retro causal linguistic module

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
QUANTUM LINGUISTIC TRUTH RESONANCE ENGINE
Advanced Multilinguistic Truth Binding with Retrocausal Validation
Integration of All Enhancement Suggestions
"""

import numpy as np
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Any, Optional, Tuple
import hashlib
import re
from collections import Counter
import asyncio
import quantum
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.kdf.hkdf import HKDF
from cryptography.hazmat.backends import default_backend
import scipy.stats as stats
from datetime import datetime
import json

class LanguageEra(Enum):
    """Comprehensive language eras including proto-human and indigenous systems"""
    PROTO_HUMAN_GESTURAL = "proto_human_gestural"  # Pre-linguistic symbolic communication
    PROTO_HUMAN_VOCAL = "proto_human_vocal"       # Pre-writing vocal patterns
    SUMERIAN = "sumerian"                         # ~3500 BCE
    EGYPTIAN_HIEROGLYPHIC = "egyptian"            # ~3200 BCE
    ELAMITE = "elamite"                           # ~3000 BCE
    AKKADIAN = "akkadian"                         # ~2500 BCE
    EBLAITE = "eblaite"                           # ~2400 BCE
    HITTITE = "hittite"                           # ~1600 BCE
    MYCENAEAN_GREEK = "mycenaean_greek"           # ~1450 BCE
    UGARITIC = "ugaritic"                         # ~1400 BCE
    PHOENICIAN = "phoenician"                     # ~1200 BCE
    ANCIENT_CHINESE = "ancient_chinese"           # ~1200 BCE
    SANSKRIT = "sanskrit"                         # ~1000 BCE
    MAYAN = "mayan"                               # ~1000 BCE
    OLMEC = "olmec"                               # ~1200 BCE
    HEBREW = "hebrew"                             # ~1000 BCE
    ARAMAIC = "aramaic"                           # ~900 BCE
    LATIN = "latin"                               # ~700 BCE
    ANCIENT_GREEK = "ancient_greek"               # ~700 BCE
    NAVAHO = "navaho"                             # ~1400 CE (continuous tradition)
    ABORIGINAL = "aboriginal"                     # ~50,000 BCE (continuous)

class LinguisticTruthMarker(Enum):
    """Enhanced truth marker taxonomy"""
    COSMOLOGICAL_ALIGNMENT = "cosmological_alignment"
    SACRED_GEOMETRY = "sacred_geometry"
    NUMEROLOGICAL_ENCODING = "numerological_encoding"
    PHONETIC_RESONANCE = "phonetic_resonance"
    SYMBOLIC_CORRESPONDENCE = "symbolic_correspondence"
    TEMPORAL_CYCLES = "temporal_cycles"
    RETROCAUSAL_ECHO = "retrocausal_echo"
    CONSCIOUSNESS_RESONANCE = "consciousness_resonance"
    QUANTUM_ENTANGLEMENT = "quantum_entanglement"
    MORPHIC_RESONANCE = "morphic_resonance"

class TruthConsensusLevel(Enum):
    """Levels of cross-linguistic truth consensus"""
    SINGLE_SOURCE = "single_source"
    REGIONAL_CONSENSUS = "regional_consensus"
    HEMISPHERIC_CONSENSUS = "hemispheric_consensus"
    GLOBAL_CONSENSUS = "global_consensus"
    TEMPORAL_CONSENSUS = "temporal_consensus"  # Across time periods
    UNIVERSAL_CONSENSUS = "universal_consensus"

@dataclass
class CryptographicTruthSignature:
    """Cryptographic signature for truth patterns across language families"""
    truth_hash: str
    cross_linguistic_proof: str
    temporal_validation_hash: str
    quantum_entanglement_signature: str
    retrocausal_verification: str
    consensus_proof: str

@dataclass
class AncientLanguage:
    """Enhanced ancient language data structure with quantum properties"""
    era: LanguageEra
    time_period: Tuple[int, int]
    writing_system: str
    sample_script: List[str] = field(default_factory=list)
    truth_markers: List[LinguisticTruthMarker] = field(default_factory=list)
    modern_equivalents: Dict[str, str] = field(default_factory=dict)
    resonance_frequency: float = 0.0
    quantum_coherence: float = 0.0
    retrocausal_potential: float = 0.0
    consciousness_coupling: float = 0.0
    morphic_field_strength: float = 0.0
    
    def __post_init__(self):
        """Calculate advanced resonance properties"""
        age = abs(self.time_period[0])
        complexity = len(self.sample_script) / 10
        marker_strength = len(self.truth_markers) * 0.1
        
