An interactive hub for exploring Symbolic Numerical Field Theory (SNFT) convergence, scaling laws, digit symbology, and non-linear numerical attractors.
In Symbolic Numerical Field Theory (SNFT), numbers are not merely magnitudes; they possess structural traits stemming from their base-10 digit symbology. The spatial placement, sum, modular congruence, and internal patterns (like palindromes or arithmetic sequences) form a "field" of forces guiding the transformation of an integer through iterative maps.
This unified explorer brings together two primary modalities of this theory:
Single-path simulations focusing on the "Sym9" rulesets — highly non-linear, adaptive maps incorporating digit sums, modular arithmetic, and cubic gates (e.g., subtracting cubes of first/last digits).
Batch processing of numerical intervals to discover global attractors, convergence landscapes, and mapping macroscopic scaling behaviors across thousands of integers.
Analysis of numbers displaying specific resonances (like containing "27", "127", or "3141") to see how symbol-level traits perturb macroscopic convergence.
Numerical Attractor Descent Curves (NADCs) map the convergence from a highly energetic "seed" down to stable loops or static zeros. SNFT explores these paths not in continuous phase space, but in discrete, integer-based topology.
Simulate the exact trajectory of a single seed integer using the Enhanced Adaptive Transform ruleset. Observe how specific algorithmic "gates" alter the descent curve.
Execute transformations across thousands of integers to map the macro-landscape. Discover statistical norms, convergence efficiencies, and global attractors within the 10000-99999 space.
This panel isolates numbers with unusual behaviors discovered during SNFT batch processing: extreme efficiencies, fast convergence, or unmapped cyclic attractors.
| Pattern Type | Count | Avg Steps | Efficiency | Primary Attractor |
|---|---|---|---|---|
| Run an SNFT Batch Analysis to populate discoveries. | ||||