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 unit potential point charges 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 charge 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 charge.
- Pj(t < now) is the path history of the point charge.
- Each point charge 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 charge. A ( Pj(t) ⋂ Sk(t, Pk(te)) )
- This is massive unbounded parallelism.
- Action depends on the velocity and location of the emitter, the velocty and location of the receiver, and the absolute time between emission and action
- The self action case, j=k, occurs when a point charge speed exceeds its own field speed @.
- The regime of point charge 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 charge how to evolve its path.
- N.B. We sum over all pairs of point charges 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 millenia.
And now for something completely different.
Monty Python’s Flying Circus
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 starting to be deployed these environments.
Yet when we now look at the equation of nature, it is conceptually simple. We need to track the path history of every point charge in our simulation and evaluate the action for each discrete time delta path interval. From the path history of each point charge 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 charges 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 charges. The scalability issues seem to be the storage of paths at incredibly fine grain and the computation of all the action ⋂ path history operations over each time slice.

My intuition/guess (and I may be wrong) is that there are some scientific problems which could be more efficiently modeled with a brute force discrete time point charge 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 charges need only be updated at a fraction the frequency of the fast moving point charges. 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 npqg.inquiries@gmail.com.