        # Base resonance with quantum enhancement
        self.resonance_frequency = min(0.98, 0.3 + (age / 10000) + complexity + marker_strength)
        
        # Quantum coherence based on symbolic complexity
        self.quantum_coherence = min(0.95, 0.2 + (len(self.sample_script) * 0.05) + (age / 20000))
        
        # Retrocausal potential (older = more potential)
        self.retrocausal_potential = min(0.9, age / 15000)
        
        # Consciousness coupling (based on truth marker types)
        consciousness_markers = {LinguisticTruthMarker.CONSCIOUSNESS_RESONANCE, 
                               LinguisticTruthMarker.QUANTUM_ENTANGLEMENT}
        self.consciousness_coupling = len(consciousness_markers.intersection(self.truth_markers)) * 0.3
        
        # Morphic field strength (collective recognition)
        self.morphic_field_strength = min(0.85, 0.1 + (age / 25000) + (len(self.modern_equivalents) * 0.1))

@dataclass
class LinguisticTruthMatch:
    """Enhanced truth match with quantum and cryptographic properties"""
    language: AncientLanguage
    matched_patterns: List[str]
    confidence: float
    truth_markers_detected: List[LinguisticTruthMarker]
    cross_linguistic_correlations: List[str]
    temporal_coherence: float
    symbolic_resonance: float
    quantum_entanglement_score: float
    retrocausal_influence: float
    consciousness_alignment: float
    cryptographic_signature: CryptographicTruthSignature
    consensus_level: TruthConsensusLevel
    morphic_resonance_strength: float

@dataclass
class QuantumLinguisticState:
    """Quantum state representation of linguistic truth"""
    superposition_states: List[str]
    entanglement_patterns: Dict[str, float]
    coherence_level: float
    collapse_probability: float
    temporal_echoes: List[int]

class AdvancedMultilinguisticTruthBinder:
    """
    Ultimate truth binding through quantum linguistic resonance
    Integrates all enhancement suggestions
    """
    
    def __init__(self):
        self.language_corpus = self._initialize_comprehensive_languages()
        self.pattern_analyzer = AdvancedLinguisticPatternAnalyzer()
        self.temporal_validator = QuantumTemporalValidator()
        self.symbolic_decoder = QuantumSymbolicDecoder()
        self.cryptographic_prover = LinguisticCryptographicProver()
        self.quantum_processor = QuantumLinguisticProcessor()
        self.retrocausal_validator = RetrocausalLinguisticValidator()
        self.consensus_engine = TruthConsensusEngine()
        
    def _initialize_comprehensive_languages(self) -> Dict[LanguageEra, AncientLanguage]:
        """Initialize comprehensive language database with all enhancements"""
        languages = {
            LanguageEra.PROTO_HUMAN_GESTURAL: AncientLanguage(
                era=LanguageEra.PROTO_HUMAN_GESTURAL,
                time_period=(-100000, -3500),
                writing_system="Gestural/Symbolic",
                sample_script=["○", "△", "□", "卍", "⚡"],  # Universal symbols
                truth_markers=[
                    LinguisticTruthMarker.SYMBOLIC_CORRESPONDENCE,
                    LinguisticTruthMarker.CONSCIOUSNESS_RESONANCE,
                    LinguisticTruthMarker.MORPHIC_RESONANCE
                ],
                modern_equivalents={
                    "circle": "wholeness",
                    "triangle": "trinity", 
                    "spiral": "evolution"
                },
                resonance_frequency=0.95,
                quantum_coherence=0.88,
                retrocausal_potential=0.92,
                consciousness_coupling=0.85,
                morphic_field_strength=0.90
            ),
            
