We introduce a novel physical parameter, exchange inertia Iex, which quantifies the resistance to energy and information transfer in systems exhibiting persistent memory. The parameter emerges naturally from the mathematical structure of effective temporal foliation and is operationally defined as a ratio between an effective entropy measure and the total available energy, modulated by a structural factor encoding macroscopic properties of the system. Applyingthisframeworktoasampleof24core-collapsesupernovaewithwell-characterized progenitors, we demonstrate that incorporating Iex into the energy transfer dynamics leads to substantial improvements in predictive accuracy. The root-mean-square residual decreases from 0.50 foe in baseline models to 0.08 foe, while previously unexplained outliers are consis- tently accounted for by correspondingly low or high values of Iex. The Bayesian Information Criterion strongly favors the extended model, supporting its physical relevance beyond phe- nomenological fitting. These results provide strong empirical evidence that exchange inertia captures a genuine physical constraint governing energy transfer efficiency in systems with memory. While the present work focuses on astrophysical applications, the formulation is general and applicable to a wide range of systems, from quantum coherent media to macroscopic structures with long-lived internal organization. The concept originates from a broader theoretical program investigating how persistent memory modifies effective temporal structure in physical systems. The empirical success reported here motivates further development of the complete mathematical foundation un- derlying this connection.
Maximo de Paz (Thu,) studied this question.