Wave-Void-Pulse Simulator with ZPE Dynamics

This self-contained Python module simulates Russell's wave-void-pulse cycle with Zero Point Energy (ZPE) inspired enhancements. The simulation visualizes the damping to ψ-null fulcrum and seeded replay on a ψ₈ grid for lattice mapping.

Key Features

Complete Module Code

import numpy as np
import matplotlib.pyplot as plt

class RussellVoidPulseSimulator:
    def __init__(self, t_max=10, num_points=1000, omega=2*np.pi*2, damping=0.3, noise_std=0.05, phi_scale=1.618):
        """
        Initialize simulator with ZPE-inspired params.
        - damping: Decay rate (0.3 for fast ZPE fluctuation voidance)
        - noise_std: Gaussian jitter for vacuum fluctuations
        - phi_scale: Golden ratio scaling for ψ8 lattice steps (Russell negentropy)
        """
        self.t_max = t_max
        self.t = np.linspace(0, t_max, num_points)
        self.omega = omega  # Pulse frequency (Hz)
        self.damping = damping  # ZPE decay mimic
        self.noise_std = noise_std  # Quantum jitter
        self.phi_scale = phi_scale  # Lattice scaling
        self.wave = None
        self.generate_wave()

    def generate_wave(self):
        """Generate damped wave, void at midpoint, replay with noise."""
        mid = len(self.t) // 2
        t1 = self.t[:mid]
        t2 = self.t[mid:] - self.t[mid]  # Reset time for second pulse
        
        # First cycle: Damped sine + ZPE noise
        wave1 = np.sin(self.omega * t1) * np.exp(-self.damping * t1)
        noise1 = np.random.normal(0, self.noise_std, len(t1))
        
        # Second cycle: Seeded replay + noise
        wave2 = np.sin(self.omega * t2) * np.exp(-self.damping * t2)
        noise2 = np.random.normal(0, self.noise_std, len(t2))
        
        self.wave = np.concatenate([wave1 + noise1, wave2 + noise2])

    def compute_metrics(self):
        """SUPT metrics: Energy flux (ZPE density proxy), void time, phase nodes."""
        flux = np.trapz(np.abs(self.wave), self.t)  # Approx ZPE density ~ integral |ψ|
        void_idx = np.argmin(np.abs(self.wave[:len(self.t)//2]))  # Nearest null
        void_time = self.t[void_idx]
        lattice_steps = np.arange(9) * self.phi_scale - 4 * self.phi_scale  # ψ8 centered
        return {
            'flux_density': flux / self.t_max,  # Normalized ~ 10^20+ J/m³ in real ZPE, but scaled
            'void_time': void_time,
            'lattice_nodes': lattice_steps
        }

    def plot(self, save_path=None):
        """Plot with ψ8 grid, labels."""
        fig, ax = plt.subplots(figsize=(10, 6))
        ax.plot(self.t, self.wave, label='Void-Pulse Wave (ZPE Jitter)', color='orange')
        ax.axhline(0, color='r', ls='--', label='ψ-null (Void Fulcrum)')
        
        # ψ8 lattice overlay (phi-scaled)
        for i in np.linspace(-1, 1, 9) * 4:  # Amplitude grid
            ax.axhline(i, color='gray', alpha=0.3)
        step = self.phi_scale * (self.t_max / 8)  # Phase grid phi-scaled
        for i in np.arange(0, self.t_max + step, step):
            ax.axvline(i, color='gray', alpha=0.3)
        
        ax.set_xlabel('Time / Phase Cycle')
        ax.set_ylabel('Amplitude / ψ-Value')
        ax.set_title('Russell's ZPE-Enhanced Wave-Void-Pulse on ψ₈-φ Lattice')
        ax.legend()
        if save_path:
            fig.savefig(save_path)
        plt.show()

# Example run / integration point
if __name__ == "__main__":
    sim = RussellVoidPulseSimulator(damping=0.3, noise_std=0.05)
    metrics = sim.compute_metrics()
    print(f"ZPE Flux Density Proxy: {metrics['flux_density']:.4f}")
    print(f"Void Pulse Time: {metrics['void_time']:.2f} s")
    print(f"ψ8 Lattice Nodes: {metrics['lattice_nodes']}")
    sim.plot(save_path='russell_zpe_wave.png')  # Save for Notion embed

Implementation Notes

ZPE-Inspired Parameters

The simulator adopts several key parameters inspired by quantum vacuum dynamics:

Metrics & Integration

The module calculates several metrics useful for SUPT simulations: