Co-aging complex systems: Featuring infected worms, competing trees and chess battles

Aging, as defined in terms of the slope of failure probability versus time, is a generic phenomenon observed in nearly all complex systems. Interdependency networks can accurately describe the aging statistics of biological species as well as complex mechanical devices: In an interdependency network, when one component malfunctions, so do others that depend on it, causing a cascading failure. This model, together with its evolutionary counterparts, predict failure rates that strictly increase in time. However, hazard curves with peculiar ups and downs have been observed in nature in seeming contradiction with theory. Here we introduce the concept of "co-aging", where the demographics of multiple cohorts are intertwined and show that co-aging dynamics can account for these peculiar bumps empirically observed in mortality curves. Specifically, we introduce a model where multiple interdependency networks inflict damage on each other, in addition to experiencing intrinsic damage. We then successfully fit our model predictions to the experimental failure statistics for (1) co-aging worm-pathogen populations (2) multiple competing tree species, and (3) machine-against-machine chess games. Importantly, our model can successfully fit not only cumulative failure rates, but also cause-specific failure rates, e.g. distinguishing between deaths that primarily stem from the accumulation of intrinsic damage versus extrinsic assaults.