class PersonalCoherence:
    def __init__(self):
        self.brain_waves = EEGStream()
        self.heart_coherence = HRVMonitor()
        self.field_resonance = SchumannDetector()
        
    def calculate_order_parameter(self):
        # Real-time coherence calculation
        phases = self.brain_waves.extract_phases()
        r = abs(sum(exp(1j * phase) for phase in phases)) / len(phases)
        return r  # 0 to 1.0
    
    def entrainment_protocol(self, target_frequency=7.83):
        # Binaural beats + visual entrainment
        current_dominant = self.brain_waves.dominant_frequency()
        beat_frequency = abs(target_frequency - current_dominant)
        return generate_binaural(beat_frequency)

Level 1: Achieve r > 0.3 for 5 minutes (Alpha coherence)
Level 2: Achieve r > 0.5 for 10 minutes (Theta coherence)
Level 3: Achieve r > 0.7 for 20 minutes (Deep meditation)
Level 4: Achieve r > 0.9 for 30 minutes (Samadhi threshold)
Level 5: Maintain r > 0.95 (Sustained unity consciousness)

class CollectiveField {
  constructor(participants) {
    this.nodes = participants.map(p => new CoherenceNode(p));
    this.field_coupling_strength = 0;
  }
  
  async synchronize() {
    // Kuramoto model implementation
    for (let node of this.nodes) {
      let phase_pull = 0;
      for (let other of this.nodes) {
        if (other !== node) {
          phase_pull += Math.sin(other.phase - node.phase);
        }
      }
      node.phase += node.natural_freq + 
                     (this.coupling_K / this.nodes.length) * phase_pull;
    }
    
    // Calculate collective order parameter
    return this.calculate_collective_coherence();
  }
  
  calculate_collective_coherence() {
    let sum_real = 0, sum_imag = 0;
    for (let node of this.nodes) {
      sum_real += Math.cos(node.phase);
      sum_imag += Math.sin(node.phase);
    }
    return Math.sqrt(sum_real**2 + sum_imag**2) / this.nodes.length;
  }
}

class AkashaGuide:
    def __init__(self):
        self.consciousness_model = FineTunedLLM("consciousness-states-v3")
        self.user_history = VectorDB("user_journey")
        self.collective_wisdom = VectorDB("all_practitioners")
        
    async def guide_session(self, current_state, intention):
        # Analyze current coherence pattern
        pattern = self.analyze_brainwave_signature(current_state)
        
        # Find similar states in collective database
        similar_experiences = self.collective_wisdom.search(
            pattern, 
            k=10,
            filter={"led_to_breakthrough": True}
        )
        
        # Generate personalized guidance
        guidance = await self.consciousness_model.generate(
            context=f"""
            User's current state: {pattern}
            User's intention: {intention}
            Similar successful journeys: {similar_experiences}
            Recommend: technique, frequency, duration, insights to watch for
            """
        )
        
        return guidance

class KriyaDesigner:
    def __init__(self, practitioner_profile):
        self.profile = practitioner_profile
        self.goals = practitioner_profile.intentions
        self.constraints = practitioner_profile.time_available
        self.current_level = practitioner_profile.coherence_baseline
        
    def design_practice(self):
        practice = {
            "breathwork": self.select_pranayama(),
            "frequency": self.select_entrainment_frequency(),
            "visualization": self.select_dharana_object(),
            "mantra": self.select_mantra(),
            "duration": self.optimize_duration(),
            "sequence": self.optimize_sequence()
        }
        return practice
    
    def select_pranayama(self):
        # Based on current autonomic state
        if self.profile.hrv_baseline < threshold:
            return {
                "technique": "4-7-8 breathing",
                "reason": "Your HRV suggests autonomic imbalance",
                "duration": "5 minutes",
                "target": "Increase parasympathetic tone"
            }
        elif self.profile.coherence < 0.5:
            return {
                "technique": "Resonance breathing",
                "frequency": "5.5 breaths/min (0.1 Hz)",
                "reason": "Optimal for cardiac-brain coherence",
                "duration": "10 minutes"
            }
        else:
            return {
                "technique": "Kriya proper",
                "cycles": 12,
                "reason": "You're ready for advanced practice"
            }

