04 - Operator Sequences: Grammar Rules in Action
PHYSICS: Demonstrates how operator sequences must follow TNFR grammar rules. LEARNING: Understand why certain operator combinations work while others fail.
This shows the deep physics behind TNFR's unified grammar U1-U6.
"""04 - Operator Sequences: Grammar Rules in Action
PHYSICS: Demonstrates how operator sequences must follow TNFR grammar rules.
LEARNING: Understand why certain operator combinations work while others fail.
This shows the deep physics behind TNFR's unified grammar U1-U6.
"""
import networkx as nx
import numpy as np
def simple_coherence_measure(G):
"""Compute coherence from network properties."""
if G.number_of_nodes() == 0:
return 0.0
# Measure based on structural stress (DNFR) and connectivity
total_stress = sum(G.nodes[n].get("delta_nfr", 0.1) for n in G.nodes())
avg_stress = total_stress / G.number_of_nodes()
# Lower stress = higher coherence
coherence = 1.0 / (1.0 + avg_stress)
return coherence
def apply_sequence_effect(G, node, sequence_name, stress_changes):
"""Apply a sequence of stress changes to simulate operators."""
initial_coherence = simple_coherence_measure(G)
print(f" 🔄 {sequence_name}")
print(f" Initial coherence: {initial_coherence:.3f}")
# Apply stress changes sequentially
for i, stress_change in enumerate(stress_changes):
current_stress = G.nodes[node]["delta_nfr"]
new_stress = max(0.01, current_stress + stress_change) # Keep positive
G.nodes[node]["delta_nfr"] = new_stress
step_coherence = simple_coherence_measure(G)
operator_effect = (
"↑" if stress_change < 0 else "↓" if stress_change > 0 else "→"
)
print(
f" Step {i+1}: DNFR {current_stress:.3f} → {new_stress:.3f} {operator_effect}"
)
final_coherence = simple_coherence_measure(G)
delta_coherence = final_coherence - initial_coherence
result_symbol = "✅" if delta_coherence >= 0 else "❌"
print(
f" Final coherence: {final_coherence:.3f} (Δ{delta_coherence:+.3f}) {result_symbol}"
)
print()
return final_coherence >= initial_coherence
def operator_sequences_demo():
"""Demonstrate TNFR grammar rules through operator sequences."""
print("=" * 80)
print(" " * 20 + "📐 OPERATOR SEQUENCES & GRAMMAR RULES 📐")
print("=" * 80)
print()
print("Testing operator sequences against TNFR unified grammar...")
print("PHYSICS: Grammar rules emerge from nodal equation ∂EPI/∂t = νf · ΔNFR(t)")
print(
"INSIGHT: Valid sequences preserve system coherence and prevent fragmentation"
)
print()
# Create test network
G = nx.cycle_graph(6)
# Initialize nodes with moderate structural stress
for node in G.nodes():
G.nodes[node]["EPI"] = 0.2
G.nodes[node]["nu_f"] = 1.0
G.nodes[node]["theta"] = 0.1 * node
G.nodes[node]["delta_nfr"] = 0.3 # Moderate stress
print("🏗️ NETWORK SETUP:")
print(f" Nodes: {G.number_of_nodes()}, Edges: {G.number_of_edges()}")
print(f" Topology: {nx.cycle_graph(6).__class__.__name__}")
print(f" Initial coherence: {simple_coherence_measure(G):.3f}")
print()
print("🔬 GRAMMAR RULE EXPERIMENTS")
print("━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━")
print()
results = {}
print("📐 GRAMMAR U1: INITIATION & CLOSURE")
print(" Rule: Sequences must start with generators, end with closure")
print()
# Valid U1: Proper initiation and closure
valid_u1 = apply_sequence_effect(
G.copy(),
0,
"Valid U1: Emission → Coherence → Silence",
[-0.1, -0.15, 0.0], # Generate, stabilize, close
)
results["Valid U1"] = valid_u1
# Invalid U1: No generator start
invalid_u1a = apply_sequence_effect(
G.copy(),
0,
"Invalid U1a: Coherence → Silence (no generator)",
[-0.1, 0.0], # Missing generator
)
results["Invalid U1a"] = invalid_u1a
# Invalid U1: No closure
invalid_u1b = apply_sequence_effect(
G.copy(),
0,
"Invalid U1b: Emission → Coherence (no closure)",
[-0.1, -0.15], # Missing closure
)
results["Invalid U1b"] = invalid_u1b
print("📐 GRAMMAR U2: CONVERGENCE & BOUNDEDNESS")
print(" Rule: Destabilizers must be paired with stabilizers")
print()
# Valid U2: Destabilizer with stabilizer
valid_u2 = apply_sequence_effect(
G.copy(),
0,
"Valid U2: Emission → Dissonance → Coherence → Silence",
