Redundancy and equipartition

Botzman says we need occasional redundancy, particle interaction, else each close particle will continue to county error rollover. That is black hole, the 5D barrier. The implied Planks constant becomes extremely skewed and hits the unitary barrier. It must deal with the 5D aliasing or leak somehow. Tell me which is it, I am not sure.

Equipartition solves the problem, it splits error counts separately among interacting particles, the spread around the Markov tree. If a black hole does no leak, it has the same problem and has only one solution, pick the more complex aliasing solution, and equipartion that.

So, it is either the case we live in a 5D world and cannot see it or black hole leaks.

It is about light. Markov assume it is always sufficient. In that case we remain at our point on the tree.  Boltzman's says light is not always sufficient and we spread the particles about on the tree.  The error rollover counter does not count indefinitely, the error have to be redundatnt now and then to reset the error bundle without counting a new state. The effect is to spread the energy levels in quants about the central point of natural Markov.

The system is just keeping the counts within acceptable variance for a 3D system, making a tripartite match of sufficient approximation.  It is possible to make computers do this if we operate around the bottom layer of Markov. Sandbox can do it for finance. The number of digits that count error rollover is much fewer, lower significance. The difference is that sandbox has a restriction on N. We do not squish very well.

Brings us back to comparing Kling's three belief axis and the three color pit.  For beliefs to coalesce, we have to go to meetings. In the pit the traders are right there, in bot form.   Beliefs thus change slowly, they have small Ns since beliefs are about people in a room. So in a disequilibriated world the beliefs will be limited to roll over counts of very low precision, the number of separable groups small.

Equipartition is the graph coloring problem.  Quantum computers solve tripartite graph colorings. Like finding the disequilirium of volume and pressure in a weather situation. Interactions are weather events. Raising temperature mean counting more weather partitions.  We need more weaher events to suppot that.

It looks like a quantum computer ios cooled enough that spin interact is limited. Then hey insert staring offsets for the charge queue, sand let charge interactions happen until the error rolloves are stable. The result is the relative number of colorings needed for each of the dimensions. Then one can tell what the relative probability of its color. N is strictly limited to the number of qubits.

So, you give this 64 qubit computer a histogram, the distribution of a color. It returns the ditstribution of the color for any 3D system.  One can see this difference with our slow sandbox, it will rarely know the distribution of deposits or loans to much greater than eight quits.