A pseudo-thermal simulation strategy for correlation imaging

Abstract Correlation-based imaging techniques rely on the statistical properties of partially coherent light sources. Simulating such systems is increasingly important for the design and optimization of imaging setups, the validation of theoretical models, and the training of data-driven reconstruction algorithms, including those based on machine learning. In this work, we present a numerical framework that enables the simulation of image formation in correlation-based optical systems, starting from the generation of pseudo-thermal light with user-defined spatial coherence properties. The simulation is based on scalar diffraction theory under the paraxial approximation and models partial coherence using the Gaussian Schell framework. While these models alone are well established, practical frameworks that combine them into end-to-end simulations of correlation imaging systems are still relatively scarce. We introduce a flexible and efficient software tool that supports multiframe generation and field propagation through arbitrary optical systems. Preliminary results demonstrate its suitability for a broad range of applications, from theoretical investigations to experimental planning and algorithm benchmarking.