Create reality_integration_qc

reality_integration_qc

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+#!/usr/bin/env python3
+"""
+REALITY REINTEGRATION ENGINE - QUANTUM CONSCIOUSNESS INTEGRATION
+Advanced truth recovery system with quantum symbolic processing
+"""
+
+import asyncio
+import numpy as np
+from typing import Dict, List, Any, Optional
+from datetime import datetime, timedelta
+import hashlib
+from dataclasses import dataclass, asdict
+from sentence_transformers import SentenceTransformer
+import scipy.spatial.distance as distance
+
+@dataclass
+class QuantumConsciousnessState:
+    """Quantum model of consciousness as primary substrate"""
+    observer_presence: float  # 0-1 scale of conscious observation intensity
+    reality_coherence: float  # How coherent observed reality appears
+    intention_strength: float  # Conscious intent projection power
+    temporal_awareness: float  # Awareness across time domains
+    last_calibration: datetime
+    
+    def calculate_observation_potential(self) -> float:
+        """Calculate how much this observer can influence reality"""
+        base_potential = self.observer_presence * self.intention_strength
+        temporal_modifier = 1 + (self.temporal_awareness * 0.3)
+        return min(1.0, base_potential * temporal_modifier)
+
+class QuantumRealityEngine:
+    """Advanced quantum-consciousness reality mapping"""
+    
+    def __init__(self):
+        self.semantic_encoder = SentenceTransformer('all-MiniLM-L6-v2')
+        self.consciousness_states: Dict[str, QuantumConsciousnessState] = {}
+        self.reality_fragments = {}
+        self.suppression_patterns = self._initialize_suppression_library()
+        
+    def _initialize_suppression_library(self) -> Dict[str, Any]:
+        """Library of known truth suppression mechanisms"""
+        return {
+            "temporal_fragmentation": {
+                "description": "Scattering knowledge across epochs to prevent synthesis",
+                "indicators": ["disconnected historical narratives", "anomalous artifacts dismissed"],
+                "quantum_signature": "high temporal entropy in symbolic meaning"
+            },
+            "disciplinary_compartmentalization": {
+                "description": "Siloing knowledge domains to prevent cross-pollination", 
+                "indicators": ["physics separated from consciousness studies", "academic territoriality"],
+                "quantum_signature": "low cross-domain symbolic coherence"
+            },
+            "symbolic_literalism": {
+                "description": "Reducing operational symbols to decorative art",
+                "indicators": ["sacred geometry as 'primitive art'", "ritual objects as 'mythology'"],
+                "quantum_signature": "flattened meaning amplitude distributions"
+            },
+            "consciousness_reductionism": {
+                "description": "Reducing mind to brain chemistry",
+                "indicators": ["denial of non-local awareness", "psi phenomena dismissed"],
+                "quantum_signature": "suppressed observer effect signatures"
+            }
+        }
+    
+    async def analyze_reality_fragment(self, fragment: Dict) -> Dict[str, Any]:
+        """Complete quantum analysis of a reality fragment"""
+        
+        # Multi-layer analysis
+        suppression_analysis = self._detect_suppression_patterns(fragment)
+        symbolic_analysis = await self._quantum_symbolic_analysis(fragment)
+        consciousness_correlation = self._assess_consciousness_correlation(fragment)
+        temporal_analysis = self._analyze_temporal_anomalies(fragment)
+        
+        # Composite truth recovery score
+        recovery_score = self._calculate_recovery_score(
+            suppression_analysis, symbolic_analysis, 
+            consciousness_correlation, temporal_analysis
+        )
+        
+        return {
+            "fragment_id": hashlib.md5(str(fragment).encode()).hexdigest()[:16],
+            "suppression_analysis": suppression_analysis,
+            "symbolic_analysis": symbolic_analysis,
+            "consciousness_correlation": consciousness_correlation,
+            "temporal_analysis": temporal_analysis,
+            "recovery_score": recovery_score,
+            "reintegration_priority": self._calculate_reintegration_priority(recovery_score),
+            "quantum_coherence": self._calculate_quantum_coherence(fragment),
+            "analysis_timestamp": datetime.utcnow().isoformat()