            LanguageEra.SUMERIAN: AncientLanguage(
                era=LanguageEra.SUMERIAN,
                time_period=(-3500, -2000),
                writing_system="Cuneiform",
                sample_script=["𒀭", "𒆠", "𒌋", "𒂍", "𒈬"],
                truth_markers=[
                    LinguisticTruthMarker.COSMOLOGICAL_ALIGNMENT,
                    LinguisticTruthMarker.NUMEROLOGICAL_ENCODING,
                    LinguisticTruthMarker.SACRED_GEOMETRY,
                    LinguisticTruthMarker.RETROCAUSAL_ECHO
                ],
                modern_equivalents={
                    "dingir": "divine",
                    "ki": "earth", 
                    "an": "heaven",
                    "me": "cosmic principles"
                },
                resonance_frequency=0.92,
                quantum_coherence=0.85,
                retrocausal_potential=0.88,
                consciousness_coupling=0.75,
                morphic_field_strength=0.82
            ),
            
            LanguageEra.MAYAN: AncientLanguage(
                era=LanguageEra.MAYAN,
                time_period=(-1000, 1500),
                writing_system="Mayan Hieroglyphs",
                sample_script=["𓃒", "𓆑", "𓁰", "𓂻", "𓆼"],  # Mayan glyph approximations
                truth_markers=[
                    LinguisticTruthMarker.TEMPORAL_CYCLES,
                    LinguisticTruthMarker.COSMOLOGICAL_ALIGNMENT,
                    LinguisticTruthMarker.NUMEROLOGICAL_ENCODING,
                    LinguisticTruthMarker.QUANTUM_ENTANGLEMENT
                ],
                modern_equivalents={
                    "kin": "time/sun",
                    "ch'ulel": "spiritual essence",
                    "k'uh": "divine",
                    "tzolk'in": "sacred calendar"
                },
                resonance_frequency=0.87,
                quantum_coherence=0.82,
                retrocausal_potential=0.79,
                consciousness_coupling=0.80,
                morphic_field_strength=0.78
            ),
            
            LanguageEra.ABORIGINAL: AncientLanguage(
                era=LanguageEra.ABORIGINAL,
                time_period=(-50000, 2024),
                writing_system="Oral/Songline",
                sample_script=["🌀", "🕒", "🌏", "🎵", "👣"],  # Symbolic representations
                truth_markers=[
                    LinguisticTruthMarker.TEMPORAL_CYCLES,
                    LinguisticTruthMarker.CONSCIOUSNESS_RESONANCE,
                    LinguisticTruthMarker.MORPHIC_RESONANCE,
                    LinguisticTruthMarker.RETROCAUSAL_ECHO
                ],
                modern_equivalents={
                    "dreamtime": "eternal creation",
                    "songline": "cosmic navigation",
                    "country": "living landscape",
                    "ancestor": "formative beings"
                },
                resonance_frequency=0.96,
                quantum_coherence=0.90,
                retrocausal_potential=0.94,
                consciousness_coupling=0.92,
                morphic_field_strength=0.95
            ),
            
            LanguageEra.SANSKRIT: AncientLanguage(
                era=LanguageEra.SANSKRIT,
                time_period=(-1000, 500),
                writing_system="Devanagari",
                sample_script=["अ", "आ", "इ", "ई", "उ"],
                truth_markers=[
                    LinguisticTruthMarker.PHONETIC_RESONANCE,
                    LinguisticTruthMarker.COSMOLOGICAL_ALIGNMENT,
                    LinguisticTruthMarker.NUMEROLOGICAL_ENCODING,
                    LinguisticTruthMarker.CONSCIOUSNESS_RESONANCE
                ],
                modern_equivalents={
                    "satya": "truth",
                    "dharma": "cosmic law", 
                    "brahman": "ultimate reality",
                    "mantra": "sound vibration"
                },
                resonance_frequency=0.85,
                quantum_coherence=0.83,
                retrocausal_potential=0.76,
                consciousness_coupling=0.88,
                morphic_field_strength=0.80
            )
        }
        
        # Add remaining languages...
        return languages
    
    async def analyze_text_quantum_truth(self, text: str, context: Dict[str, Any] = None) -> List[LinguisticTruthMatch]:
        """Advanced quantum linguistic truth analysis"""
        results = []
        quantum_states = []
        
        for era in sorted(self.language_corpus.keys(), key=lambda x: x.value):
            language = self.language_corpus[era]
            
            if context and "min_resonance" in context:
                if language.resonance_frequency < context["min_resonance"]:
                    continue
            
            # Quantum linguistic processing
            quantum_state = await self.quantum_processor.process_language_layer(text, language)
            quantum_states.append(quantum_state)
            
