Cosmic Lattice Theory explores whether a discrete relational substrate can recover familiar physical behavior and generate testable differences. It is presented as a developing theoretical framework—not an accepted unification of physics. Every claim must be traced to definitions, derivations, simulations, or proposed observations.
Questions worth building a program around.
A foundational physical model must do more than offer an evocative picture of the universe. Its structures need definitions, its quantities need units, and its dynamics need equations that can be compared with observations. CLT explores a discrete or relational foundation while treating recovery of familiar behavior as a central research obligation. The value of a candidate framework depends on what it explains quantitatively and what would distinguish it from neighboring approaches.
From an idea to inspectable work.
The proposed sequence begins with postulates and a minimal model. Researchers can then examine limiting behavior, conservation laws, symmetries, stability and dimensional consistency before adding cosmological interpretation. Toy simulations should expose sensitivity to resolution and parameter choices. Connections to gravity, quantum behavior and spacetime require explicit derivations rather than shared vocabulary alone. A comparison register should document where the model agrees with an existing framework, where it differs, and what observation could constrain that difference.
Can continuum symmetries emerge from a discrete relational model?
Which parameter regimes reproduce known physics without ad hoc repair?
What observable would distinguish the theory from existing frameworks?
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Publish a falsifiable core specification
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Release reproducible simulation notebooks
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Seek adversarial review from theoretical physicists
Where a contribution can matter.
Priority contributions include mathematical formalization, reproducible toy simulations, comparison with established approaches, and adversarial technical review. The public goal is a framework clear enough to evaluate, revise or reject on specific grounds.
Program support can help fund documentation, computation, reproducible tools and qualified review. Explore research partnerships or support the institute.