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Sym9 & SNFT Unified Explorer

An interactive hub for exploring Symbolic Numerical Field Theory (SNFT) convergence, scaling laws, digit symbology, and non-linear numerical attractors.

Digit Symbology & Number Theory

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:

Sym9 Adaptive Transforms

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).

SNFT 5-Digit Space

Batch processing of numerical intervals to discover global attractors, convergence landscapes, and mapping macroscopic scaling behaviors across thousands of integers.

Resonance Patterns

Analysis of numbers displaying specific resonances (like containing "27", "127", or "3141") to see how symbol-level traits perturb macroscopic convergence.

Theoretical Foundations

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.

  • Universality: We often find that regardless of the initial starting band (10000 vs 90000), halting times fall into universal statistical distributions.
  • Gate Functions: Specific transform steps (like the 27-Gate or Cubic Gate) act as filters, rapidly collapsing entropy for specific sets of integers.
  • Attractors: Terminal nodes (like 0, 90, 729, or cycle-loops) represent the lowest energy states of the arithmetic field.

Sym9 Transformation Explorer

Simulate the exact trajectory of a single seed integer using the Enhanced Adaptive Transform ruleset. Observe how specific algorithmic "gates" alter the descent curve.

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Steps Taken
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Path Trajectory

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SNFT 5-Digit Batch Framework

Execute transformations across thousands of integers to map the macro-landscape. Discover statistical norms, convergence efficiencies, and global attractors within the 10000-99999 space.

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Avg Convergence
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Attractor Landscape & Patterns

Discoveries & Anomalies

This panel isolates numbers with unusual behaviors discovered during SNFT batch processing: extreme efficiencies, fast convergence, or unmapped cyclic attractors.

New Patterns Found
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Total Anomalies
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Pattern Type Count Avg Steps Efficiency Primary Attractor
Run an SNFT Batch Analysis to populate discoveries.