Translational Physics Under Constraint: A Framework for Understanding the Limits of Scientific Application

This paper introduces a structured framework for understanding the limits of translating physics from controlled theoretical environments into real-world systems. While physics provides highly reliable predictive models under idealized conditions, its application across domains such as energy systems, medical technologies, climate modelling, and infrastructure often produces outcomes that diverge from theoretical expectations. This review argues that these divergences are not primarily due to failures in engineering, funding, or policy, but are instead driven by intrinsic constraints embedded within physical law, computational modelling, and system-level realities. The paper develops the TPPRI Translational Constraint Framework, which identifies three interacting constraint classes: Physical constraints: thermodynamic limits, noise floors, and nonlinear scaling Computational constraints: resolution limitations, model incompleteness, and infrastructure dependence System-level constraints: calibration drift, institutional instability, and interpretive variability These constraints interact through a process described as the Degradation Cascade, where losses introduced at each stage of translation compound as systems move from theory to deployment. The paper advances a central principle: Physical knowledge does not transfer unchanged into real-world systems; it undergoes structured degradation under constraint. From the perspective of the The Physics Paradox Research Initiative (TPPRI), this work reframes translation itself as a domain of physics inquiry. It argues for a shift in research design, where scaling, uncertainty, and infrastructure are treated as core variables rather than external considerations. This paper serves as a conceptual foundation for the TPPRI Review Paper Series and contributes to ongoing work on translational physics for societal impact.