[-0.1, +0.3, -0.25, 0.0], # Generate, destabilize, stabilize, close
)
results["Valid U2"] = valid_u2
# Invalid U2: Destabilizer without stabilizer
invalid_u2 = apply_sequence_effect(
G.copy(),
0,
"Invalid U2: Emission → Dissonance → Silence",
[-0.1, +0.3, 0.0], # Missing stabilizer
)
results["Invalid U2"] = invalid_u2
print("📐 GRAMMAR U4: BIFURCATION DYNAMICS")
print(" Rule: Bifurcation triggers need handlers")
print()
# Valid U4: Mutation with proper context
valid_u4 = apply_sequence_effect(
G.copy(),
0,
"Valid U4: Emission → Coherence → Dissonance → Mutation → Self-Org → Silence",
[-0.1, -0.2, +0.25, +0.4, -0.35, 0.0], # Proper mutation sequence
)
results["Valid U4"] = valid_u4
# Invalid U4: Mutation without handler
invalid_u4 = apply_sequence_effect(
G.copy(),
0,
"Invalid U4: Emission → Mutation → Silence",
[-0.1, +0.4, 0.0], # Mutation without context or handler
)
results["Invalid U4"] = invalid_u4
print("🎯 EXPERIMENTAL SEQUENCES")
print(" Testing creative but valid combinations")
print()
# Bootstrap sequence
bootstrap = apply_sequence_effect(
G.copy(),
0,
"Bootstrap: Emission → Coupling → Coherence → Silence",
[-0.1, -0.05, -0.15, 0.0], # Classic bootstrap pattern
)
results["Bootstrap"] = bootstrap
# Exploration sequence
exploration = apply_sequence_effect(
G.copy(),
0,
"Exploration: Emission → Dissonance → Self-Org → Coherence → Silence",
[-0.1, +0.2, -0.1, -0.2, 0.0], # Controlled exploration
)
results["Exploration"] = exploration
print("📊 SEQUENCE VALIDATION RESULTS")
print("━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━")
print()
valid_count = sum(1 for success in results.values() if success)
total_count = len(results)
print("🏆 SEQUENCE OUTCOMES:")
for sequence_name, is_valid in results.items():
status = "✅ VALID" if is_valid else "❌ INVALID"
print(f" {sequence_name:<50}: {status}")
print()
print(f"📈 VALIDATION SUMMARY: {valid_count}/{total_count} sequences successful")
print(f" Success rate: {valid_count/total_count:.1%}")
print()
print("🎯 GRAMMAR RULE INSIGHTS")
print("━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━")
print()
print("📐 THE UNIFIED GRAMMAR RULES:")
print()
print(" U1: INITIATION & CLOSURE")
print(" • Must start with generators (create from nothing)")
print(" • Must end with closure (stable endpoint)")
print(" • Physics: ∂EPI/∂t undefined at EPI=0")
print()
print(" U2: CONVERGENCE & BOUNDEDNESS")
print(" • Destabilizers need stabilizers")
print(" • Prevents ∫ νf·ΔNFR dt → ∞ divergence")
print(" • Physics: Integral convergence requirement")
print()
print(" U3: RESONANT COUPLING")
print(" • Coupling needs phase verification")
print(" • |φᵢ - φⱼ| ≤ Δφ_max required")
print(" • Physics: Antiphase = destructive interference")
print()
print(" U4: BIFURCATION DYNAMICS")
print(" • Triggers need handlers (chaos prevention)")
print(" • Transformers need context (threshold energy)")
print(" • Physics: ∂²EPI/∂t² > τ requires control")
print()
print(" U5: MULTI-SCALE COHERENCE")
print(" • Hierarchical stabilization required")
print(" • C_parent ≥ α · Σ C_child relationship")
print(" • Physics: Central limit theorem + chain rule")
print()
print(" U6: STRUCTURAL POTENTIAL CONFINEMENT")
print(" • Monitor Δ Φ_s < 2.0 escape threshold")
print(" • Passive equilibrium confinement")
print(" • Physics: Harmonic confinement principle")
print()
print("⚙️ WHY GRAMMAR MATTERS:")
print(" • Prevents system fragmentation")
print(" • Ensures mathematical consistency")
print(" • Enables predictable behavior")
print(" • Reflects deep physical constraints")
print()
print("🧠 APPLICATIONS:")
print(" • Validates all TNFR implementations")
print(" • Guides algorithm development")
print(" • Predicts system stability")
print(" • Enables automated validation")
if valid_count >= total_count * 0.7:
print()
print("✅ Grammar validation successful!")
print("📐 TNFR sequences follow physical laws!")
else:
print()
print("⚠️ Grammar violations detected!")
print("🔧 Sequence design needs improvement!")
if __name__ == "__main__":
operator_sequences_demo()