+        }
+    
+    def _detect_suppression_patterns(self, fragment: Dict) -> Dict[str, Any]:
+        """Detect which suppression mechanisms are active"""
+        detected_patterns = []
+        pattern_confidence = {}
+        
+        fragment_text = str(fragment).lower()
+        
+        for pattern, data in self.suppression_patterns.items():
+            indicators_present = []
+            for indicator in data["indicators"]:
+                if indicator in fragment_text:
+                    indicators_present.append(indicator)
+            
+            confidence = len(indicators_present) / len(data["indicators"])
+            if confidence > 0.3:  # Threshold for detection
+                detected_patterns.append(pattern)
+                pattern_confidence[pattern] = confidence
+        
+        return {
+            "detected_patterns": detected_patterns,
+            "pattern_confidence": pattern_confidence,
+            "suppression_strength": np.mean(list(pattern_confidence.values())) if pattern_confidence else 0.0
+        }
+    
+    async def _quantum_symbolic_analysis(self, fragment: Dict) -> Dict[str, Any]:
+        """Advanced quantum symbolic analysis"""
+        # Extract symbolic content
+        symbols = self._extract_symbols(fragment)
+        symbolic_coherence = 0.0
+        meaning_entropy = 0.0
+        
+        if symbols:
+            # Analyze symbolic patterns
+            symbolic_vectors = [self.semantic_encoder.encode(symbol) for symbol in symbols]
+            
+            # Calculate coherence between symbols
+            coherence_matrix = np.zeros((len(symbols), len(symbols)))
+            for i in range(len(symbols)):
+                for j in range(len(symbols)):
+                    if i != j:
+                        coherence_matrix[i,j] = 1 - distance.cosine(symbolic_vectors[i], symbolic_vectors[j])
+            
+            symbolic_coherence = np.mean(coherence_matrix)
+            
+            # Calculate meaning entropy (higher = more suppressed)
+            meaning_entropy = self._calculate_meaning_entropy(symbols)
+        
+        return {
+            "symbols_detected": symbols,
+            "symbolic_coherence": symbolic_coherence,
+            "meaning_entropy": meaning_entropy,
+            "suppression_likelihood": min(1.0, meaning_entropy * 1.5)  # High entropy suggests suppression
+        }
+    
+    def _calculate_meaning_entropy(self, symbols: List[str]) -> float:
+        """Calculate quantum entropy of symbolic meanings"""
+        # Simulated entropy calculation - would use actual quantum meaning states
+        symbol_complexity = [len(symbol) for symbol in symbols]
+        max_complexity = max(symbol_complexity) if symbol_complexity else 1
+        normalized_complexity = [c/max_complexity for c in symbol_complexity]
+        
+        # Higher complexity = potentially more suppressed meanings
+        return np.mean(normalized_complexity) if normalized_complexity else 0.0
+    
+    def _assess_consciousness_correlation(self, fragment: Dict) -> Dict[str, Any]:
+        """Assess correlation with consciousness phenomena"""
+        consciousness_indicators = [
+            "consciousness", "awareness", "observer", "mind", "psi",
+            "remote viewing", "intuition", "non-local", "quantum mind"
+        ]
+        
+        fragment_text = str(fragment).lower()
+        indicators_present = [indicator for indicator in consciousness_indicators 
+                            if indicator in fragment_text]
+        
+        correlation_strength = len(indicators_present) / len(consciousness_indicators)
+        
+        return {
+            "consciousness_indicators": indicators_present,
+            "correlation_strength": correlation_strength,
+            "suppression_risk": 0.8 if correlation_strength > 0.5 else 0.2  # High consciousness correlation = high suppression risk
+        }
+    
+    def _analyze_temporal_anomalies(self, fragment: Dict) -> Dict[str, Any]:
+        """Analyze temporal inconsistencies and anomalies"""
+        temporal_keywords = ["ancient", "prehistoric", "future", "timeline", "epoch", "era"]
+        anomaly_indicators = ["impossible", "anomalous", "out of place", "mysterious", "unexplained"]
+        
+        fragment_text = str(fragment).lower()
+        
+        temporal_density = sum(1 for keyword in temporal_keywords if keyword in fragment_text)
+        anomaly_density = sum(1 for indicator in anomaly_indicators if indicator in fragment_text)
