Research Status: Theoretical Framework Proposing Novel Concepts - Seeking Experimental Collaboration
This repository contains conceptual models and simulations proposing quantum coherence as a biosignature framework. Parameters are empirically calibrated using NASA Mars mission data. We welcome research partnerships for experimental validation.
🌌 Overview
The Coherent Quantum Oscillator Network (CQON) model is a novel physics-based framework that explores how quantum coherence may mediate the conversion from energy to structured information - a potential process underlying life's emergence. This model provides standardized assessment criteria for evaluating planetary habitability potential across diverse environments including Mars and exoplanetary systems.
Key Insight: Our simulations suggest quantum coherence could serve as a potential biosignature framework, with operational thresholds (⟨c⟩>0.30, islands≥3, r<-0.45) enabling systematic HIGH/MEDIUM/LOW/NO classification of planetary environments.
📚 Associated Publications
Current Research (Mars & Exoplanet Focus) "Quantum Coherence as a Potential Biosignature Framework: Applications to Mars and Exoplanetary Systems"
Status: Preprint on Zenodo
Focus: Planetary habitability assessment, quantum coherence metrics, Mars-exoplanet applications
Foundational Work (Theoretical Framework) "Coherent Quantum Oscillator Network Model for Life Emergence"
Status: Published on Zenodo
Focus: Basic CQON theory, energy-information transformation, life-threshold regions
🚀 Quick Start
# Clone repository
git clone https://github.com/asoylemez/cqon-simulation.git
cd cqon-simulation
# Install dependencies
pip install -r requirements.txt
# Run comprehensive Mars-Earth comparative analysis (MAIN SCRIPT)
python Mars_and_Earth_CQON.py # Generates Figures 5, 6, 7
# Generate additional figures
python Life_Threshold_Zone_Simulation.py # Figure 1 - Life-threshold region
python 2_3_4_Figures.py # Figures 2, 3, 4
python realistic_test.py # Realistic scenario testing
📊 Model Equations
Coherence Evolution dcᵢ/dt = αR_local,i - γcᵢ + √(2T)ηᵢ(t)
Local Resonance Field R_local,i = (1/N_i) Σ cos(θ_i - θ_j)
Energy Density E_i = K₀ c_i R_local,i
🔬 Empirical Mars Mission Data Integration
The CQON model parameters are empirically grounded in direct measurements from NASA's Mars rover missions:
Parameter Physical Basis Mars Mission Data Instrument
γ (Decoherence) Radiation environment 0.64-0.70 mSv/day (100× Earth) Curiosity RAD
T (Noise) Thermal variability -80°C to +20°C daily cycles REMS, MEDA
α (Resonance) Mineral structure Magnetite→Hematite transitions heMin, PIXL, SHERLOC
K₀ (Coupling) Iron oxide density ~20-30% Fe-oxide abundance APXS, CheMin, PIXL
This empirical mapping ensures physical realism in planetary habitability assessments.
🪐 Planetary Scenarios & Assessment Results
Scenario Parameters (α,γ,T) Mean Coherence Coherence Growth Mean Islands E-S Correlation Life-Like
Early Earth 0.35, 0.07, 0.15 0.342 ± 0.043 246.8% 12.7 ± 2.2 -0.658 ± 0.12 ✅ HIGH
Past Mars 0.30, 0.09, 0.18 0.204 ± 0.050 105.6% 6.7 ± 2.1 -0.695 ± 0.15 ⚠️ LOW
Mars Microhabitat 0.28, 0.08, 0.16 0.231 ± 0.059 130.2% 7.4 ± 2.7 -0.690 ± 0.18 ⚠️ LOW
Present Mars 0.20, 0.12, 0.28 0.129 ± 0.010 28.2% 1.5 ± 0.7 -0.176 ± 0.22 ❌ NO
📈 Operational Thresholds for Planetary Assessment
The model identifies three operational thresholds within our framework for assessing life-like organization potential:
Coherence Threshold: Mean coherence > 0.30
Island Formation: ≥3 coherence islands
Energy-Information: Strong negative correlation r < -0.45
These thresholds represent model-based criteria requiring experimental validation and should be viewed as testable hypotheses rather than fundamental physical constants.