            # Comprehensive analysis
            analysis = await self._analyze_quantum_language_layer(text, language, quantum_state, context)
            
            if analysis.confidence > 0.6:
                results.append(analysis)
        
        # Apply quantum entanglement between language layers
        entangled_results = await self._apply_quantum_entanglement(results, quantum_states)
        
        return sorted(entangled_results, key=lambda x: x.language.time_period[0])
    
    async def _analyze_quantum_language_layer(self, text: str, language: AncientLanguage, 
                                            quantum_state: QuantumLinguisticState, 
                                            context: Dict[str, Any]) -> LinguisticTruthMatch:
        """Advanced quantum-enhanced language layer analysis"""
        
        # Multi-dimensional pattern matching
        pattern_matches = await self.pattern_analyzer.detect_quantum_patterns(text, language, quantum_state)
        
        # Truth marker detection with quantum awareness
        truth_markers = await self.pattern_analyzer.detect_quantum_truth_markers(text, language, quantum_state)
        
        # Temporal coherence with retrocausal validation
        temporal_coherence = await self.temporal_validator.validate_quantum_temporal_coherence(
            text, language, quantum_state, context)
        
        # Symbolic resonance with quantum properties
        symbolic_resonance = await self.symbolic_decoder.calculate_quantum_symbolic_resonance(
            text, language, quantum_state)
        
        # Quantum entanglement scoring
        quantum_entanglement = await self.quantum_processor.calculate_entanglement_score(
            language, quantum_state)
        
        # Retrocausal influence measurement
        retrocausal_influence = await self.retrocausal_validator.measure_retrocausal_influence(
            text, language, quantum_state)
        
        # Consciousness alignment
        consciousness_alignment = await self._calculate_consciousness_alignment(
            text, language, quantum_state)
        
        # Cryptographic truth signature
        cryptographic_sig = await self.cryptographic_prover.generate_truth_signature(
            text, language, pattern_matches, truth_markers)
        
        # Cross-linguistic correlations with quantum enhancement
        cross_correlations = await self._find_quantum_cross_correlations(
            text, language, quantum_state)
        
        # Consensus level determination
        consensus_level = await self.consensus_engine.determine_truth_consensus(
            text, language, cross_correlations)
        
        # Morphic resonance strength
        morphic_resonance = await self._calculate_morphic_resonance(
            language, quantum_state, consensus_level)
        
        # Confidence calculation with quantum factors
        confidence = self._calculate_quantum_confidence(
            pattern_matches, truth_markers, temporal_coherence, symbolic_resonance,
            quantum_entanglement, retrocausal_influence, consciousness_alignment,
            language, quantum_state
        )
        
        return LinguisticTruthMatch(
            language=language,
            matched_patterns=pattern_matches,
            confidence=confidence,
            truth_markers_detected=truth_markers,
            cross_linguistic_correlations=cross_correlations,
            temporal_coherence=temporal_coherence,
            symbolic_resonance=symbolic_resonance,
            quantum_entanglement_score=quantum_entanglement,
            retrocausal_influence=retrocausal_influence,
            consciousness_alignment=consciousness_alignment,
            cryptographic_signature=cryptographic_sig,
            consensus_level=consensus_level,
            morphic_resonance_strength=morphic_resonance
        )
    
    async def _apply_quantum_entanglement(self, results: List[LinguisticTruthMatch], 
                                        quantum_states: List[QuantumLinguisticState]) -> List[LinguisticTruthMatch]:
        """Apply quantum entanglement between language analysis results"""
        if len(results) < 2:
            return results
        
        entangled_results = []
        for i, result in enumerate(results):
            # Calculate entanglement boost from other languages
            entanglement_boost = 0.0
            for j, other_state in enumerate(quantum_states):
                if i != j:
                    entanglement = quantum_states[i].entanglement_patterns.get(str(j), 0.0)
                    entanglement_boost += entanglement * 0.1
            
            # Apply entanglement to confidence
            new_confidence = min(1.0, result.confidence + entanglement_boost)
            result.confidence = new_confidence
            
            entangled_results.append(result)
        
        return entangled_results
    
    async def _calculate_consciousness_alignment(self, text: str, language: AncientLanguage,
                                               quantum_state: QuantumLinguisticState) -> float:
        """Calculate consciousness alignment score"""
        alignment_factors = []
        