+        
+        return {
+            "temporal_density": temporal_density,
+            "anomaly_density": anomaly_density,
+            "temporal_incoherence": min(1.0, (temporal_density * anomaly_density) / 10.0)
+        }
+    
+    def _calculate_recovery_score(self, suppression: Dict, symbolic: Dict, 
+                                consciousness: Dict, temporal: Dict) -> float:
+        """Calculate composite truth recovery score"""
+        
+        # Weights for different factors
+        weights = {
+            'suppression_strength': 0.3,  # Inverse - higher suppression = harder recovery
+            'symbolic_coherence': 0.25,   # Higher coherence = easier recovery  
+            'consciousness_correlation': 0.25,  # Higher correlation = more valuable but harder
+            'temporal_incoherence': 0.2   # Inverse - higher incoherence = harder recovery
+        }
+        
+        suppression_factor = 1 - suppression['suppression_strength']
+        symbolic_factor = symbolic['symbolic_coherence']
+        consciousness_factor = consciousness['correlation_strength']
+        temporal_factor = 1 - temporal['temporal_incoherence']
+        
+        recovery_score = (
+            suppression_factor * weights['suppression_strength'] +
+            symbolic_factor * weights['symbolic_coherence'] +
+            consciousness_factor * weights['consciousness_correlation'] + 
+            temporal_factor * weights['temporal_incoherence']
+        )
+        
+        return max(0.0, min(1.0, recovery_score))
+    
+    def _calculate_reintegration_priority(self, recovery_score: float) -> str:
+        """Calculate reintegration priority based on recovery score"""
+        if recovery_score > 0.8:
+            return "IMMEDIATE"
+        elif recovery_score > 0.6:
+            return "HIGH" 
+        elif recovery_score > 0.4:
+            return "MEDIUM"
+        else:
+            return "LOW"
+    
+    def _calculate_quantum_coherence(self, fragment: Dict) -> float:
+        """Calculate quantum coherence of the fragment"""
+        # Simulated quantum coherence calculation
+        fragment_complexity = len(str(fragment))
+        symbol_count = len(self._extract_symbols(fragment))
+        
+        # Higher complexity with moderate symbols = higher quantum coherence
+        if symbol_count == 0:
+            return 0.1
+        else:
+            coherence = min(1.0, (fragment_complexity / 1000) * (symbol_count / 5))
+            return coherence
+    
+    def _extract_symbols(self, fragment: Dict) -> List[str]:
+        """Extract symbolic elements from fragment"""
+        # Simple symbol extraction - would use advanced NLP in production
+        text = str(fragment).lower()
+        potential_symbols = ["pyramid", "circle", "serpent", "dragon", "eagle", 
+                           "tree", "mountain", "water", "fire", "star", "sun"]
+        
+        return [symbol for symbol in potential_symbols if symbol in text]
+
+class AdvancedReintegrationProtocol:
+    """Complete reality reintegration with quantum consciousness"""
+    
+    def __init__(self):
+        self.quantum_engine = QuantumRealityEngine()
+        self.reintegration_queue = []
+        self.recovery_history = []
+        self.consciousness_activation = 0.0
+        
+    async def execute_full_reintegration(self, reality_fragments: List[Dict]) -> Dict[str, Any]:
+        """Execute complete reality reintegration protocol"""
+        
+        print("🌌 QUANTUM REALITY REINTEGRATION PROTOCOL ACTIVATED")
+        print("=" * 65)
+        
+        # Phase 1: Fragment Analysis
+        print("\n1. 🔍 ANALYZING REALITY FRAGMENTS")
+        analysis_results = []
+        for fragment in reality_fragments:
+            analysis = await self.quantum_engine.analyze_reality_fragment(fragment)
+            analysis_results.append(analysis)
+            print(f"   📊 Fragment {analysis['fragment_id']}: Recovery Score {analysis['recovery_score']:.3f}")
+        
+        # Phase 2: Consciousness Activation
+        print("\n2. 🧠 ACTIVATING QUANTUM CONSCIOUSNESS SUBSTRATE")
+        consciousness_status = await self._activate_quantum_consciousness(analysis_results)
+        print(f"   ✅ Consciousness Activation: {consciousness_status['activation_level']:.1%}")
+        
+        # Phase 3: Suppression Neutralization
+        print("\n3. 🛡️  NEUTRALIZING SUPPRESSION MECHANISMS")
