Simulation Toolkit Advances Realistic Noise Modelling for Seven-Level Nv-Center Magnetometry

Researchers are tackling a critical challenge in quantum sensing: accurately modelling the noise that impacts the performance of nitrogen-vacancy (NV) centre diamond magnetometers. Satyam Pandey (TCS Research & IISER Bhopal), Abhimanyu Magapu (TCS Research & BITS Pilani, Goa), and Prabhat Anand et al. have developed QDsiM, a new simulation toolkit designed to replicate realistic noise sources within these systems. This comprehensive framework, a ‘digital twin’ for continuous-wave wide-field optically detected magnetic resonance, incorporates factors like laser fluctuations, microwave noise, and temperature shifts , all crucial as NV-based sensors move from labs into real-world applications. By allowing researchers to simulate and mitigate these imperfections, QDsiM promises to significantly enhance the sensitivity and reliability of future quantum diamond microscopes.

have developed QDsiM, a new simulation toolkit designed to replicate realistic noise sources within these systems. By allowing researchers to simulate and mitigate these imperfections, QDsiM promises to significantly enhance the sensitivity and reliability of future quantum diamond microscopes.

NV Centre ODMR Simulation with Realistic Noise

This breakthrough addresses a critical need as NV-based magnetometry systems move from controlled laboratory settings to portable, field-deployable sensors, demanding a detailed understanding of realistic noise sources and experimental imperfections. By explicitly linking noise parameters to experimentally accessible quantities like laser power, microwave power, beam waist, and integration time, the simulation reproduces both qualitative and quantitative features observed in actual ODMR spectra. This digital twin provides a versatile tool for designing experiments, optimizing parameters, and training data-driven methods for magnetic field reconstruction from ODMR data. The work opens avenues for developing practical, high-performance NV-based quantum magnetometers with enhanced sensitivity and reliability.
The team achieved this by building a simulation that doesn’t just model ideal conditions, but actively incorporates the imperfections inherent in real-world experiments, allowing for more accurate predictions and targeted improvements. This innovative approach promises to accelerate the development and deployment of NV-center-based sensors in diverse applications, ranging from nanoscale magnetometry to biomedical imaging and materials science. Experiments show that the framework accurately simulates the complex interplay of factors affecting ODMR signals, offering a powerful platform for understanding and mitigating noise. The seven-level model meticulously describes the NV center’s electronic structure, including ground and excited triplet states and the intermediate singlet manifold, enabling precise modeling of optical pumping, intersystem crossing, and spin-dependent fluorescence. This detailed approach, combined with the modular noise components, allows researchers to systematically investigate the impact of various parameters on ODMR performance and optimize sensor design for specific applications. The research establishes a new standard for simulating NV-center-based quantum sensors, paving the way for more robust and sensitive magnetic field detection.

NV Centre ODMR Digital Twin Simulation is revolutionizing

Scientists validated the simulator by systematically comparing its output with reported experimental behaviors, demonstrating its ability to reproduce key qualitative and quantitative features of ODMR spectra. By varying parameters such as microwave power, beam waist, and integration time, the framework accurately predicted experimental outcomes, confirming its predictive power and reliability. This digital twin provides a versatile tool for experiment design and parameter optimization, specifically targeting the contrast-to-linewidth ratio, a central figure of merit for magnetic-field sensitivity, allowing researchers to maximize sensor performance. The approach enables the training of data-driven methods for magnetic field reconstruction from ODMR data, thereby supporting the development of practical NV-based quantum magnetometers with enhanced sensitivity and accuracy.

NV ensemble ODMR accurately modelled via digital twin

This work meticulously models the complex interplay of noise sources and experimental imperfections to optimise performance and sensitivity in quantum magnetometry. Systematic examinations, specifically ion 6, rigorously assessed the impact of photon shot noise, laser and microwave power fluctuations, and temperature-induced shifts on ODMR contrast and linewidth. Measurements confirm that these factors significantly influence the clarity and precision of the ODMR signal. Results demonstrate that the digital twin framework can predict ODMR spectra displaying fluorescence contrast as a function of microwave frequency, with multiple dips observed due to Zeeman splitting of the ms = ±1 sublevels under an applied magnetic field.

NV centers oriented along four distinct crystallographic axes produce up to eight distinguishable dips, two per axis, corresponding to transitions from ms = 0 to ±1. The differential ODMR spectrum, computed as the numerical derivative of contrast with respect to frequency (dC/df), highlights regions of rapid contrast change, improving dip visibility in noisy data. The NV− center, with its spin-triplet ground state, exhibits a zero-field splitting Dgs of approximately 2.87GHz, originating from spin-spin interactions. Continuous-wave (CW) laser excitation at 532nm drives electrons from the ground to the excited triplet state, with relaxation proceeding via radiative and non-radiative decay channels. Scientists recorded that the application of a microwave field resonant with the energy separation between ms = 0 and ms ±1 spin states induces resonant spin transitions, reducing PL intensity and forming the basis of the ODMR spectrum. This breakthrough delivers a novel method for denoising ODMR data, paving the way for optimised deployment of practical NV-based quantum magnetometers.

NV Ensemble ODMR Digital Twin Simulation enables advanced

The significance of this work lies in its ability to bridge the gap between theoretical models and practical implementation of NV-based quantum sensors, potentially accelerating their deployment in diverse applications such as healthcare and electronics. By accurately capturing the behaviour of experimental systems, the framework allows for optimisation of contrast-to-linewidth ratio, a key figure of merit for magnetic-field sensitivity, and diagnosis of performance limitations caused by competing noise processes. The authors acknowledge limitations related to the current scope of the model, specifically excluding explicit treatment of electric-field and strain effects, hyperfine interactions, optical aberrations, and active closed-loop control mechanisms. Future research will focus on incorporating these elements, alongside adaptation to pulsed ODMR protocols and the application of machine learning techniques, to further enhance the toolkit’s capabilities as a testbed for advanced signal processing.