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