We present bifrost, a first-principles model of polarization mode dispersion (PMD) in optical fibers. Unlike conventional models, bifrost employs physically motivated representations of the PMD properties of fibers, allowing users to computationally investigate real-world fibers in ways that are connected to physical parameters such as environmental temperature and external stresses. Our model, implemented in an open-source Python module, incorporates birefringence from core geometry, material properties, environmental stress, and fiber spinning. We validate our model by examining commercial fiber specifications, fiber-paddle measurements, and published PMD statistics for deployed fiber links, and we showcase bifrost’s predictive power by considering wavelength-division-multiplexed PMD compensation schemes for polarization-encoded quantum networks. bifrost’s physical grounding enables investigations into such questions as the sensitivity of fiber sensors, the evaluation of PMD mitigation strategies in quantum networks, and many more applications across fiber technologies.

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• Birefringence
• Optical quantum information processing
• Polarization of light
• Quantum communication
• Quantum networks
• Optical fibers
• Waveguides
• First-principles calculations