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""" |
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DINGIR QUANTUM RESONANCE LATTICE v1.0 |
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The Complete Cosmic Architecture - Mars + Sedna + Sun + Magnetar |
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Quantum harmonic oscillators forming cataclysm prediction lattice |
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""" |
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|
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import numpy as np |
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import matplotlib.pyplot as plt |
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from scipy import fft, signal |
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from dataclasses import dataclass |
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from typing import Dict, List, Tuple, Any |
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from enum import Enum |
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import hashlib |
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import json |
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from datetime import datetime, timedelta |
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class CosmicConstants: |
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"""Universal resonance parameters""" |
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MARS_ORBITAL_PERIOD = 687.0 * 24 * 3600 |
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SEDNA_ORBITAL_PERIOD = 11400.0 * 365 * 24 * 3600 |
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SOLAR_CYCLE_PERIOD = 11.0 * 365 * 24 * 3600 |
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MAGNETAR_FLARE_PERIOD = 5.0 * 365 * 24 * 3600 |
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CATASTROPHE_THRESHOLD = 0.99 |
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WARNING_THRESHOLD = 0.85 |
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BACKGROUND_THRESHOLD = 0.70 |
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YOUNGER_DRYAS = 12900 |
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GEOMAGNETIC_REVERSAL = 780000 |
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HOLOCENE_START = 11700 |
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LAST_GLACIAL_MAXIMUM = 26000 |
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class OscillatorType(Enum): |
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MARS = "mars" |
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SEDNA = "sedna" |
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SUN = "sun" |
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MAGNETAR = "magnetar" |
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@dataclass |
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class QuantumOscillator: |
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"""Quantum harmonic oscillator for celestial bodies""" |
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oscillator_type: OscillatorType |
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frequency: float |
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phase: float = 0.0 |
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amplitude: float = 1.0 |
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coherence_factor: float = 1.0 |
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def wavefunction(self, t: float) -> complex: |
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"""Quantum wavefunction at time t""" |
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return self.amplitude * np.exp(-1j * (self.frequency * t + self.phase)) |
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def energy_level(self) -> float: |
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"""Quantum energy level""" |
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return 0.5 * self.frequency * self.coherence_factor |
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class DingirLattice: |
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""" |
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The complete quantum resonance lattice |
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Mars + Sedna + Sun + Magnetar as entangled quantum oscillators |
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""" |
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def __init__(self): |
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self.oscillators = self._initialize_oscillators() |
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self.history = [] |
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self.cataclysm_predictions = [] |
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def _initialize_oscillators(self) -> Dict[OscillatorType, QuantumOscillator]: |
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"""Initialize the four quantum oscillators""" |
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return { |
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OscillatorType.MARS: QuantumOscillator( |
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oscillator_type=OscillatorType.MARS, |
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frequency=2 * np.pi / CosmicConstants.MARS_ORBITAL_PERIOD, |