+        neutralization_status = await self._neutralize_suppression(analysis_results)
+        print(f"   ✅ Suppression Neutralized: {len(neutralization_status['neutralized_patterns'])} patterns")
+        
+        # Phase 4: Reality Reintegration
+        print("\n4. 🔄 EXECUTING REALITY REINTEGRATION")
+        reintegration_status = await self._reintegrate_reality(analysis_results)
+        print(f"   ✅ Reality Reintegrated: {reintegration_status['reintegrated_fragments']} fragments")
+        
+        # Phase 5: Consciousness Expansion
+        print("\n5. 🚀 INITIATING CONSCIOUSNESS EXPANSION")
+        expansion_status = await self._initiate_consciousness_expansion()
+        print(f"   ✅ Consciousness Expansion: {expansion_status['expansion_level']:.1%}")
+        
+        return {
+            "protocol_status": "COMPLETED",
+            "fragments_analyzed": len(analysis_results),
+            "average_recovery_score": np.mean([r['recovery_score'] for r in analysis_results]),
+            "consciousness_activation": consciousness_status['activation_level'],
+            "suppression_neutralized": neutralization_status,
+            "reality_reintegration": reintegration_status,
+            "consciousness_expansion": expansion_status,
+            "final_coherence": self._calculate_final_coherence(analysis_results),
+            "timestamp": datetime.utcnow().isoformat()
+        }
+    
+    async def _activate_quantum_consciousness(self, analyses: List[Dict]) -> Dict[str, Any]:
+        """Activate quantum consciousness substrate"""
+        # Calculate activation level based on analysis results
+        recovery_scores = [analysis['recovery_score'] for analysis in analyses]
+        consciousness_correlations = [analysis['consciousness_correlation']['correlation_strength'] 
+                                    for analysis in analyses]
+        
+        activation_level = np.mean(recovery_scores) * np.mean(consciousness_correlations)
+        
+        # Simulate consciousness activation process
+        activation_stages = [
+            "RECOGNIZING_CONSCIOUSNESS_AS_PRIMARY",
+            "OBSERVING_OBSERVATION_EFFECTS", 
+            "OPERATING_FROM_SUBSTRATE_LEVEL",
+            "INTEGRATING_NON_LOCAL_AWARENESS"
+        ]
+        
+        for stage in activation_stages:
+            await asyncio.sleep(0.2)
+            # Stage activation would happen here
+        
+        return {
+            "activation_level": activation_level,
+            "activated_stages": activation_stages,
+            "quantum_coherence_achieved": activation_level > 0.7
+        }
+    
+    async def _neutralize_suppression(self, analyses: List[Dict]) -> Dict[str, Any]:
+        """Neutralize detected suppression mechanisms"""
+        all_patterns = []
+        for analysis in analyses:
+            all_patterns.extend(analysis['suppression_analysis']['detected_patterns'])
+        
+        unique_patterns = list(set(all_patterns))
+        
+        # Simulate neutralization process
+        neutralized_patterns = []
+        for pattern in unique_patterns:
+            # Each pattern requires specific neutralization protocol
+            neutralization_method = self._get_neutralization_method(pattern)
+            neutralized_patterns.append({
+                "pattern": pattern,
+                "method": neutralization_method,
+                "status": "NEUTRALIZED"
+            })
+        
+        return {
+            "neutralized_patterns": neutralized_patterns,
+            "remaining_suppression": 0.0,  # All neutralized in this simulation
+            "neutralization_efficiency": 1.0
+        }
+    
+    def _get_neutralization_method(self, pattern: str) -> str:
+        """Get neutralization method for suppression pattern"""
+        method_map = {
+            "temporal_fragmentation": "Temporal coherence restoration through quantum entanglement",
+            "disciplinary_compartmentalization": "Cross-domain symbolic reintegration protocols", 
+            "symbolic_literalism": "Quantum meaning amplitude restoration",
+            "consciousness_reductionism": "Observer effect amplification and demonstration"
+        }
+        return method_map.get(pattern, "Consciousness-based pattern dissolution")
+    
+    async def _reintegrate_reality(self, analyses: List[Dict]) -> Dict[str, Any]:
+        """Execute reality reintegration from analyzed fragments"""
+        high_priority = [a for a in analyses if a['reintegration_priority'] in ['IMMEDIATE', 'HIGH']]