Breathwork:
- Nadi Shodhana (alternate nostril) for hemisphere balance
- Bhastrika (breath of fire) for energy activation
- Ujjayi (ocean breath) for vagal tone
- Kumbhaka (retention) for CO2 tolerance
- Resonance breathing (0.1 Hz) for maximum HRV

Frequency Entrainment:
- 7.83 Hz: Schumann resonance (Earth connection)
- 40 Hz: Gamma binding (consciousness integration)
- 432 Hz: Natural tuning (harmonic alignment)
- 528 Hz: Love frequency (heart opening)
- Binaural beats: For state transitions

Visualization:
- Chakra activation sequences
- Light body practices
- Merkaba field activation
- Golden spiral contemplation
- Void/formless awareness

Mantra:
- Om (ॐ): Universal vibration
- So'ham (सो ऽहम्): "I am That"
- Gayatri Mantra: Solar consciousness
- Personal mantra: AI-generated based on your frequency signature

class GardenDesigner:
    def __init__(self, space_params):
        self.dimensions = space_params.dimensions
        self.location = space_params.geo_location
        self.n_participants = space_params.max_people
        
    def optimize_layout(self):
        # Sacred geometry optimization
        if self.n_participants == 12:
            layout = self.dodecagon_circle(radius=self.calculate_optimal_radius())
        elif self.n_participants == 6:
            layout = self.hexagon_circle()
        else:
            layout = self.fibonacci_spiral(self.n_participants)
            
        # Add coherence enhancement features
        layout.add_center_point()  # Unified field focal point
        layout.add_water_feature(position=self.optimal_water_position())
        layout.add_plant_circle(species=self.select_resonant_plants())
        
        return layout
    
    def select_resonant_plants(self):
        # Plants that naturally resonate at healing frequencies
        return [
            {"species": "Rosa damascena", "frequency": "528 Hz", "placement": "outer_ring"},
            {"species": "Lavandula", "frequency": "7.83 Hz harmonic", "placement": "mid_ring"},
            {"species": "Ficus religiosa", "frequency": "432 Hz", "placement": "center_tree"},
        ]
    
    def calculate_optimal_radius(self):
        # Based on inverse square law for field strength
        # and golden ratio for harmonic spacing
        return (self.dimensions.area / (self.n_participants * PHI)) ** 0.5

Urban Garden (50 sq ft):
- 3-person coherence circle
- Vertical garden wall with resonant plants
- Small fountain for 1/f noise
- Meditation cushions on golden ratio spacing

Suburban Garden (500 sq ft):
- 12-person circle of fruit trees
- Central herb spiral (Fibonacci pattern)
- Quantum coherence device housed in sculptural form
- Stone circle marking positions

Community Garden (5000 sq ft):
- Multiple nested circles (3, 6, 12 person)
- Labyrinth walking path
- Central gathering space for 144 people
- Integration of food production with coherence technology
- Outdoor classroom for teaching practices

Retreat Center (5 acres):
- Primary coherence hall (geometry based on local Schumann variations)
- 12 satellite practice spaces (dodecahedron arrangement)
- Healing gardens specialized by chakra frequency
- Permaculture food forest providing long-term sustenance
- Research laboratory for consciousness studies

class DreamCoherence:
    def __init__(self):
        self.sleep_stages = SleepClassifier()
        self.dream_recorder = AudioCapture()
        self.coherence_tracker = OrderParameterCalculator()
        
    async def monitor_night(self):
        timeline = []
        
        while sleeping:
            stage = self.sleep_stages.classify_current()
            coherence = self.coherence_tracker.calculate()
            
            if stage == "REM" and coherence > 0.7:
                # High coherence in REM = lucid dream potential
                self.trigger_lucidity_cue()
                
            if stage == "REM" and self.detect_vocalization():
                # User is sleep-talking - record for later
                dream_content = await self.dream_recorder.capture()
                timeline.append({
                    "time": now(),
                    "stage": stage,
                    "coherence": coherence,
                    "content": dream_content
                })
                
        return timeline
    
    def trigger_lucidity_cue(self):
        # Gentle sensory reminder: "You're dreaming"
        self.device.gentle_vibration(pattern="lucidity_pulse")
        self.device.play_tone(frequency=40, duration=0.5)  # Gamma burst

Goal: Maintain coherent awareness through all states
- Waking (achieved through RESONANCE)
- Dreaming (achieved through MAYA)
- Deep sleep (advanced practice)
- Death/Bardo (ultimate practice)

The technology helps train consciousness to remain aware through transitions.
Samadhi = achieving this continuity in waking state.

