This paper presents PySkyLumos, an open-source Python framework for simulating skylight polarization measurements and metadata. It implements the Rayleigh, Berry, and Pan models, capturing both classical scattering and elevation-expressed singularity dynamics. Efficiency benchmarks show a fivefold overall speedup and up to two orders of magnitude faster Stokes-parameter image formation compared to existing tools. Validation against real polarization camera data confirms its accuracy and suitability for bio-inspired computer vision, navigation, robotics, and sensing applications.

This paper presents PySkyLumos, an open-source Python framework for simulating skylight polarization measurements and metadata. It implements the Rayleigh, Berry, and Pan models, covering single scattering, the splitting of the neutral points caused by multiple scattering, and the elevation-dependent motion of these points. Benchmarks show a fivefold overall speed-up and up to two orders of magnitude faster Stokes-parameter image formation than a recent open-source simulator. Validation against real polarization-camera images shows close agreement between the simulated and measured polarization patterns, supporting its use in algorithm development for bio-inspired computer vision, navigation, robotics, and sensing.