Stochastic Frequency Fluctuation Super-Resolution Imaging

TL;DR

This paper introduces Spectral Fluctuation Super-Resolution (SFSR) imaging, a method that enhances resolution by analyzing spectral correlation functions, applicable to quantum emitters with spectral diffusion, achieving up to twofold resolution improvement.

Contribution

The paper proposes a novel super-resolution imaging technique based on spectral fluctuations, extending beyond intensity correlation methods like SOFI, with theoretical, computational, and experimental validation.

Findings

Resolution improves by a factor of √2 in most cases.

Up to twofold resolution enhancement for two emitters.

Applicable to non-blinking emitters with spectral diffusion.

Abstract

The inherent non-linearity of intensity correlation functions can be used to spatially distinguish identical emitters beyond the diffraction limit, as achieved, for example, in Super-Resolution Optical Fluctuation Imaging (SOFI). Here, we propose a complementary concept based on spectral correlation functions, termed Spectral Fluctuation Super-Resolution (SFSR) imaging. Through theoretical and computational analysis, we show that spatially resolving time-frequency correlation functions in the image plane can improve the imaging resolution by a factor of $\sqrt2$ in most cases and up to twofold for strictly two emitters. This improvement is achieved by quantifying the degree of correlation in spectral fluctuations across the spatial domain. Experimentally, SFSR can be implemented using a combination of interferometry and photon-correlation measurements. The method works for non-blinking emitters and stochastic spectral fluctuations with arbitrary temporal statistics. This suggests its utility in super-resolution microscopy of quantum emitters at low temperatures, where spectral diffusion is often more pronounced than emitter blinking.