Synchrony by Birth and Death

What the math gives to ML

The paper provides a nonstandard synchronization mechanism in which phase-dependent birth and death rates replace direct phase-coupling forces. Its transferable asset is a positive population dynamics with an alignment fitness term and logarithmic crowding penalty, yielding self-stabilized abundance allocation and a nongeneric coherence onset proportional to the one-fourth power of the distance from threshold. A promising neural implementation is a differentiable birth/death or soft-routing layer whose expert abundances evolve according to this demographic law, while expert phases drift independently and communicate only through survival rates.