1 min of integration time. We also show that our technique enhances the readout of the nuclear spin memory. The demonstrated way is helpful for a wide range of measurements, from a few minutes to several days.
Abstract In this work, a time-varying pulse waveform spin readout sequence method is proposed to improve the spin readout efficiency of nitrogen-vacancy (NV) centers. The method consists of performing the readout signal-to-noise ratio (SNR) analysis via the construction of a rate equation model of the NV center. We demonstrate a superior performance from the time-varying waveform readout approach and focus on the role of the readout optimization in quantum measurements. A detailed comparison of the readout SNR of the time-varying waveform and conventional waveform is provided. We experimentally demonstrate that the readout SNR is increased by 8% by utilizing an optimized waveform. It is anticipated that the improved method will effectively benefit the sensing capability of NV center ensembles and provide support for high-precision measurements of solid systems.
We propose and theoretically analyze the use of coherent population trapping of a single diamond nitrogen-vacancy (NV) center for continuous real-time sensing. The formation of the dark state in coherent population trapping prevents optical emissions from the NV center. Fluctuating magnetic fields, however, can kick the NV center out of the dark state, leading to a sequence of single-photon emissions. A time series of the photon counts detected can be used for magnetic field estimations, even when the average photon count per update time interval is much smaller than 1. For a theoretical demonstration, the nuclear spin bath in a diamond lattice is used as a model fluctuating magnetic environment. For fluctuations with known statistical properties, such as an Ornstein-Uhlenbeck process, Bayesian inference-based estimators can lead to an estimation variance that approaches the classical Cramer-Rao lower bound and can update dynamical information in real time with the detection of just a single photon. Real-time sensing using coherent population trapping adds a powerful tool to the emerging technology of quantum sensing.
Nitrogen-vacancy (NV) centers in diamond have become an important instrument for quantum sensing and quantum information science. However, the readout of NV spin state requires bulky optical setups, limiting fabrication of miniaturized compact devices for practical use. Here we realized photoelectrical detection of magnetic resonance as well as Rabi oscillations on a single-defect level. Furthermore, photoelectrical imaging of individual NV centers at room temperature was demonstrated, surpassing conventional optical readout methods by providing high imaging contrast and signal-to-noise ratio. These results pave the way toward fully integrated quantum diamond devices.
The nitrogen-vacancy (NV) center in diamond has been developed as a promising platform for quantum sensing, especially for magnetic field measurements in the nano-tesla range with a nano-meter resolution. Optical spin readout performance has a direct effect on the signal-to-noise ratio (SNR) of experiments. In this work, we introduce an online optimization method to customize the laser waveform for readout. Both simulations and experiments reveal that our new scheme optimizes the optically detected magnetic resonance in NV center. The SNR of optical spin readout has been witnessed a 44.1% increase in experiments. In addition, we applied the scheme to the Rabi oscillation experiment, which shows an improvement of 46.0% in contrast and a reduction of 12.1% in mean deviation compared to traditional constant laser power SNR optimization. This scheme is promising to improve sensitivities for a wide range of NV-based applications in the future.