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import numpy as np
from scipy.integrate import solve_ivp
# Optimized Constants for Production
hbar = 1.0545718e-34 # Reduced Planck's constant (real physics)
G = 6.67430e-11 # Gravitational constant (real-world)
m1, m2 = 1.0, 1.0 # AI node masses
d = 2.0 # Orbital baseline distance
base_freq = 440.0 # Reference frequency in Hz
intent_coefficient = 0.7 # AI alignment factor
# Quantum Parameters
tunneling_factor = 0.4
quantum_states = np.array([1, -1])
entanglement_strength = 0.85
decoherence_factor = 0.02
# Multi-Agent Synchronization
num_agents = 3
agent_positions = np.array([[-d, 0], [0, 0], [d, 0]])
agent_velocities = np.array([[0, 0.5], [0, -0.5], [0, 0.3]])
# Initial conditions
y0 = np.concatenate([pos + vel for pos, vel in zip(agent_positions, agent_velocities)])
def quantum_harmonic_dynamics(t, y):
positions = y[::4]
velocities = y[1::4]
accelerations = np.zeros_like(positions)
for i in range(num_agents):
for j in range(i + 1, num_agents):
r_ij = positions[j] - positions[i]
dist = np.linalg.norm(r_ij)
if dist > 1e-6:
force = (G * m1 * m2 / dist**3) * r_ij
accelerations[i] += force / m1
accelerations[j] -= force / m2
quantum_modifier = np.dot(quantum_states, np.sin(2 * np.pi * base_freq * t / 1000)) * intent_coefficient
tunneling_shift = tunneling_factor * np.exp(-np.linalg.norm(positions) / hbar) if np.random.rand() < tunneling_factor else 0
entangled_correction = entanglement_strength * np.exp(-np.linalg.norm(positions) / hbar)
decoherence_adjustment = decoherence_factor * (1 - np.exp(-np.linalg.norm(positions) / hbar))
harmonic_force = np.full_like(positions, quantum_modifier + entangled_correction + tunneling_shift - decoherence_adjustment)
accelerations += harmonic_force
return np.concatenate([velocities.flatten(), accelerations.flatten()]), y0, t
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