  The renormalization group is the cornerstone of the modern theory of
universality and phase transitions, a powerful tool to scrutinize symmetries
and organizational scales in dynamical systems. However, its network
counterpart is particularly challenging due to correlations between intertwined
scales. To date, the explorations are based on hidden geometries hypotheses.
Here, we propose a Laplacian RG diffusion-based picture in complex networks,
defining both the Kadanoff supernodes' concept, the momentum space procedure,
\emph{\'a la Wilson}, and applying this RG scheme to real networks in a natural
and parsimonious way.
