Noise analysis and sensitivity optimization in NV-diamond based magnetic field imaging systems

Magnetic field imaging technologies based on nitrogen-vacancy centers (NVCs) in diamond, the quantum diamond microscope (QDM), has emerged as a unique sensing modality in detecting spatiotemporally-varying magnetic fields for applications including the characterization of microelectronic circuits. For many impactful use cases, sub nT/√Hz sensitivities are required to resolve the dynamical behavior of small signals. While these sensitivities have been achieved in bulk (3D) NVCs, the 2D NVC magnetometers employed for near-field, wide-field-of-view magnetic microscopy applications have only reached nT/√Hz sensitivities.



Closing this sensitivity gap is a critical challenge in the field and requires a comprehensive understanding of how environmental noise diminishes sensitivity. This can be accomplished with a quantitative mapping between noise sources across the system stack and the measured imaging sensitivities to understand how environmental noise diminishes sensitivity. We demonstrate a combined experimental and theoretical framework to map experimental noise sources from an imager to measured sensitivities. We present frequency-dependent noise contributions from the optical, microwave, and readout chains then demonstrate their effects on the coherence times and sensitivities for QDM systems operating with pulsed control and LED optical control. We then calibrate our framework against a theoretical noise model and suggest techniques for further improving sensitivities.