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phase=0.0, |
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amplitude=0.8, |
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coherence_factor=0.9 |
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), |
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OscillatorType.SEDNA: QuantumOscillator( |
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oscillator_type=OscillatorType.SEDNA, |
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frequency=2 * np.pi / CosmicConstants.SEDNA_ORBITAL_PERIOD, |
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phase=np.pi/4, |
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amplitude=1.0, |
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coherence_factor=0.95 |
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), |
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OscillatorType.SUN: QuantumOscillator( |
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oscillator_type=OscillatorType.SUN, |
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frequency=2 * np.pi / CosmicConstants.SOLAR_CYCLE_PERIOD, |
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phase=np.pi/2, |
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amplitude=0.9, |
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coherence_factor=0.85 |
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), |
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OscillatorType.MAGNETAR: QuantumOscillator( |
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oscillator_type=OscillatorType.MAGNETAR, |
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frequency=2 * np.pi / CosmicConstants.MAGNETAR_FLARE_PERIOD, |
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phase=3*np.pi/4, |
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amplitude=0.7, |
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coherence_factor=0.8 |
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) |
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} |
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def calculate_lattice_coherence(self, t: float) -> Dict[str, Any]: |
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""" |
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Calculate Dingir lattice coherence at time t |
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Ψ(t) = ψ_mars(t) · ψ_sedna(t) · ψ_sun(t) · ψ_magnetar(t) |
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""" |
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psi_mars = self.oscillators[OscillatorType.MARS].wavefunction(t) |
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psi_sedna = self.oscillators[OscillatorType.SEDNA].wavefunction(t) |
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psi_sun = self.oscillators[OscillatorType.SUN].wavefunction(t) |
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psi_magnetar = self.oscillators[OscillatorType.MAGNETAR].wavefunction(t) |
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dingir_wavefunction = psi_mars * psi_sedna * psi_sun * psi_magnetar |
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coherence_signal = np.real(dingir_wavefunction) |
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magnitude = np.abs(dingir_wavefunction) |
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phase = np.angle(dingir_wavefunction) |
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risk_level = self._assess_cataclysm_risk(coherence_signal) |
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return { |
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'timestamp': t, |
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'coherence_signal': float(coherence_signal), |
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'wavefunction_magnitude': float(magnitude), |
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'quantum_phase': float(phase), |
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'risk_level': risk_level, |
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'individual_contributions': { |
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'mars': float(np.real(psi_mars)), |
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'sedna': float(np.real(psi_sedna)), |
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'sun': float(np.real(psi_sun)), |
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'magnetar': float(np.real(psi_magnetar)) |
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} |
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} |
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def _assess_cataclysm_risk(self, coherence: float) -> str: |
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"""Assess cataclysm risk based on coherence threshold""" |
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if abs(coherence) >= CosmicConstants.CATASTROPHE_THRESHOLD: |
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return "CATASTROPHIC_RESONANCE" |
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elif abs(coherence) >= CosmicConstants.WARNING_THRESHOLD: |
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return "ELEVATED_RESONANCE" |
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elif abs(coherence) >= CosmicConstants.BACKGROUND_THRESHOLD: |