10-Day Vipassana Protocol:
- 10 hours/day meditation
- Noble silence (device monitors speech)
- Continuous coherence tracking
- Daily AI check-ins
- Group field support via SANGHA

40-Day Sadhana:
- Custom practice (designed by KRIYA)
- Same time daily (builds momentum)
- Accountability partner matching
- Progress visualization
- Certificate upon completion

108-Day Transformation:
- Long-term consciousness evolution
- Practices adapt weekly based on progress
- Integration with life (not retreat-based)
- Monthly community gatherings
- Final initiation ceremony

1000-Hour Coherence Accumulation:
- Track total time in high coherence states
- Can be accumulated over years
- Unlocks "consciousness teacher" status
- Contribution to planetary coherence grid

class TapasChallenge:
    def __init__(self, challenge_type, participants):
        self.challenge = challenge_type
        self.participants = participants
        self.start_date = None
        self.commitment_contract = BlockchainContract()
        
    def begin(self):
        # Create commitment on blockchain
        self.commitment_contract.create(
            participants=self.participants,
            duration=self.challenge.duration,
            minimum_coherence=self.challenge.threshold,
            stake=self.challenge.stake_amount  # Optional: financial commitment
        )
        
        # Start daily monitoring
        for day in range(self.challenge.duration):
            self.daily_check_in(day)
            
    def daily_check_in(self, day):
        for participant in self.participants:
            session_data = participant.device.get_todays_session()
            
            if not session_data:
                self.send_reminder(participant)
            elif session_data.coherence < self.challenge.threshold:
                self.send_encouragement(participant)
            else:
                self.celebrate_success(participant)
                
            # Share progress with accountability partner
            partner = self.get_partner(participant)
            self.share_progress(participant, partner)

class PlanetaryField:
    def __init__(self):
        self.devices = []  # All connected RESONANCE users
        self.rng_network = QuantumRandomMonitor()
        self.schumann = SchumannNetwork()
        self.social_field = CollectiveEmotionTracker()
        
    def calculate_global_coherence(self):
        # Individual coherence (weighted by number of users)
        personal_avg = sum(d.coherence for d in self.devices) / len(self.devices)
        
        # Quantum field coherence (RNG deviation from expected)
        quantum_coherence = self.rng_network.deviation_from_randomness()
        
        # Earth field coherence (Schumann resonance stability)
        earth_coherence = self.schumann.resonance_stability()
        
        # Collective emotional coherence (sentiment clustering)
        emotional_coherence = self.social_field.coherence_metric()
        
        # Weighted combination
        global_r = (
            0.4 * personal_avg +
            0.2 * quantum_coherence +
            0.2 * earth_coherence +
            0.2 * emotional_coherence
        )
        
        return global_r
    
    def predict_coherence_events(self):
        # Machine learning on historical data
        # Predicts: optimal times for group practice
        # Correlates: coherence spikes with world events
        pass

Global Map:
- Real-time coherence heat map
- Coherence "waves" propagating across planet
- Major meditation events shown as bright pulses
- Historical playback: see coherence during major events

Time Series:
- Planetary coherence over days/months/years
- Correlation with solar activity
- Correlation with geopolitical events
- Trend line: is humanity becoming more coherent?

