The image below shows the evolution equation of nature and the universe. This is it! Everything emerges from this equation and a density of energetic point potentials in Euclidean time and space.
Let’s go through the equation step by step.
- A single evolution equation marches forward in absolute time throughout Euclidean 3D space.
- Absolute time, which is an abstract concept, moves forward continuously.
- At this level, absolute time is implemented by the speed of emitted potential.
- Each point potential j follows a continuous path Pj(t) described by (t, x, y, z, x’, y’, z’) j
- Pj(t = now) is the current location of the point potential.
- Pj(t < now) is the path history of the point potential.
- Each point potential j continuously emits a Dirac sphere potential described by Sj(t, Pj(te)) where t > te
- The absolute physical location where a Dirac sphere potential is emitted is an unchanging characteristic of that particular expanding Dirac sphere.
- Dirac sphere potentials expand at the universal constant rate @ = dr/dt
- The speed of light c, is emergent from field speed @.
- Action occurs when a Dirac sphere potential intersects a point potential. A ( Pj(t) ⋂ Sk(t, Pk(te)) )
- This is massive unbounded parallelism.
- Action depends on the velocity and location of the emitter, the velocity and location of the receiver, and the absolute time between emission and action
- Action at the symmetry breaking point may very well be the case where randomness is introduced in the outcome of the action. Conjecture: There are one or more effects around the symmetry breaking point that may explain why the universe is not deterministic, and why we have free will.
- The self action case, j=k, occurs when a point potential speed exceeds its own field speed @.
- The regime of point potential self action is unexplored in science and geometry to the best of my knowledge.
- This regime can lead to behaviour that is non-intuitive from a classical point of view.
- Net action, the superposition of all actions on Pj(t), tells the point potential how to evolve its path.
- N.B. We sum over all pairs of point potential j and k, including the case where j=k from the self action regime.
The evolution equation of the universe leads to emergence of assemblies that implement the particles of the standard model. This is the simple equation that intelligent life has sought for millennia.
Certainly, science can build bespoke models like general relativity and the quantum theories for physics, and lambda cold dark matter for cosmology. Applying those modeled theories can require tremendous compute and memory resources on massively parallel supercomputers. Enormous Ai models are also deployed in these environments.
Yet when we look at the equation of nature, it is conceptually simple. We need to track the path history of every point potential in our simulation and evaluate the action for each discrete time delta path interval. From the path history of each point potential we can calculate the present radius and magnitude of each Dirac sphere. So at the crudest brute force approach we have N paths to track.
Consider that fermion and photon assemblies have 12 point potentials and nucleons each have 36. Higgs clusters have 24. Therefore, if one can provide the proper initial and bounding conditions we can begin simulating systems with tens to hundreds of point potentials. The scalability issues seem to be the storage of paths at incredibly fine grain and the computation of all the action ⋂ path history intersection operations over each time slice.
I conjecture that there are some scientific problems which could be more efficiently modeled with a brute force discrete time point potential simulation than current techniques. Furthermore, I foresee the opportunity for simulation software that can optimize the simulations. Instead of “renormalization” the optimizer can simply realize that the paths of slow point potentials need only be updated at a fraction the frequency of the fast moving point potentials. That is the tip of the iceberg in optimization — there is plenty of opportunity for simulation efficiency. I’ve written about this in my simulation posts.
J Mark Morris : Boston : Massachusetts
p.s. There may be an even more elegant notation for the equation of the universe. Feel free to reach out to me with improvement suggestions at inquiries@neoclassical.ai
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