Interpreting the Synchronization Gap: The Hidden Mechanism Inside Diffusion Transformers

In this paper, we investigate how the synchronization gap is mechanistically realized within pretrained Diffusion Transformers (DiTs) by constructing an explicit architectural realization of replica coupling by embedding two generative trajectories into a joint token sequence, modulated by a symmetric cross attention gate with variable coupling strength $g$. Through a linearized analysis of the attention difference, we show that the replica interaction decomposes mechanistically and we empirically validate our theoretical framework on a pretrained DiT-XL/2 model by tracking commitment and per layer internal mode energies. Our results reveal that: (1) the synchronization gap is an intrinsic architectural property of DiTs that persists even when external coupling is turned off; (2) as predicted by our spatial routing bounds, the gap completely collapses under strong coupling $g\rightarrow1$; (3) the gap is strictly depth localized, emerging sharply only within the final layers of the Transformer; and (4) global, low frequency structures consistently commit before local, high frequency details. Ultimately, our findings provide a mechanistic interpretation of how Diffusion Transformers resolve generative ambiguity, isolating speciation transitions to the terminal layers of the network.