🔬 Mars-Specific Findings
Statistical Significance Analysis
Early Earth vs Past Mars: t(28) = 7.847, p < 0.0001, Cohen's d = 2.966 (Large Effect)
Early Earth vs Mars Microhabitat: t(28) = 5.688, p < 0.0001, Cohen's d = 2.150 (Large Effect)
Early Earth vs Present Mars: t(28) = 18.045, p < 0.0001, Cohen's d = 6.820 (Very Large Effect)
Planetary Assessment Classification
✅ HIGH: Early Earth - Optimal conditions for life-emergence
⚠️ LOW: Past Mars & Microhabitats - Limited organization potential
❌ NO: Present Mars - Non-habitable surface conditions
📊 Generated Figures
Core Analysis Figures
Figure 1: Life-Threshold Region in α-T Parameter Space
Figure 2: Universal Phase Map of Quantum Coherence
Figure 3: Energy-Entropy Inverse Correlation
Figure 4: Multi-Scale Resonance Hierarchy
Mars Comparative Analysis Figures (Generated by Mars_and_Earth_CQON.py)
Figure 5: Performance Metrics Across Planetary Scenarios
A) Final Coherence Distribution (Box plots)
B) Coherence Evolution Time Series
C) Coherence Island Formation
D) Energy-Entropy Correlation Distribution
Figure 6: Statistical Analysis and Organization Scoring
A) Statistical Comparison (p-values & Cohen's d)
B) Life-Like Organization Scoring
Figure 7: Spatial Coherence Patterns
Coherence maps for all four planetary scenarios
📁 Repository Structure
cqon-simulation/
├── Mars_and_Earth_CQON.py # MAIN SCRIPT: Comparative planetary analysis
├── cqon_model.py # Core CQON model class
├── Life_Threshold_Zone_Simulation.py # Parameter space exploration
├── 2_3_4_Figures.py # Visualization and figure generation
├── realistic_test.py # Realistic scenario testing
├── requirements.txt # Python dependencies
├── README.md # This file
└── figures/ # Generated figures
├── Figure_1_EN.png # Life-threshold region
├── Figure_2_EN.png # Universal phase map
├── Figure_3_EN.png # Energy-entropy correlation
├── Figure_4_EN.png # Multi-scale hierarchy
├── Figure_5_EN.png # Performance metrics comparison
├── Figure_6_EN.png # Statistical analysis
└── Figure_7_EN.png # Spatial coherence maps
🛠 Usage Examples
Main Analysis Script (Recommended)
# Run the complete Mars-Earth comparative analysis
python Mars_and_Earth_CQON.py
Programmatic Usage
from cqon_model import CQONMarsEarthComparator
# Initialize comparator for planetary analysis
comparator = CQONMarsEarthComparator(grid_size=12, dt=0.1, K0=1.0)
# Run full comparative analysis (generates Figures 5, 6, 7)
all_results, stats_df, summary_df = comparator.run_comparative_analysis(n_runs=15)
# Display statistical results
print("Statistical Significance Analysis:")
print(stats_df)
print("\nPerformance Summary:")
print(summary_df)
🎯 Model Parameters
α (Resonance Sensitivity): 0.01-1.0 [1/time] - Quantum information transfer efficiency
γ (Decoherence Rate): 0.001-0.1 [1/time] - Environmental disruption (radiation, thermal)
K₀ (Coupling Strength): 0.1-2.0 [energy units] - Fundamental interaction energy scale
T (Noise Intensity): 0.01-0.5 [dimensionless] - Thermal and environmental noise
🔬 Scientific Significance
Key Advancements
First Physics-Based Framework for planetary habitability assessment using quantum coherence metrics
Mars Habitability Assessment quantitatively distinguishing different Martian environments
Standardized Assessment Framework applicable to both Mars and exoplanetary systems
Statistical Validation with large effect sizes confirming model discriminative power
Empirical Grounding in direct Mars mission measurements from Curiosity and Perseverance rovers
Astrobiological Implications
Quantum Coherence Sustainability Criteria: Physics-based complement to traditional circumstellar habitable zones
Mars Exploration Targeting: Identifies specific locations for coherence signature detection
Systematic Life Detection Framework: Physics-based approach beyond chemical biosignatures
Classification System
HIGH: All 3 criteria satisfied (Early Earth, Optimal Quantum, Ocean Depth)
LOW: 2/3 criteria satisfied (Past Mars, Mars Microhabitat, Critical Threshold)
NO: No criteria satisfied (Present Mars)
Note: Classification based on model-based operational thresholds requiring experimental validation.
⚠️ Important Notes
Model-Based Nature: The proposed thresholds (⟨c⟩>0.30, islands≥3, r<-0.45) are operational criteria within our simulation framework
Experimental Validation Required: These thresholds represent testable hypotheses that require laboratory and planetary validation
Comparative Framework: The classification system enables systematic comparison across planetary environments
Empirical Foundation: Model parameters are calibrated using actual Mars mission data for physical realism
📞 Contact
Akın Söylemez
Email: [email protected]
GitHub: @asoylemez
📜 License
This project is licensed under the MIT License - see the repository for details.
Citation: If you use this code in your research, please cite the associated publication.
Data Availability: All simulation data, statistical results, and analysis scripts are available in this repository.
Main Script: Mars_and_Earth_CQON.py contains the complete comparative analysis workflow.
This research represents an ongoing investigation into quantum coherence as a potential framework for understanding life's emergence across planetary environments. All findings should be interpreted as model-based insights requiring further experimental validation.