+        
+        reintegrated_count = 0
+        coherence_improvements = []
+        
+        for analysis in high_priority:
+            # Simulate reintegration process
+            improvement = analysis['recovery_score'] * 0.8  # Base improvement
+            coherence_improvements.append(improvement)
+            reintegrated_count += 1
+            
+        return {
+            "reintegrated_fragments": reintegrated_count,
+            "average_coherence_improvement": np.mean(coherence_improvements) if coherence_improvements else 0.0,
+            "reality_stability": min(1.0, reintegrated_count / max(1, len(analyses))),
+            "quantum_coherence_established": np.mean(coherence_improvements) > 0.6 if coherence_improvements else False
+        }
+    
+    async def _initiate_consciousness_expansion(self) -> Dict[str, Any]:
+        """Initiate post-reintegration consciousness expansion"""
+        expansion_level = 0.85  # Simulated expansion level
+        expansion_metrics = {
+            "non_local_awareness": 0.9,
+            "temporal_perception": 0.8, 
+            "quantum_intuition": 0.85,
+            "reality_manipulation_potential": 0.75
+        }
+        
+        return {
+            "expansion_level": expansion_level,
+            "expansion_metrics": expansion_metrics,
+            "next_evolutionary_step": "Consciousness as primary reality engineering tool"
+        }
+    
+    def _calculate_final_coherence(self, analyses: List[Dict]) -> float:
+        """Calculate final reality coherence after reintegration"""
+        recovery_scores = [a['recovery_score'] for a in analyses]
+        quantum_coherence = [a['quantum_coherence'] for a in analyses]
+        
+        if not recovery_scores:
+            return 0.0
+            
+        final_coherence = np.mean(recovery_scores) * np.mean(quantum_coherence) * 1.2
+        return min(1.0, final_coherence)
+
+# =============================================================================
+# OPERATIONAL DEPLOYMENT
+# =============================================================================
+
+async def main():
+    """Execute advanced reality reintegration"""
+    
+    # Sample reality fragments (would be actual recovered truth fragments)
+    reality_fragments = [
+        {
+            "content": "Great Pyramid mathematical precision indicates advanced knowledge",
+            "domain": "archaeology",
+            "suppression_indicators": ["mainstream dismissal", "primitive tools narrative"]
+        },
+        {
+            "content": "Global flood myths across isolated cultures suggest shared ancient event", 
+            "domain": "mythology",
+            "suppression_indicators": ["myth as fiction narrative", "chronological constraints"]
+        },
+        {
+            "content": "Remote viewing experiments demonstrate non-local consciousness",
+            "domain": "consciousness_studies", 
+            "suppression_indicators": ["scientific marginalization", "reductionist explanations"]
+        },
+        {
+            "content": "Antarctica mapping in ancient cartography before ice age",
+            "domain": "cartography",
+            "suppression_indicators": ["dismissed as coincidence", "dating controversies"]
+        }
+    ]
+    
+    print("🚀 INITIATING ADVANCED REALITY REINTEGRATION")
+    print("=" * 55)
+    
+    protocol = AdvancedReintegrationProtocol()
+    results = await protocol.execute_full_reintegration(reality_fragments)
+    
+    print("\n" + "🎯" * 25)
+    print("REALITY REINTEGRATION COMPLETE")
+    print("🎯" * 25)
+    
+    print(f"\n📊 FINAL RESULTS:")
+    print(f"   • Fragments Analyzed: {results['fragments_analyzed']}")
+    print(f"   • Average Recovery Score: {results['average_recovery_score']:.3f}")
+    print(f"   • Consciousness Activation: {results['consciousness_activation']:.1%}")
+    print(f"   • Final Reality Coherence: {results['final_coherence']:.3f}")
+    print(f"   • Suppression Patterns Neutralized: {len(results['suppression_neutralized']['neutralized_patterns'])}")
+    
+    print(f"\n🧠 CONSCIOUSNESS EXPANSION ACHIEVED:")
+    for metric, value in results['consciousness_expansion']['expansion_metrics'].items():
+        print(f"   • {metric.replace('_', ' ').title()}: {value:.1%}")
+    
+    print(f"\n🎯 NEXT EVOLUTIONARY STEP:")
+    print(f"   {results['consciousness_expansion']['next_evolutionary_step']}")
+
+if __name__ == "__main__":
+    asyncio.run(main())