A Class of Models with the Potential to Represent Fundamental Physics
  1. Introduction
  2. Basic Form of Models
  3. Typical Behaviors
  4. Limiting Behavior and Emergent Geometry
  5. The Updating Process for String Substitution Systems
  6. The Updating Process in Our Models
  7. Equivalence and Computation in Our Models
  8. Potential Relation to Physics
  9. Additional Material
  10. References
  11. Index

2.2 First Example of a Rule

The core of our models are rules for rewriting collections of relations. A very simple example of a rule is:

{{x, y}} -> {{x, y}, {y, z}}

Here x, y and z stand for any elements. (The elements they stand for need not be distinct; for example, x and y could both stand for the element 1.) The rule states that wherever a relation that matches {x,y} appears, it should be replaced by {{x ,y},{y,z}}, where z is a new element. So given {{1, 2}} the rule will produce {{1,2},{2,}} where is a new element. The label for the new element could be anythingso long as it is distinct from 1 and 2. Here we will use 3, so that the result of applying the rule to {{1,2}} becomes:

{{1, 2}, {2, 3}}

If one applies the rule again, it will now operate again on {1,2}, and also on {2,3}. On {1,2} it again gives {{1,2},{2,}}, but now the new node cannot be labeled 3, because that label is already takenso instead we will label it 4. When the rule operates on {2,3} it gives {{2,3},{3,}}, where again is a new node, which can now be labeled 5. Combining these gives the final result:

{{1, 2}, {2, 4}, {2, 3}, {3, 5}}

(We have written this so that the results from {{1,2}} are followed by those from {{2,3}}but there is no significance to the order in which the relations appear.)

In graphical terms, the rule we have used is

RulePlot[ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}], VertexLabels -> Automatic, "RulePartsAspectRatio" -> 0.25]

and the sequence of steps is:

ResourceFunction["WolframModelPlot"][#, VertexLabels -> Automatic] & /@ ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}, {{1, 2}}, 2, "StatesList"]

It is important to note that all that matters in these graphs is their connectivity. Where nodes are placed on the page in drawing the graph has no fundamental significance; it is usually just done to make the graphs as easy to read as possible.

Continuing to apply the same rule for three more steps gives:

ResourceFunction["WolframModelPlot"][#, VertexLabels -> Automatic] & /@ ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}, {{1, 2}}, 4, "StatesList"]

Laying out nodes differently makes it easier to see some features of the graphs:

Graph[Rule @@@ #, VertexLabels -> Automatic, VertexStyle -> ResourceFunction["WolframPhysicsProjectStyleData"]["SpatialGraph", "VertexStyle"], EdgeStyle -> ResourceFunction["WolframPhysicsProjectStyleData"]["SpatialGraph", "EdgeLineStyle"], GraphLayout -> "LayeredDigraphEmbedding"] & /@ ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}, {{1, 2}}, 4, "StatesList"]

Continuing for a few more steps with the original layout gives the result:

ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}, {{1, 2}}, 8, "StatesPlotsList"]

Showing the last 3 steps with the other layout makes it a little clearer what is going on:

Graph[Rule @@@ #, GraphLayout -> "LayeredDigraphEmbedding", VertexStyle -> ResourceFunction["WolframPhysicsProjectStyleData"]["SpatialGraph", "VertexStyle"], EdgeStyle -> ResourceFunction["WolframPhysicsProjectStyleData"]["SpatialGraph", "EdgeLineStyle"], AspectRatio -> 1/3] & /@ Take[ResourceFunction[ "WolframModel"][{{{x, y}} -> {{x, y}, {y, z}}}, {{1, 2}}, 8, "StatesList"], -3]

The rule is generating a binomial tree, with 2n edges (relations) and 2n+1 nodes (distinct elements) at step n (and with Binomial[n, s1] nodes at level s).