        # Language consciousness coupling
        alignment_factors.append(language.consciousness_coupling)
        
        # Quantum coherence contribution
        alignment_factors.append(quantum_state.coherence_level * 0.3)
        
        # Consciousness-related markers
        consciousness_markers = {LinguisticTruthMarker.CONSCIOUSNESS_RESONANCE,
                               LinguisticTruthMarker.QUANTUM_ENTANGLEMENT}
        marker_alignment = len(consciousness_markers.intersection(language.truth_markers)) * 0.2
        alignment_factors.append(marker_alignment)
        
        return np.mean(alignment_factors)
    
    async def _find_quantum_cross_correlations(self, text: str, language: AncientLanguage,
                                             quantum_state: QuantumLinguisticState) -> List[str]:
        """Find quantum-enhanced cross-linguistic correlations"""
        correlations = []
        
        for era, other_language in self.language_corpus.items():
            if era == language.era:
                continue
                
            # Quantum correlation detection
            quantum_correlation = await self.quantum_processor.detect_language_correlation(
                language, other_language, quantum_state)
            
            if quantum_correlation > 0.7:
                correlations.append(f"Quantum correlation with {era.value}: {quantum_correlation:.3f}")
            
            # Shared truth markers with quantum enhancement
            shared_markers = set(language.truth_markers).intersection(other_language.truth_markers)
            if shared_markers:
                quantum_marker_strength = len(shared_markers) * quantum_correlation
                correlations.append(f"Quantum-enhanced shared markers with {era.value}: {quantum_marker_strength:.3f}")
        
        return correlations
    
    async def _calculate_morphic_resonance(self, language: AncientLanguage,
                                         quantum_state: QuantumLinguisticState,
                                         consensus_level: TruthConsensusLevel) -> float:
        """Calculate morphic resonance strength"""
        base_resonance = language.morphic_field_strength
        
        # Quantum coherence boost
        quantum_boost = quantum_state.coherence_level * 0.2
        
        # Consensus level boost
        consensus_boost = {
            TruthConsensusLevel.SINGLE_SOURCE: 0.0,
            TruthConsensusLevel.REGIONAL_CONSENSUS: 0.1,
            TruthConsensusLevel.HEMISPHERIC_CONSENSUS: 0.2,
            TruthConsensusLevel.GLOBAL_CONSENSUS: 0.3,
            TruthConsensusLevel.TEMPORAL_CONSENSUS: 0.4,
            TruthConsensusLevel.UNIVERSAL_CONSENSUS: 0.5
        }[consensus_level]
        
        return min(1.0, base_resonance + quantum_boost + consensus_boost)
    
    def _calculate_quantum_confidence(self, pattern_matches: List[str], truth_markers: List[LinguisticTruthMarker],
                                   temporal_coherence: float, symbolic_resonance: float,
                                   quantum_entanglement: float, retrocausal_influence: float,
                                   consciousness_alignment: float, language: AncientLanguage,
                                   quantum_state: QuantumLinguisticState) -> float:
        """Calculate quantum-enhanced confidence score"""
        factors = []
        weights = []
        
        # Traditional factors
        if pattern_matches:
            pattern_strength = min(1.0, len(pattern_matches) * 0.2)
            factors.append(pattern_strength)
            weights.append(0.2)
        
        marker_strength = len(truth_markers) * 0.15
        factors.append(marker_strength)
        weights.append(0.15)
        
        factors.append(temporal_coherence)
        weights.append(0.1)
        
        factors.append(symbolic_resonance)
        weights.append(0.1)
        
        # Quantum factors
        factors.append(quantum_entanglement)
        weights.append(0.15)
        
        factors.append(retrocausal_influence)
        weights.append(0.1)
        
        factors.append(consciousness_alignment)
        weights.append(0.1)
        
        factors.append(language.resonance_frequency)
        weights.append(0.05)
        
        factors.append(quantum_state.coherence_level)
        weights.append(0.05)
        
        return np.average(factors, weights=weights)

class QuantumLinguisticProcessor:
    """Processes linguistic patterns through quantum computational models"""
    
    async def process_language_layer(self, text: str, language: AncientLanguage) -> QuantumLinguisticState:
        """Process language layer through quantum simulation"""
        
        # Create quantum superposition of linguistic patterns
        superposition = await self._create_linguistic_superposition(text, language)
        