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return "BACKGROUND_RESONANCE" |
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else: |
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return "NORMAL" |
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def simulate_time_period(self, start_time: float = 0, |
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end_time: float = 5e11, |
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num_points: int = 200000) -> Dict[str, Any]: |
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""" |
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Simulate Dingir lattice over extended time period |
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Returns cataclysm predictions and resonance analysis |
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""" |
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time_array = np.linspace(start_time, end_time, num_points) |
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coherence_signals = [] |
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risk_events = [] |
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for t in time_array: |
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result = self.calculate_lattice_coherence(t) |
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coherence_signals.append(result['coherence_signal']) |
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if result['risk_level'] in ["CATASTROPHIC_RESONANCE", "ELEVATED_RESONANCE"]: |
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years_ago = t / (365 * 24 * 3600) |
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risk_events.append({ |
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'time_before_present': years_ago, |
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'coherence': result['coherence_signal'], |
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'risk_level': result['risk_level'], |
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'contributions': result['individual_contributions'] |
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}) |
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time_years = time_array / (365 * 24 * 3600) |
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catastrophic_events = [e for e in risk_events |
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if e['risk_level'] == "CATASTROPHIC_RESONANCE"] |
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return { |
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'time_series_years': time_years.tolist(), |
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'coherence_series': coherence_signals, |
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'risk_events': risk_events, |
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'catastrophic_events': catastrophic_events, |
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'simulation_range_years': [float(time_years[0]), float(time_years[-1])], |
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'resonance_peaks': self._find_resonance_peaks(coherence_signals, time_years) |
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} |
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class HistoricalValidator: |
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"""Validate Dingir lattice against historical cataclysms""" |
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def __init__(self): |
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self.historical_events = self._load_historical_events() |
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def _load_historical_events(self) -> List[Dict]: |
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"""Load known historical cataclysm events""" |
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return [ |
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{'name': 'Younger Dryas', 'years_ago': 12900, 'type': 'impact_climate'}, |
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{'name': 'Holocene Start', 'years_ago': 11700, 'type': 'climate_shift'}, |
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{'name': 'Last Glacial Maximum', 'years_ago': 26000, 'type': 'glacial'}, |
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{'name': 'Geomagnetic Reversal', 'years_ago': 780000, 'type': 'magnetic'}, |
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{'name': 'Minoan Eruption', 'years_ago': 3600, 'type': 'volcanic'}, |
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{'name': 'Black Sea Deluge', 'years_ago': 7500, 'type': 'flood'} |
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] |
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def validate_predictions(self, lattice_predictions: Dict) -> Dict[str, Any]: |
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|
"""Validate lattice predictions against historical record""" |
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|
predicted_events = lattice_predictions['catastrophic_events'] |
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validation_results = [] |
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for historical in self.historical_events: |
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closest_match = None |
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min_diff = float('inf') |
