The run time Huffman encoder works just like a Walmart supply chain

The Huffman encoder on the right, essentially exchange nodes to keep iLogi within a unit of each other. It is a batch form.

But the node exchanges will exceed the point during exchange, the cost of the map. We are lightly more redundant than theoretical limit. But Walmart adjusts its supply chain with the same goal, adiabatic change, we coll it in sandbox. An like an encoder, Walmart is adjusting 'items per basket' along the descending distribution tree. It is all about keeping inventory from bunching up. Flow drives quantization, flow wants to be packaged so units do not bunch up,

The Walmart inventory manager is buying empty space in the trucks and packages. He play the in and out game, trying to keep both distributions at the same skew so inventory, on the whole, is close to a dividable flow. He want a fixed bandwidth channel, encoded so input and output is a N bit number divided by an N-1 bit number,in a typical dual colored system.  All parties get that they get a fixed portion of inventory space.

But uniform congestion means the distribution networks can be approximated as smooth surface, they should scale properly it they are queued properly. The pit boss can swap across the distributions and keep the accumulated scale error less than one. Scale error thus being the error need to make both trees similar in a geometric sense, but homogeneous in the general case.

Inventory exchanges are like quantum qubit operations.