Efficient signal processing for time-resolved fluorescence detection of nitrogen-vacancy spins in diamond
Anchal Gupta, Luke Hacquebard, and Lilian Childress

TL;DR
This paper introduces a simple signal processing method to enhance the precision of time-resolved fluorescence detection of nitrogen-vacancy spins in diamond, significantly improving measurement quality without hardware changes.
Contribution
A novel analysis technique for fluorescence data that boosts signal-to-noise ratio, aiding in the optimization of NV spin detection for sensing applications.
Findings
Achieved a 14% increase in photon collection efficiency.
Demonstrated improved measurement precision through data analysis.
Analyzed the impact of excitation power on signal-to-noise ratio.
Abstract
Room-temperature fluorescence detection of the nitrogen-vacancy center electronic spin typically has low signal to noise, requiring long experiments to reveal an averaged signal. Here, we present a simple approach to analysis of time-resolved fluorescence data that permits an improvement in measurement precision through signal processing alone. Applying our technique to experimental data reveals an improvement in signal to noise equivalent to a 14% increase in photon collection efficiency. We further explore the dependence of the signal to noise ratio on excitation power, and analyze our results using a rate equation model. Our results provide a rubric for optimizing fluorescence spin detection, which has direct implications for improving precision of nitrogen-vacancy-based sensors.
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