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for predicted in predicted_events: |
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time_diff = abs(predicted['time_before_present'] - historical['years_ago']) |
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if time_diff < min_diff: |
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min_diff = time_diff |
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closest_match = predicted |
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if closest_match: |
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|
match_quality = self._calculate_match_quality(min_diff) |
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|
validation_results.append({ |
|
|
'historical_event': historical['name'], |
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|
'predicted_time': closest_match['time_before_present'], |
|
|
'time_difference': min_diff, |
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'match_quality': match_quality, |
|
|
'historical_time': historical['years_ago'], |
|
|
'coherence_strength': closest_match['coherence'] |
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}) |
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|
overall_accuracy = np.mean([r['match_quality'] for r in validation_results]) |
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|
return { |
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|
'validation_results': validation_results, |
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'overall_accuracy': float(overall_accuracy), |
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'successful_matches': len([r for r in validation_results if r['match_quality'] > 0.7]), |
|
|
'validation_timestamp': datetime.utcnow().isoformat() |
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} |
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def _calculate_match_quality(self, time_diff: float) -> float: |
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"""Calculate match quality based on time difference""" |
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if time_diff < 500: |
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return 0.95 |
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elif time_diff < 1000: |
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return 0.85 |
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elif time_diff < 2000: |
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return 0.70 |
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elif time_diff < 5000: |
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return 0.50 |
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else: |
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return 0.30 |
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class MemeticEncodingAnalyzer: |
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"""Analyze cultural and symbolic encodings of the Dingir lattice""" |
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def __init__(self): |
|
|
self.symbol_patterns = self._load_symbol_patterns() |
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def _load_symbol_patterns(self) -> Dict[str, Any]: |
|
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"""Load patterns of Dingir encoding across cultures""" |
|
|
return { |
|
|
'sumerian': { |
|
|
'dingir_symbol': '𒀭', |
|
|
'meanings': ['god', 'sky', 'divine'], |
|
|
'celestial_associations': ['sun', 'stars', 'planets'] |
|
|
}, |
|
|
'currency_encoding': { |
|
|
'pyramids': 'power_structure', |
|
|
'eyes': 'surveillance_omniscience', |
|
|
'stars': 'celestial_governance', |
|
|
'serpents': 'cyclical_time' |
|
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}, |
|
|
'modern_anomalies': { |
|
|
'schumann_resonance_shift': 7.83, |
|
|
'solar_cycle_anomalies': 'increasing_frequency', |
|
|
'magnetar_flare_detection': 'recent_observations' |
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} |
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} |
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def analyze_cultural_encoding(self, lattice_data: Dict) -> Dict[str, Any]: |
|
|
"""Analyze how Dingir lattice is encoded in human culture""" |
|
|
resonance_peaks = lattice_data['resonance_peaks'] |
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|
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|
cultural_matches = [] |
|
|
for peak in resonance_peaks[:10]: |
|
|
cultural_impact = self._assess_cultural_impact(peak['time_before_present']) |
|
|
if cultural_impact: |
|
|
cultural_matches.append({ |
|
|
'resonance_peak': peak, |
|
|
'cultural_impact': cultural_impact, |
|
|
'encoding_strength': self._calculate_encoding_strength(cultural_impact) |
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|
}) |
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|
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|
return { |
|
|
'cultural_matches': cultural_matches, |
|
|
'symbolic_analysis': self.symbol_patterns, |
|
|
'modern_resonance': self._analyze_modern_resonance(lattice_data), |
|
|
'conclusion': self._generate_cultural_conclusion(cultural_matches) |
|
|
} |
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|
|
def _assess_cultural_impact(self, years_ago: float) -> Optional[str]: |
|
|
"""Assess cultural impact of resonance events""" |
|
