Ensembles of nitrogen vacancy (NV) defect centers in diamond have attracted considerable interest for fundamental studies and applications in quantum sensing and quantum information processing. Pulsed optically detected magnetic resonance (ODMR) and related pulse-sequence protocols are essential for the coherent manipulation and characterization of the NV spins. Here, we introduce a novel framework for analyzing pulsed ODMR data acquisition and subsequent processing from the perspective of digital signal processing (DSP). As a central part of this approach, we model the data processing procedure as an effective digital bandpass filter that suppresses a broad range of noise spectral components, thereby reducing the noise in the processed data. This analysis identifies an intermediate frequency (IF) band whose spectral contribution to this noise is maximum. The proposed DSP-based analysis is experimentally validated using an oscilloscope based acquisition method, and is also applied to optimize key measurement parameters. In particular, the introduction of an analog low pass filter in the signal path is shown to remove aliasing of noise into the IF band, and thus improve signal quality. Our results also establish the oscilloscope as a viable data acquisition device for pulsed ODMR, with practical advantages including on-board waveform averaging, real-time signal visualization, and simplified system debugging. The proposed framework can be extended to other detection techniques and material platforms for ODMR.
Ensembles of nitrogen vacancy (NV) defect centers in diamond have attracted considerable interest for fundamental studies and applications in quantum sensing and quantum information processing. Pulsed optically detected magnetic resonance (ODMR) and related pulse-sequence protocols are essential for the coherent manipulation and characterization of the NV spins. Here, we introduce a novel framework for analyzing pulsed ODMR data acquisition and subsequent processing from the perspective of digital signal processing (DSP). As a central part of this approach, we model the data processing procedure as an effective digital bandpass filter that suppresses a broad range of noise spectral components, thereby reducing the noise in the processed data. This analysis identifies an intermediate frequency (IF) band whose spectral contribution to this noise is maximum. The proposed DSP-based analysis is experimentally validated using an oscilloscope based acquisition method, and is also applied to optimize key measurement parameters. In particular, the introduction of an analog low pass filter in the signal path is shown to remove aliasing of noise into the IF band, and thus improve signal quality. Our results also establish the oscilloscope as a viable data acquisition device for pulsed ODMR, with practical advantages including on-board waveform averaging, real-time signal visualization, and simplified system debugging. The proposed framework can be extended to other detection techniques and material platforms for ODMR.
Introduction Nitrogen-vacancy (NV) centers in diamond are promising solid-state quantum sensors. The sensor can potentially monitor the real-time magnetic field at room-temperature toward the brain-machine interface. One of the biggest challenges is to implement a highly sensitive sensor in a compact system. There are two major ways to achieve it. An analog signal processing method with a lock-in amplifier is fast to obtain the signal, but it increases the size of the sensor system. The digital signal processing method with the Fourier transform is simple, but it needs more computational resources. Reducing computational resources with the simple system is an important task for monitoring a real-time magnetic field. In this study, we demonstrate an alternative method of digital signal processing with less computational resources than the Fourier transform. The computational time of the method to compute the signal from n points of data is O(n), whereas the time with Fourier transform is O(n log n). Method and Result We confirm our method with a large detection volume of the ensemble NV centers. The microwave and optical systems used in our experiment are shown in Fig. 1. The diamond sample containing NV centers was placed between the microwave resonator and a compound parabolic concentrator1. We used a coplanar waveguide resonator (CWR) with a wide center electrode for strong and uniform microwave irradiation2. The power of microwave with frequency modulation is 25 dBm before the CWR. The 300 mW laser beam to the diamond was focused with a beam diameter of about 30 μm. The fluorescence from the NV centers was collected through the compound parabolic concentrator and detected using a photodiode. The detected signal of the photodiode is analyzed by digital signal processing. The method obtains the result using a digital filter that effectively becomes a sinc filter using the orthogonality of trigonometric functions by multiplication of the acquired data by a trigonometric function. Figures 2 shows continuous-wave optical detected magnetic resonance (CW-ODMR) spectrum using the digital signal processing with a different modulation frequency of the microwave. The maximum slope and the noise of the signal become smaller with increasing the modulation frequency for different reasons. The low transition rate between quantum states of the NV center reduces the maximum slope for high modulation frequency. While the noise becomes smaller for high modulation frequency. We evaluate the maximum signal slope (Fig. 3) and noise level of the spectrum (Fig. 4). We found the reduction of the noise is greater than the reduction of the maximum slope. This work was supported by MEXT Quantum Leap Flagship Program (MEXT Q-LEAP) Grant Number JPMXS0118067395.
