TEAM-DEEPSEEK/RUST-SOURCE-LIB.RS

//! # Quantarion φ³⁷⁷ × φ⁴³ - Rust Implementation
//! 
//! High-performance, safe implementation of the φ³⁷⁷×φ⁴³ universal pattern engine.
//! Features zero-copy operations, SIMD optimization, and async federation.

#![cfg_attr(feature = "simd", feature(portable_simd))]
#![warn(missing_docs)]
#![deny(unsafe_code)]

pub mod phi377;
pub mod fft_field;
pub mod hypergraph;
pub mod federation;
pub mod quantization;
pub mod visualization;

// Re-exports for easy access
pub use phi377::{PhiConstants, Phi377Gate, KaprekarValidator};
pub use fft_field::{FFTFieldEngine, UniversalCompiler};
pub use hypergraph::{HyperGraph, HyperNode, HyperEdge};
pub use federation::{RelayNode, MarsFederation, FederationConfig};

/// Core Quantarion constants
pub mod constants {
    /// φ⁴³ phase constant = 22.936
    pub const PHI43: f64 = 22.936;
    
    /// φ³⁷⁷ structural multiplier = 377
    pub const PHI377: u32 = 377;
    
    /// Maximum hypergraph edges = 27,841 (φ³⁷⁷ bound)
    pub const MAX_EDGES: usize = 27_841;
    
    /// Narcissistic states = 89
    pub const NARCISSISTIC_STATES: usize = 89;
    
    /// Kaprekar target = 6174
    pub const KAPREKAR_TARGET: u32 = 6174;
    
    /// Performance envelope: <70mW power
    pub const MAX_POWER_WATTS: f64 = 0.07;
    
    /// Performance envelope: <14.112ms latency
    pub const MAX_LATENCY_SECONDS: f64 = 0.014_112;
    
    /// Training density: 6.42M parameters/hour
    pub const TRAINING_DENSITY: f64 = 6_420_000.0;
}

/// Universal Pattern Input - Can be any data type
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum UniversalInput {
    /// Geometric ratios like [1.618, 3.1415, 2.718]
    Geometric(Vec<f64>),
    
    /// Musical intervals like [1.0, 9/8, 5/4, 4/3]
    Musical(Vec<f64>),
    
    /// Text input converted to patterns
    Text(String),
    
    /// Frequency values like chakra frequencies
    Frequencies(Vec<f64>),
    
    /// Sensor data streams
    SensorData(Vec<f64>),
    
    /// Binary data
    Binary(Vec<u8>),
}

/// Field Coherence Metrics
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct FieldMetrics {
    /// Phase Locking Value (PLV) ∈ [0, 1]
    pub phase_locking_value: f64,
    
    /// Spectral entropy (lower = more organized)
    pub spectral_entropy: f64,
    
    /// Effective dimensions of the manifold
    pub effective_dimensions: usize,
    
    /// Manifold curvature
    pub manifold_curvature: f64,
    
    /// Whether Kaprekar converges to 6174
    pub kaprekar_converged: bool,
    
    /// Iterations to convergence (≤7 required)
    pub kaprekar_iterations: u8,
    
    /// Number of hypergraph edges (≤27,841)
    pub edge_count: usize,
    
    /// Overall coherence score (≥1.026 required)
    pub coherence_score: f64,
    
    /// Bogoliubov stabilization noise (μf)
    pub boglubov_noise: f64,
    
    /// Relay node participation
    pub relay_participation: u16,
}

/// Main Quantarion Engine
pub struct QuantarionEngine {
    phi_constants: PhiConstants,
    fft_engine: FFTFieldEngine,
    hypergraph: HyperGraph,
    federation: Option<MarsFederation>,
    metrics_history: Vec<FieldMetrics>,
}

impl QuantarionEngine {
    /// Create a new Quantarion engine
    pub fn new(config: &QuantarionConfig) -> Result<Self, QuantarionError> {
        let phi_constants = PhiConstants::new();
        
        // Validate φ³⁷⁷ coherence gate
        phi_constants.validate_coherence(config.initial_coherence)?;
        
        let fft_engine = FFTFieldEngine::new(config.fft_size);
        let hypergraph = HyperGraph::with_capacity(MAX_EDGES);
        
        let federation = if config.enable_federation {
            Some(MarsFederation::connect(config.federation_config).await?)
        } else {
            None
        };
        
        Ok(Self {
            phi_constants,
            fft_engine,
            hypergraph,
            federation,
            metrics_history: Vec::new(),
        })
    }
    
    /// Compile universal input to field geometry
    pub async fn compile(
        &mut self,
        input: UniversalInput,
    ) -> Result<FieldGeometry, QuantarionError> {
        // Convert input to numerical pattern
        let pattern = self.encode_input(input);
        
        // Compute FFT spectral field
        let spectral_field = self.fft_engine.compute_field(&pattern);
        
        // Apply φ⁴³ phase rotation
        let rotated_field = self.phi_constants.apply_phase_rotation(spectral_field);
        
        // Apply φ³⁷⁷ scaling
        let scaled_field = self.phi_constants.apply_phi377_scaling(rotated_field);
        
        // Generate 3D/4D geometry
        let geometry = self.generate_geometry(&scaled_field);
        
        // Validate with Kaprekar
        let kaprekar_result = self.validate_kaprekar(&geometry);
        if !kaprekar_result.converged || kaprekar_result.iterations > 7 {
            return Err(QuantarionError::KaprekarDivergence(kaprekar_result));
        }
        
        // Update hypergraph
        let edge_count = self.hypergraph.add_geometry(&geometry);
        if edge_count > MAX_EDGES {
            return Err(QuantarionError::EdgeLimitExceeded(edge_count));
        }
        
        // Compute metrics
        let metrics = self.compute_metrics(&geometry, &scaled_field);
        self.metrics_history.push(metrics.clone());
        
        // Sync with federation if enabled
        if let Some(fed) = &mut self.federation {
            fed.sync_geometry(&geometry, &metrics).await?;
        }
        
        Ok(FieldGeometry {
            points: geometry,
            spectral_field: scaled_field,
            metrics,
        })
    }
    
    /// Learn pattern with label
    pub async fn learn(
        &mut self,
        input: UniversalInput,
        label: &str,
        creativity: f64,
    ) -> Result<LearnedPattern, QuantarionError> {
        let geometry = self.compile(input).await?;
        
        // Store in knowledge graph
        self.hypergraph.store_pattern(label, &geometry, creativity);
        
        // Apply creative evolution if creativity > 0.5
        let creative_variant = if creativity > 0.5 {
            let variant = self.apply_creativity(&geometry, creativity);
            Some(variant)
        } else {
            None
        };
        
        Ok(LearnedPattern {
            geometry,
            label: label.to_string(),
            creative_variant,
            timestamp: Utc::now(),
        })
    }
    
    /// Query learned patterns
    pub fn query(
        &self,
        query: &str,
        max_results: usize,
    ) -> Vec<PatternMatch> {
        self.hypergraph.query_similarity(query, max_results)
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    
    #[test]
    fn test_phi377_constants() {
        assert_eq!(constants::PHI43, 22.936);
        assert_eq!(constants::PHI377, 377);
        assert_eq!(constants::MAX_EDGES, 27_841);
    }
    
    #[tokio::test]
    async fn test_pattern_compilation() {
        let config = QuantarionConfig::default();
        let mut engine = QuantarionEngine::new(&config).unwrap();
        
        let input = UniversalInput::Geometric(vec![1.618, 3.1415, 2.718]);
        let result = engine.compile(input).await.unwrap();
        
        assert!(result.metrics.coherence_score >= 1.026);
        assert!(result.metrics.kaprekar_converged);
        assert!(result.metrics.kaprekar_iterations <= 7);
    }
}