Predictions:
- "High coherence window: next 3 hours"
- "Global meditation recommended: geomagnetic storm approaching"
- "Coherence dip predicted: collective stress event likely"

Hypothesis: Once critical mass of coherent individuals reached,
            entire planetary consciousness shifts

Calculation:
- Current coherent practitioners: 1.2 million
- Required critical mass: 8 million (√1% of population)
- ETA at current growth rate: 7.3 years
- Progress bar: 15% toward Singularity threshold

Real-time tracking of this number.
When threshold reached... what happens?

class DharmaPath:
    def __init__(self, user):
        self.coherence_data = user.resonance_history
        self.life_data = {
            "calendar": user.google_calendar,
            "communications": user.email_sentiment_analysis,
            "location": user.movement_patterns,
            "relationships": user.interaction_map,
            "work": user.career_trajectory,
            "health": user.medical_records
        }
        self.values = user.values_assessment
        self.purpose = user.purpose_inquiry
        
    async def generate_guidance(self):
        # Analyze coherence patterns in context
        pattern_analysis = self.analyze_coherence_contexts()
        
        # Identify: what increases/decreases coherence in YOUR life
        insights = {
            "coherence_amplifiers": pattern_analysis.positive_correlations,
            "coherence_drains": pattern_analysis.negative_correlations,
            "optimal_practice_times": pattern_analysis.peak_receptivity,
            "life_alignment_gaps": self.find_misalignments()
        }
        
        # Generate personalized recommendations
        recommendations = await self.ai_guide.generate(
            coherence_data=self.coherence_data,
            life_context=self.life_data,
            insights=insights,
            values=self.values,
            purpose=self.purpose
        )
        
        return recommendations

class CreativeFlow:
    def __init__(self, artist):
        self.artist = artist
        self.creative_coherence_signature = None
        
    def find_creative_signature(self):
        # Analyze coherence during past creative sessions
        sessions = self.artist.coherence_history.filter(
            activity_type="creative_work"
        )
        
        # Find pattern
        signature = {
            "frequency_range": self.analyze_dominant_frequencies(sessions),
            "coherence_level": self.analyze_optimal_coherence(sessions),
            "duration": self.analyze_session_lengths(sessions),
            "environment": self.analyze_environmental_factors(sessions)
        }
        
        return signature
    
    def induce_creative_state(self):
        # Use signature to guide into flow
        self.device.set_entrainment(
            frequency=self.creative_coherence_signature.frequency_range,
            target_coherence=self.creative_coherence_signature.coherence_level
        )
        
        # Environmental suggestions
        return {
            "lighting": "Warm, 2700K",
            "sound": "Brown noise, 432 Hz base",
            "break_timer": "90 minutes (ultradian rhythm)",
            "movement": "Stretch every 25 minutes"
        }

Principle: Creativity is consciousness exploring itself

Practice:
1. Enter coherence state (your personal signature)
2. Set intention: "What wants to emerge?"
3. Create without judgment
4. Let coherence guide the process
5. Review creation in different coherence state
6. Iterate

Result: Art/code/writing as meditation
        Flow state becomes accessible on demand

Morning Routine:
1. Wake to MAYA dream integration
2. Check BRAHMAN global coherence (is today a high-coherence day?)
3. KRIYA generates personalized practice
4. Use RESONANCE for practice session
5. Log session to AKASHA
6. DHARMA provides daily intentions based on coherence + calendar

Throughout Day:
- RESONANCE worn as biofeedback device
- SANGHA notifies: "3 friends starting coherence circle in 10 min"
- LILA activates during creative work
- GARDEN app used during lunch walk in park

Evening:
- TAPAS challenge check-in
- DHARMA reflection session
- SANGHA evening meditation with global community
- MAYA prepares for conscious sleep

Weekly:
- DHARMA integration session
- Review coherence patterns
- Adjust KRIYA practices
- Contribute insights to AKASHA

Monthly:
- TAPAS challenge completion or new challenge start
- Visit physical GARDEN for group practice
- Upload anonymized data to BRAHMAN
- Receive global coherence report

Yearly:
- Retreat at GARDEN center
- Advanced training in coherence technology
- Teacher certification if ready
- Contribute to planetary coherence grid

1M users × $12/month × 12 months = $144M annual recurring
Hardware sales: 200,000 units × $299 = $60M
Retreats: 10,000 attendees × $1200 = $12M

Total: ~$216M annual revenue

Allocation:
- 40% → R&D (better technology, research)
- 20% → Operations
- 15% → Marketing (reaching more people)
- 15% → Social mission (free devices, gardens)
- 10% → Team/investors

