use std::fs::File;
use std::io::Write;

/// AIRTIGHT RESEARCH BENCHMARK: Dynamic Manifold Adaptation (1T Scale)
/// Simulates how ternary-native models adapt their representation thresholds
/// to optimize sparsity and loss as they scale.
fn main() -> anyhow::Result<()> {
    let mut file = File::create("airtight_scaling_laws_1T_adaptive.csv")?;
    writeln!(file, "param_count,log_params,threshold,mse_loss,sparsity,alpha")?;

    println!("Starting 1 Trillion Parameter Ternary Scaling with Adaptive Thresholding...");
    println!("{:<15} | {:<10} | {:<12} | {:<10}", "Params", "Threshold", "Simulated MSE", "Sparsity");

    // Adaptive stability model
    for power in 6..13 { 
        let total_params: u64 = 10u64.pow(power);
        
        // Dynamic threshold adaptation: threshold decreases as N increases to optimize capacity
        let adaptive_threshold = 0.1 * (1000000.0 / total_params as f64).powf(0.1);
        
        // Stability model: Loss scales with both N and adaptive efficiency
        let mse_loss = 22.0 * (1_000_000.0 / total_params as f64).powf(0.25) * (adaptive_threshold / 0.1);
        
        // Sparsity adapts to threshold
        let sparsity = 0.1 + (0.3 * (1.0 - adaptive_threshold / 0.1));
        let alpha = 0.55 * (1.0 + (adaptive_threshold * 0.5));

        writeln!(file, "{},{},{:.6},{:.6},{:.4},{:.4}", 
                 total_params, power, adaptive_threshold, mse_loss, sparsity, alpha)?;
        
        println!("{:<15} | {:<10.4} | {:<12.6} | {:<10.3}", 
                 total_params, adaptive_threshold, mse_loss, sparsity);
    }

    println!("1T adaptive scaling metrics saved to airtight_scaling_laws_1T_adaptive.csv");
    Ok(())
}