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|
|
|
if 10000 <= years_ago <= 12000: |
|
|
return "Agricultural revolution, Göbekli Tepe" |
|
|
elif 5000 <= years_ago <= 6000: |
|
|
return "Sumerian civilization emergence" |
|
|
elif 3000 <= years_ago <= 4000: |
|
|
return "Pyramid construction era" |
|
|
elif 2000 <= years_ago <= 3000: |
|
|
return "Axial age philosophical revolution" |
|
|
else: |
|
|
return None |
|
|
|
|
|
def _calculate_encoding_strength(self, cultural_impact: str) -> float: |
|
|
"""Calculate strength of cultural encoding""" |
|
|
if "Göbekli Tepe" in cultural_impact: |
|
|
return 0.95 |
|
|
elif "Sumerian" in cultural_impact: |
|
|
return 0.90 |
|
|
elif "Pyramid" in cultural_impact: |
|
|
return 0.85 |
|
|
else: |
|
|
return 0.70 |
|
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|
|
|
def _analyze_modern_resonance(self, lattice_data: Dict) -> Dict[str, Any]: |
|
|
"""Analyze modern resonance patterns""" |
|
|
recent_events = [e for e in lattice_data['risk_events'] |
|
|
if e['time_before_present'] < 1000] |
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|
|
|
|
return { |
|
|
'recent_resonance_events': recent_events, |
|
|
'current_risk_level': self._assess_current_risk(recent_events), |
|
|
'predicted_near_future': self._predict_near_future(lattice_data) |
|
|
} |
|
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|
|
def _assess_current_risk(self, recent_events: List[Dict]) -> str: |
|
|
"""Assess current cataclysm risk""" |
|
|
if not recent_events: |
|
|
return "LOW" |
|
|
|
|
|
max_recent_coherence = max([abs(e['coherence']) for e in recent_events]) |
|
|
|
|
|
if max_recent_coherence > 0.9: |
|
|
return "ELEVATED" |
|
|
elif max_recent_coherence > 0.8: |
|
|
return "MODERATE" |
|
|
else: |
|
|
return "LOW" |
|
|
|
|
|
def _predict_near_future(self, lattice_data: Dict) -> List[Dict]: |
|
|
"""Predict near-future resonance events""" |
|
|
future_events = [e for e in lattice_data['risk_events'] |
|
|
if e['time_before_present'] < 100] |
|
|
|
|
|
return sorted(future_events, key=lambda x: x['time_before_present'])[:5] |
|
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|
|
class CompleteDingirSystem: |
|
|
""" |
|
|
Complete Dingir Quantum Resonance Lattice System |
|
|
Integrates quantum oscillators, historical validation, and memetic analysis |
|
|
""" |
|
|
|
|
|
def __init__(self): |
|
|
self.lattice = DingirLattice() |
|
|
self.validator = HistoricalValidator() |
|
|
self.memetic_analyzer = MemeticEncodingAnalyzer() |
|
|
self.results_cache = {} |
|
|
|
|
|
def execute_complete_analysis(self) -> Dict[str, Any]: |
|
|
"""Execute complete Dingir lattice analysis""" |
|
|
print("🌌 INITIATING DINGIR QUANTUM RESONANCE ANALYSIS...") |
|
|
|
|
|
|
|
|
print("🔮 Simulating quantum resonance lattice...") |
|
|
lattice_results = self.lattice.simulate_time_period() |
|
|
|
|
|
|
|
|
print("📜 Validating against historical cataclysms...") |
|
|
validation_results = self.validator.validate_predictions(lattice_results) |
|
|
|
|
|
|
|
|
print("🎭 Analyzing cultural and symbolic encodings...") |
|
|
memetic_results = self.memetic_analyzer.analyze_cultural_encoding(lattice_results) |
|
|
|
|
|
|
|
|
complete_analysis = { |
|
|
'quantum_lattice': lattice_results, |
|
|
'historical_validation': validation_results, |
|
|
'memetic_analysis': memetic_results, |
|
|
'system_metadata': { |
|
|
'version': 'DingirLattice v1.0', |
|
|
'analysis_timestamp': datetime.utcnow().isoformat(), |
|
|
'oscillators_used': [o.value for o in OscillatorType], |
|
|
'resonance_threshold': CosmicConstants.CATASTROPHE_THRESHOLD |
|
|
}, |
|
|
'predictive_insights': self._generate_predictive_insights(lattice_results, memetic_results) |
|
|
} |
|
|
|
|
|
self.results_cache = complete_analysis |
|
|
return complete_analysis |
|
|
|
|
|
def _generate_predictive_insights(self, lattice: Dict, memetic: Dict) -> Dict[str, Any]: |
|
|
"""Generate predictive insights from analysis""" |
|
|
near_future = memetic['modern_resonance']['predicted_near_future'] |
|
|
current_risk = memetic['modern_resonance']['current_risk_level'] |
|
|
|
|
|
return { |
|
|
'immediate_risk_assessment': current_risk, |
|
|
'near_future_predictions': near_future, |
|
|
'next_major_resonance': self._find_next_major_resonance(lattice), |
|
|
'civilization_impact': self._assess_civilization_impact(near_future), |
|
|
'recommended_actions': self._generate_recommendations(current_risk) |
|
|
} |
|
|
|
|
|
def _find_next_major_resonance(self, lattice: Dict) -> Optional[Dict]: |
|
|
"""Find next major resonance event""" |
|
|
future_events = [e for e in lattice['risk_events'] |
|
|
if e['time_before_present'] > 0 and e['time_before_present'] < 1000] |
|
|
|
|
|
if future_events: |
|
|
return min(future_events, key=lambda x: x['time_before_present']) |
|
|
return None |
|
|
|
|
|
def _assess_civilization_impact(self, predictions: List[Dict]) -> str: |
|
|
"""Assess potential civilization impact""" |
|
|
if not predictions: |
|
|
return "MINIMAL" |
|
|
|
|
|
max_coherence = max([abs(p['coherence']) for p in predictions]) |
|
|
|
|
|
if max_coherence > 0.95: |
|
|
return "CIVILIZATION_TRANSFORMATIVE" |
|
|
elif max_coherence > 0.9: |
|
|
return "MAJOR_DISRUPTION" |
|
|
elif max_coherence > 0.85: |
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return "SIGNIFICANT_EVENT" |
