MUFASA: A Continuous-Time Stochastic Framework for Realistic Fluorescence Microscopy Simulation

We present MUFASA ( M ulti-Protocol U nified F luorescence-based A dvanced S imulation A lgorithm), a physically grounded, continuous-time simulator for super-resolution fluorescence microscopy. By modeling fluorophore dynamics using continuous-time Markov chains, MUFASA’s simulation features yield realistic photon emission behavior across both Single Molecule Localization Microscopy (SMLM) and fluorescence fluctuation-based (FF-SRM) protocols—independently of frame duration and sampling. The framework supports both individual emitters and structure-level simulations, incorporating photophysical transitions, photobleaching, and camera properties.

To quantitatively validate simulations with real data, we introduce a novel validation metric based on the 1-Wasserstein distance between simulated and experimental photon-count distributions. In addition to simulation, another functionality estimates key photophysical parameters (e.g., molar extinction coefficient) and to suggest optimal light-source power ranges from fluctuation data. An intuitive Python-based graphical interface enables real-time parameter tuning, visualization, and TIFF export. Designed for biologists, physicists, microscopists, and numerical imaging engineers, MUFASA offers a practical platform for microscopy experiment design, hypothesis testing and the generation of realistic training data for data-driven microscopy methods across modalities.