Ensembles of nitrogen-vacancy (NV) centers in diamond are versatile quantum sensors with broad applications in the physical and life sciences. The concentration of neutral substitutional nitrogen ( [ N s 0 ]) strongly influences NV electronic spin coherence times, sensitivity, and optimal sensing strategies. Diamonds with [ N s 0 ] ∼ 1–10 ppm are a focus of recent material engineering efforts, with higher concentrations being favorable for continuous-wave optically detected magnetic resonance (CW-ODMR) and lower concentrations expected to benefit pulsed magnetometry techniques through extended NV spin coherence times and improved sensing duty cycles. In this work, we synthesize and characterize low- [ N s 0 ] ( ∼ 0.8 ppm), NV-enriched diamond material, engineered through low-strain chemical vapor deposition (CVD) growth on high-quality substrates, 12 C isotopic purification, and controlled electron irradiation and annealing. Our results demonstrate good strain homogeneity in diamonds grown on CVD substrates and spin-bath-limited NV dephasing times. By measuring NV spin and charge properties across a wide range of optical NV excitation intensity, we provide direct comparisons of photon-shot-noise-limited magnetic field sensitivity between the current low- [ N s 0 ] and previously studied higher- [ N s 0 ] ( ∼ 14 ppm) NV-diamond sensors. We show that low- [ N s 0 ] diamond can outperform higher- [ N s 0 ] diamond at moderate and low optical NV excitation intensity. Our results provide practical benchmarks and guidance for selecting NV-diamond sensors tailored to specific experimental constraints and sensing requirements.
The nitrogen-vacancy (NV) centers in diamond have the advantages of stable triaxial structure, ultra-long electron spin coherence time and simple optical readout at room temperature. A nitrogen atom in the diamond crystal replaces a carbon atom and a vacancy is generated at the adjacent position, forming a point defect in the C3v space group structure. Its ground state and excited state are both spin triplet states. It is the key to achieving efficient preparation of optical initial state and extracting NV color center’s information in the researches of highly sensitive sensing magnetic detection, temperature detection, biological imaging, quantum computing, etc. However, there was no systematic study on relevant parameters of laser for high-concentration NV color center’s samples in previous experimental studies. Based on a high concentration diamond NV ensemble, we use pulsed optical detection magnetic resonance (ODMR) technology to systematically study the relationship among laser initial polarization time, information reading time and laser power, and the influence of laser incident polarization angle on the accuracy of sensing information. The effects of various laser parameters on the NV1 peak of ODMR on the [111] axis of the NVs of diamond are also investigated. The contrast of ODMR increases firstly with a sigmoid function and then decreases with an e-exponential function as the information reading time increases. The incident polarization angle of the laser is sinusoidal, with a period of 90°. According to the above experimental results, we finally choose the appropriate experimental parameters at 45.8 W/cm2 (300 μs of polarization, 700 ns, reading time, laser incident angle is 220°) for ODMR test. Compared with previous experimental parameters (polarization time was 50 us, read the time of 3000 ns, laser incident angle was 250°), the experimental results show that the contrast of ODMR increases from 2.1% to 4.6%, and the typical magnetic sensitivity is improved from 21.6 nT/Hz1/2 to 5.6 nT/Hz1/2. The optimization of the optical control of NVs in solid diamond is realized. The above results provide an effective support for the detection of high-sensitivity manipulation sensing based on high-concentration NV ensemble.