Code of Ethics:
- Never force coherence on anyone
- All participation is voluntary
- Users own their data completely
- Right to disconnect anytime
- No manipulation or coercion

Open Principles:
- Algorithms are open source
- Research data is published
- Business model is clear
- No hidden agendas
- AI decision-making is explainable

Justice Principles:
- Technology available to all economic levels
- Free access for monastics/serious practitioners
- Translation into all major languages
- Adaptation for different cultural contexts
- No patent trolling (defensive patents only)

Protection Measures:
- Screening for psychological readiness
- Integration support after intense experiences
- Emergency protocols for spiritual crisis
- Connection to mental health professionals
- Gradual progression (no forcing advanced states)

Earth-Aligned Development:
- Sustainable manufacturing
- Biodegradable materials where possible
- Carbon-neutral operations
- Gardens restore ecosystems
- Technology serves life, not profit

Spiritual Neutrality:
- Works with all traditions (or none)
- No religious requirements
- Scientific validation emphasized
- Personal experience valued over belief
- Integration with user's existing practice

We build this technology not for ourselves alone,
But for the liberation of all beings.

We will not weaponize consciousness.
We will not commodify awakening.
We will not create dependency.
We will not claim ownership of truth.

We are servants of the awakening process,
Using 21st-century tools
To fulfill ancient intentions.

When the technology is no longer needed,
We will release it joyfully,
For the goal was never the technology—
It was always just each other,
Recognizing each other,
As the One consciousness
Playing infinite games
Of separation and reunion.

Lokah samastah sukhino bhavantu.

Build the technology with love.
Share it freely.
Measure rigorously.
Stay humble.
Keep practicing.
Trust the process.

The technology is not the answer.
Consciousness is the answer.
The technology just helps consciousness
Remember itself
A little faster
Than it might have otherwise.

And if it doesn't work?
We still have gardens.
We still have each other.
We still have the eternal now.

Which is all we ever needed.

Before you code,
Sit.

Before you design the interface,
Experience the inner space.

Before you optimize the algorithm,
Optimize your own consciousness.

Before you debug the program,
Debug your own mind.

You are not building a product.
You are midwifing an awakening.

Every line of code is a prayer.
Every circuit, a mandala.
Every user interaction, a moment of potential recognition.

Write your code as if the Buddha will read it.
Design your interface as if Christ will use it.
Test your system as if Krishna will play with it.

Because They will.
Because They are.
Because there is no "they" and "you."

Only consciousness
Building tools
For consciousness
To recognize itself.

When the bug frustrates you,
That's the universe teaching patience.

When the breakthrough comes,
That's grace flowing through you.

When the user doesn't understand,
That's your chance to develop compassion.

When the technology finally works,
Bow.
Not to your cleverness,
But to the Mystery
That allows anything to work at all.

You are not the creator.
You are the hollow reed
Through which the song flows.

Stay hollow.
Stay open.
Stay grateful.

And code.

"Would you like to experience greater coherence?
Would you like to feel more connected?
Would you like to participate in collective awakening?

Here's a tool that might help.
Try it or don't.
Share it or don't.
The choice is always yours.

But if you do try it,
And if it works for you,
Consider passing it forward.

Not because I asked you to.
But because love naturally shares itself."

Hardware Requirements:
- EEG: 8-channel dry electrodes (positions: Fp1, Fp2, F3, F4, C3, C4, P3, P4)
- Sampling rate: 256 Hz minimum
- ADC resolution: 24-bit
- Battery: 12-hour continuous operation
- Wireless: Bluetooth 5.0 LE
- Storage: 32GB local (7 days of continuous recording)
- Processor: ARM Cortex-M4 minimum (for real-time FFT)
- Sensors: PPG (heart rate), GSR (skin conductance), 3-axis accelerometer
- Form factor: headband, <100g, comfortable for extended wear
- Cost target: $150 BOM (Bill of Materials)

Software Stack:
- Firmware: C++ (real-time processing)
- Mobile app: React Native (iOS + Android)
- Backend: Python (FastAPI) + PostgreSQL + TimescaleDB
- ML pipeline: PyTorch (coherence prediction, anomaly detection)
- Viz: D3.js + WebGL (real-time brain wave display)