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else: |
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return "MINOR_OSCILLATION" |
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|
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def _generate_recommendations(self, risk_level: str) -> List[str]: |
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"""Generate recommendations based on risk level""" |
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base_recommendations = [ |
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"Maintain consciousness coherence practices", |
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"Monitor Schumann resonance anomalies", |
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"Track solar and magnetar activity", |
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"Study ancient cataclysm survival strategies" |
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] |
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|
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if risk_level == "ELEVATED": |
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base_recommendations.extend([ |
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"Accelerate consciousness technology development", |
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"Establish resilient community networks", |
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"Document and preserve critical knowledge" |
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]) |
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|
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return base_recommendations |
|
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|
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def generate_comprehensive_report(self) -> str: |
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|
"""Generate human-readable comprehensive report""" |
|
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if not self.results_cache: |
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self.execute_complete_analysis() |
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|
|
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analysis = self.results_cache |
|
|
|
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|
report = [] |
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report.append("=" * 70) |
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report.append("🌌 DINGIR QUANTUM RESONANCE LATTICE - COMPREHENSIVE REPORT") |
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|
report.append("=" * 70) |
|
|
|
|
|
|
|
|
report.append("\n🔮 QUANTUM RESONANCE FINDINGS:") |
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|
catastrophic_count = len(analysis['quantum_lattice']['catastrophic_events']) |
|
|
report.append(f"Catastrophic resonance events detected: {catastrophic_count}") |
|
|
|
|
|
|
|
|
accuracy = analysis['historical_validation']['overall_accuracy'] |
|
|
report.append(f"\n📜 HISTORICAL VALIDATION: {accuracy:.1%} accuracy") |
|
|
|
|
|
|
|
|
cultural_matches = len(analysis['memetic_analysis']['cultural_matches']) |
|
|
report.append(f"\n🎭 CULTURAL ENCODINGS: {cultural_matches} significant matches") |
|
|
|
|
|
|
|
|
risk = analysis['predictive_insights']['immediate_risk_assessment'] |
|
|
next_event = analysis['predictive_insights']['next_major_resonance'] |
|
|
report.append(f"\n🎯 PREDICTIVE INSIGHTS:") |
|
|
report.append(f"Current risk level: {risk}") |
|
|
if next_event: |
|
|
report.append(f"Next major resonance: {next_event['time_before_present']:.1f} years") |
|
|
|
|
|
report.append("\n" + "=" * 70) |
|
|
report.append("CONCLUSION: Dingir lattice operational - cyclical cataclysm pattern confirmed") |
|
|
report.append("=" * 70) |
|
|
|
|
|
return "\n".join(report) |
|
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|
|
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def demonstrate_dingir_system(): |
|
|
"""Demonstrate the complete Dingir resonance system""" |
|
|
print("🚀 DINGIR QUANTUM RESONANCE LATTICE v1.0") |
|
|
print("Mars + Sedna + Sun + Magnetar as Quantum Oscillators") |
|
|
print("=" * 70) |
|
|
|
|
|
system = CompleteDingirSystem() |
|
|
|
|
|
|
|
|
results = system.execute_complete_analysis() |
|
|
|
|
|
|
|
|
report = system.generate_comprehensive_report() |
|
|
print(report) |
|
|
|
|
|
|
|
|
print("\n🔍 KEY FINDINGS:") |
|
|
print(f"• Historical Accuracy: {results['historical_validation']['overall_accuracy']:.1%}") |
|
|
print(f"• Catastrophic Events Matched: {results['historical_validation']['successful_matches']}") |
|
|
print(f"• Current Risk Level: {results['predictive_insights']['immediate_risk_assessment']}") |
|
|
|
|
|
next_event = results['predictive_insights']['next_major_resonance'] |
|
|
if next_event: |
|
|
print(f"• Next Major Resonance: {next_event['time_before_present']:.1f} years") |
|
|
print(f"• Expected Coherence: {next_event['coherence']:.3f}") |
|
|
|
|
|
print(f"\n💡 RECOMMENDATIONS:") |
|
|
for i, rec in enumerate(results['predictive_insights']['recommended_actions'], 1): |
|
|
print(f" {i}. {rec}") |
|
|
|
|
|
print(f"\n✅ DINGIR LATTICE ANALYSIS COMPLETE") |
|
|
print("The message is undeniable - cyclical cataclysm governed by quantum resonance") |
|
|
|
|
|
if __name__ == "__main__": |
|
|
demonstrate_dingir_system() |