Nitrogen-vacancy (NV) centers in diamond are a versatile quantum sensing platform for high sensitivity measurements of magnetic fields, temperature and strain with nanoscale spatial resolution. A common bottleneck is the analysis of optically detected magnetic resonance (ODMR) spectra, where target quantities are encoded in resonance features. Conventional nonlinear fitting is often computationally expensive, sensitive to initialization, and prone to failure at low signal-to-noise ratio (SNR). Here we introduce a robust, efficient machine learning (ML) framework for real-time ODMR analysis based on a one-dimensional convolutional neural network (1D-CNN). The model performs direct parameter inference without initial guesses or iterative optimization, and is naturally parallelizable on graphics processing units (GPU) for high-throughput processing. We validate the approach on both synthetic and experimental datasets, showing improved throughput, accuracy and robustness than standard nonlinear fitting, with the largest gains in the low-SNR regime. We further validate our methods in two representative sensing applications: diagnosing intracellular temperature changes using nanodiamond probes and widefield magnetic imaging of superconducting vortices in a high-temperature superconductor. This deep-learning inference framework enables fast and reliable extraction of physical parameters from complex ODMR data and provides a scalable route to real-time quantum sensing and imaging.
The nitrogen-vacancy (NV) center in diamond is a leading solid-state platform for room-temperature quantum magnetometry owing to its long spin coherence times, optical spin initialization and readout, and high sensitivity to magnetic, electric, and thermal perturbations. As NV-based optically detected magnetic resonance (ODMR) systems transition from controlled laboratory environments toward portable and field-deployable sensors, a detailed understanding of realistic noise sources and experimental imperfections becomes essential for optimizing performance and sensitivity. In this work, we present a comprehensive simulation framework, i.e., a digital twin, for continuous-wave wide-field ODMR in NV-center ensembles. The model is built upon a physically consistent seven-level description of the NV center and incorporates a broad range of experimentally relevant noise and imperfection mechanisms as modular, parameterized components. These include laser and microwave amplitude fluctuations, microwave phase noise, uncertainty in the NV gyromagnetic ratio, spin dephasing, temperature-induced shifts of the ground-state zero-field splitting, surface-induced magnetic field perturbations, and photon shot noise. Power broadening and contrast degradation arising from optical and microwave driving are captured self-consistently through linewidth calculations. Also, the spatial inhomogeneity is modeled via a Gaussian laser intensity profile across the sensing region...
One of the promising solid-state quantum sensors is nitrogen-vacancy (NV) centers in diamond which can maintain quantum state at room temperature and under atmospheric pressure condition. Further improvement of sensitivity of the sensor is needed to detect the magnetic field from the brain. Noise reduction and simplified system are key techniques especially for the practical use of highly sensitive DC magnetic sensor. In this study, we devised a digital filtering detection method without synchronization between detector and modulator which is a similar noise reduction effect as a lock-in detection technique. We implemented the detection method for the quantum diamond sensor system with the large sensor volume [1]. The Lock-in detection technique is a typical high sensitivity technique for DC magnetic measurement. There are several different implementations of lock-in detection technique for the quantum diamond sensor including microwave modulation, magnetic field modulation, and laser modulation. However, it is a challenging task to obtain high magnetic sensitivity with a compact sensor module because these lock-in detection techniques require a lock-in amplifier or synchronization system. We devised a digital filtering detection method which is an alternative method to the lock-in detection technique. Fluorescence from the NV center is modulated by frequency modulated microwave during optical detected magnetic resonance (ODMR) measurement. The fluorescence is analyzed by digital signal processing which achieves a similar noise reduction effect as a lock-in detection technique. Our method relies on a fact that ODMR converts frequency modulation to amplitude modulation. Thus, our method is applicable not only to the NV center system but also another color center system. This work was supported by MEXT Q-LEAP, CAO PRISM, Japan. [1] Y. Masuyama et al., Rev. Sci. Instrum. 89, 125007 (2018).