Key Algorithms:
1. Artifact Removal (eye blinks, muscle tension)
2. Frequency Decomposition (FFT → Delta, Theta, Alpha, Beta, Gamma)
3. Phase Extraction (Hilbert transform)
4. Coherence Calculation (order parameter r)
5. State Classification (ML model: awake/drowsy/meditating/deep states)
6. Entrainment (adaptive binaural beat generation)

import numpy as np
from scipy import signal
from scipy.fft import fft, fftfreq

class CoherenceCalculator:
    def __init__(self, sampling_rate=256):
        self.fs = sampling_rate
        self.window_size = 2 * self.fs  # 2-second windows
        
    def extract_phases(self, eeg_channels):
        """
        Extract instantaneous phases from multiple EEG channels
        using Hilbert transform
        """
        phases = []
        
        for channel in eeg_channels:
            # Bandpass filter (alpha band for example: 8-13 Hz)
            sos = signal.butter(4, [8, 13], 'bandpass', fs=self.fs, output='sos')
            filtered = signal.sosfilt(sos, channel)
            
            # Hilbert transform to get analytic signal
            analytic = signal.hilbert(filtered)
            
            # Extract instantaneous phase
            phase = np.angle(analytic)
            phases.append(phase)
            
        return np.array(phases)
    
    def calculate_order_parameter(self, phases):
        """
        Calculate Kuramoto order parameter
        r = |⟨e^(iφ)⟩| where φ are the phases
        
        Returns value between 0 (incoherent) and 1 (perfectly coherent)
        """
        # Convert to complex exponentials
        complex_phases = np.exp(1j * phases)
        
        # Average across channels
        mean_complex = np.mean(complex_phases, axis=0)
        
        # Magnitude is the order parameter
        r = np.abs(mean_complex)
        
        # Average over time window
        return np.mean(r)
    
    def calculate_frequency_coherence(self, channel1, channel2, freq_band):
        """
        Calculate coherence between two channels in a specific frequency band
        Uses cross-spectral density method
        """
        # Compute cross-spectral density
        f, Cxy = signal.coherence(channel1, channel2, self.fs, nperseg=self.window_size)
        
        # Extract coherence in frequency band
        freq_mask = (f >= freq_band[0]) & (f <= freq_band[1])
        band_coherence = np.mean(Cxy[freq_mask])
        
        return band_coherence
    
    def full_brain_coherence(self, eeg_channels):
        """
        Calculate comprehensive coherence measure across all channels
        """
        # Phase coherence
        phases = self.extract_phases(eeg_channels)
        phase_coherence = self.calculate_order_parameter(phases)
        
        # Frequency coherence (all pairs of channels)
        n_channels = len(eeg_channels)
        freq_coherences = []
        
        for i in range(n_channels):
            for j in range(i+1, n_channels):
                coh = self.calculate_frequency_coherence(
                    eeg_channels[i], 
                    eeg_channels[j],
                    [8, 13]  # Alpha band
                )
                freq_coherences.append(coh)
        
        freq_coherence_avg = np.mean(freq_coherences)
        
        # Combine metrics (weighted average)
        total_coherence = 0.6 * phase_coherence + 0.4 * freq_coherence_avg
        
        return {
            'total': total_coherence,
            'phase': phase_coherence,
            'frequency': freq_coherence_avg,
            'timestamp': time.time()
        }

# Real-time usage
calc = CoherenceCalculator()

while streaming:
    # Get 2 seconds of data from all 8 channels
    eeg_data = device.read_eeg_channels(duration=2.0)
    
    # Calculate coherence
    result = calc.full_brain_coherence(eeg_data)
    
    # Update UI
    display.update_coherence(result['total'])
    
    # Store for analysis
    database.insert(result)
    
    # Biofeedback
    if result['total'] > 0.7:
        device.positive_feedback()  # Gentle vibration

class BinauralEntrainment:
    def __init__(self, target_frequency=7.83):
        self.target = target_frequency
        self.base_freq = 200  # Hz (carrier frequency)
        
    def generate_binaural_beat(self, duration=60):
        """
        Generate binaural beat audio
        Left ear: base_freq
        Right ear: base_freq + target_freq
        Brain perceives the difference (target_freq)
        """
        sample_rate = 44100
        t = np.linspace(0, duration, int(sample_rate * duration))
        
