Humans got a beat

I used to make semi regular visits to the hardware store.  My sense of time, if I were to measure customer flows, is based on my beat, the beat of my feet wandering around in a Gaussian crowd with others like me. Gaussi8an means I minimally interfere with others like me.

It is the store manager that wrote the beat, she constantly rearrranges shelving to keep the typical me in a Gaussian crowd. So, the beat of my walk is coherent with a specific, but imprecise count of customers who have transitioned. And that is maintained at the checkout counter queue.  That me and others are a Guassian crowd is the hologram effect. We get the N+1 dimensional simulation, we can wander about in two dimensions, at the same beat and navigate by shelf index.

This whole system is as accurate as the shopkeeper can keep Gaussian crowds, so he computes price of sustainability, he can vary that. In essence, the hologram effect makes the MV=PY work. Use whatever X axis you need to define a walk about the store, as long as there are no runs at the checkout counter, the ratio of V should work.

Price works because the currency banker makes S/L work.  S/L is a constraint on the aggregate, and price is a local constrain relative.  The price of my good is the cost of setting aside inventory space along the chain, but that space will be relative to S/L, the homomorphic queuing constrain.  Along the chain, inventory constraints are solved with either deposit or loan events, they will be homomorphic with inventory flow.

Anyway, this is optimal channel stuffing. And this is a theory of sticky things, economically. But can be seen as a high uncertainty version of the Lindbladian model of quantization.  They both implement the hologram, but with orders of magnitude differences in uncertainty.  Store clerks, around the globe, and their logistics managers set the 'items per basket'. What is the size of my basket for a trip to the hardware store?  That basket size gets locked in place and only a cost of requantization will unlock it.  Basket concept is everywhere, once one starts to look.

The shopping aisles are Riemann spaces, they all curve equally to the checkout counters.  And we see the floor manager setting goods to match the typical set of basket sizes which match one to one on the counter tops.  But with the low flowe rate, compared to the Limbladian, the pattern matching problem, setting the placement of goods by coherence, is a small set problem, easily described by an eight or nine bit channel.  The sequence sizes are perfect for AI style sequence matching. And AI is widely used for this purpose, product selection and placement.