Quantum super-resolution microscopy by photon statistics and structured light

Abstract

We present an advanced quantum super-resolution imaging technique based on photon statistics measurement and its accurate modeling. Our reconstruction algorithm adapts to any kind of non-Poissonian emitters, outperforming the corresponding classical SOFI method. It offers sub-diffraction resolution improvement that scales with the $\sqrt{j}$, where $j$ is the highest order central moments of the photocounts. More remarkably, in combination with structured illumination a linear improvement with j can be reached. Through simulations and experiments, we prove our method's clear superiority over traditional SOFI, especially in low excitation light conditions, providing a promising avenue for non-invasive super-resolution microscopy of delicate samples.