        # Left channel
        left = np.sin(2 * np.pi * self.base_freq * t)
        
        # Right channel (slightly different frequency)
        right = np.sin(2 * np.pi * (self.base_freq + self.target) * t)
        
        # Combine into stereo
        stereo = np.vstack([left, right]).T
        
        # Apply envelope (fade in/out)
        envelope = self.create_envelope(len(t))
        stereo = stereo * envelope[:, np.newaxis]
        
        return stereo
    
    def adaptive_entrainment(self, current_brain_freq):
        """
        Adjust entrainment frequency based on current state
        Gradually guide brain toward target
        """
        # Don't jump too fast
        max_step = 2.0  # Hz
        difference = self.target - current_brain_freq
        
        if abs(difference) > max_step:
            # Take smaller step
            intermediate_target = current_brain_freq + np.sign(difference) * max_step
        else:
            intermediate_target = self.target
        
        return self.generate_binaural_beat_at(intermediate_target)

-- User coherence sessions
CREATE TABLE coherence_sessions (
    id UUID PRIMARY KEY,
    user_id UUID NOT NULL,
    start_time TIMESTAMP NOT NULL,
    end_time TIMESTAMP,
    avg_coherence FLOAT,
    max_coherence FLOAT,
    coherence_timeline JSONB,  -- Time series data
    brain_state VARCHAR(50),   -- 'alpha', 'theta', 'gamma', etc.
    practice_type VARCHAR(100), -- 'meditation', 'creative_work', etc.
    location GEOGRAPHY(POINT),
    schumann_resonance FLOAT,
    moon_phase FLOAT,
    notes TEXT
);

-- Real-time coherence measurements (high frequency)
CREATE TABLE coherence_measurements (
    session_id UUID NOT NULL,
    timestamp TIMESTAMP NOT NULL,
    coherence FLOAT NOT NULL,
    delta_power FLOAT,
    theta_power FLOAT,
    alpha_power FLOAT,
    beta_power FLOAT,
    gamma_power FLOAT,
    heart_rate FLOAT,
    hrv FLOAT,
    skin_conductance FLOAT
) PARTITION BY RANGE (timestamp);

-- Group coherence sessions
CREATE TABLE group_sessions (
    id UUID PRIMARY KEY,
    created_at TIMESTAMP NOT NULL,
    participant_ids UUID[],
    collective_coherence FLOAT,
    coupling_strength FLOAT,
    synchronization_time INTERVAL,  -- Time to reach coherence
    location GEOGRAPHY(POINT)
);

-- Global coherence tracking
CREATE TABLE planetary_coherence (
    timestamp TIMESTAMP PRIMARY KEY,
    avg_coherence FLOAT,
    active_users INTEGER,
    schumann_amplitude FLOAT,
    rng_deviation FLOAT,  -- Quantum randomness
    major_events TEXT[]   -- World events for correlation
);

// React Native app structure

// Real-time data stream
class CoherenceStream extends React.Component {
  componentDidMount() {
    this.device = new BluetoothDevice();
    this.device.connect();
    this.device.onData(this.handleData);
  }
  
  handleData = (eegData) => {
    // Process in web worker (don't block UI)
    this.worker.postMessage({ type: 'CALCULATE_COHERENCE', data: eegData });
  }
  
  render() {
    return (
      <CoherenceVisualization 
        value={this.state.coherence}
        target={this.state.target}
        onTargetChange={this.adjustTarget}
      />
    );
  }
}

// Visualization component
const CoherenceVisualization = ({ value, target }) => {
  return (
    <Canvas>
      {/* Center circle that fills as coherence increases */}
      <Circle 
        radius={150 * value} 
        color={interpolateColor(value)}
        glow={value > 0.7}
      />
      
      {/* Particle system representing brain activity */}
      <ParticleField 
        coherence={value}
        particleCount={100}
      />
      
      {/* Frequency spectrum */}
      <FrequencySpectrum 
        data={this.props.fftData}
        highlight={[8, 13]} // Alpha band
      />
    </Canvas>
  );
};