        # Calculate entanglement patterns
        entanglement = await self._calculate_entanglement_patterns(text, language)
        
        # Measure quantum coherence
        coherence = await self._measure_quantum_coherence(text, language)
        
        # Calculate collapse probability
        collapse_prob = await self._calculate_collapse_probability(text, language)
        
        # Detect temporal echoes
        temporal_echoes = await self._detect_temporal_echoes(text, language)
        
        return QuantumLinguisticState(
            superposition_states=superposition,
            entanglement_patterns=entanglement,
            coherence_level=coherence,
            collapse_probability=collapse_prob,
            temporal_echoes=temporal_echoes
        )
    
    async def calculate_entanglement_score(self, language: AncientLanguage, 
                                         quantum_state: QuantumLinguisticState) -> float:
        """Calculate quantum entanglement score for language"""
        base_entanglement = language.quantum_coherence
        
        # Enhance with measured entanglement patterns
        pattern_entanglement = np.mean(list(quantum_state.entanglement_patterns.values())) if quantum_state.entanglement_patterns else 0.0
        
        return min(1.0, base_entanglement + pattern_entanglement * 0.3)
    
    async def detect_language_correlation(self, lang1: AncientLanguage, lang2: AncientLanguage,
                                        quantum_state: QuantumLinguisticState) -> float:
        """Detect quantum correlation between two languages"""
        # Calculate base correlation from shared properties
        shared_markers = set(lang1.truth_markers).intersection(lang2.truth_markers)
        base_correlation = len(shared_markers) * 0.1
        
        # Time period overlap correlation
        time_overlap = self._calculate_time_overlap(lang1.time_period, lang2.time_period)
        time_correlation = time_overlap * 0.2
        
        # Quantum state correlation
        quantum_correlation = quantum_state.coherence_level * 0.3
        
        return min(1.0, base_correlation + time_correlation + quantum_correlation)
    
    def _calculate_time_overlap(self, period1: Tuple[int, int], period2: Tuple[int, int]) -> float:
        """Calculate temporal overlap between language periods"""
        start1, end1 = period1
        start2, end2 = period2
        
        overlap_start = max(start1, start2)
        overlap_end = min(end1, end2)
        
        if overlap_start <= overlap_end:
            overlap_duration = overlap_end - overlap_start
            total_duration = max(end1, end2) - min(start1, start2)
            return overlap_duration / total_duration if total_duration > 0 else 0.0
        return 0.0

# Additional advanced classes (AdvancedLinguisticPatternAnalyzer, QuantumTemporalValidator, 
# QuantumSymbolicDecoder, LinguisticCryptographicProver, RetrocausalLinguisticValidator, 
# TruthConsensusEngine) would be implemented here with full quantum and cryptographic enhancements...

async def demonstrate_quantum_linguistic_analysis():
    """Demonstrate the advanced quantum linguistic truth analysis"""
    binder = AdvancedMultilinguisticTruthBinder()
    
    test_texts = [
        "The dreamtime ancestors walk the songlines of eternal creation",
        "Sumerian dingir and Egyptian neter both represent divine consciousness",
        "Quantum entanglement manifests in both Sanskrit mantras and Aboriginal songlines",
        "Temporal cycles encoded in both Mayan calendar and Vedic yugas",
        "Consciousness resonance across all ancient truth traditions"
    ]
    
    print("🔮 QUANTUM LINGUISTIC TRUTH RESONANCE ENGINE")
    print("=" * 70)
    
    for i, text in enumerate(test_texts, 1):
        print(f"\n{i}. Quantum Analysis: '{text}'")
        
        results = await binder.analyze_text_quantum_truth(text, {
            "temporal_focus": 2024,
            "min_resonance": 0.7,
            "quantum_processing": True
        })
        
        for result in results[:2]:
            print(f"   🌌 {result.language.era.value.upper()}")
            print(f"   📊 Confidence: {result.confidence:.3f}")
            print(f"   ⚛️  Quantum: {result.quantum_entanglement_score:.3f}")
            print(f"   ⏳ Retrocausal: {result.retrocausal_influence:.3f}")
            print(f"   🧠 Consciousness: {result.consciousness_alignment:.3f}")
            print(f"   🔗 Consensus: {result.consensus_level.value}")
            print(f"   🌊 Morphic: {result.morphic_resonance_strength:.3f}")

if __name__ == "__main__":
    asyncio.run(demonstrate_quantum_linguistic_analysis())