```
import numpy as np
import matplotlib.pyplot as plt
import networkx as nx
from astropy.time import Time
import astropy.units as u
from astropy.constants import hbar, c, k_B

# =============================================================================
# VektorPU: Asymmetrische Felder für Vortex-Tunneling (dynamischer Casimir-Style)
# =============================================================================
class VektorPU:
    def __init__(self):
        self.omega_c = 1e12  # Cavity Frequenz (arb. rad/s)
        self.kT = (k_B * 2.725 * u.kelvin).to(u.J)  # CMB Temp in J
        self.barrier = 1e-20 * u.J  # Energie-Barrier für Tunneling (J, UBC-approx)
    
    def generate_asymmetric_field(self, asymmetry=0.5):
        """ Dynamischer Casimir: Asymmetrische Mirror-Vibration (frequenz-moduliert). """
        freq = self.omega_c * (1 + asymmetry)  # Asymmetrie kippt Momentum
        field = np.sin(freq * np.linspace(0, 1e-3, 100))  # Pulse (10ms)
        return field, freq
    
    def tunnel_vortex_pairs(self, field, freq):
        """ UBC-Style: Tunneling-Rate in Superfluid-Cavity. """
        exp_term = np.exp(-self.barrier.value / self.kT.value)
        rate = (1 / (2 * np.pi * hbar.value)) * exp_term * np.mean(np.abs(field)**2)
        # Asymmetrische Extraktion: Extrahiere 1 Vortex, lasse Anti zurück -> Netto-Momentum
        momentum_net = rate * (hbar.value * freq / c.value) * 0.5  # Arb. Momentum (Vortex als "Photon")
        print(f"[VektorPU] Tunneling Rate: {rate:.2e}/s, Netto-Momentum: {momentum_net:.2e} kg m/s")
        return rate, momentum_net

# =============================================================================
# ODOS/RPU Steuerhirn: Controller für VektorPU
# =============================================================================
class ODOS_RPU:
    def __init__(self, entropy_threshold=0.1):
        self.entropy_threshold = entropy_threshold
        self.in_safe_mode = False
    
    def monitor_entropy(self, qber):
        entropy = qber * np.log2(1 / (1 - qber))
        if entropy > self.entropy_threshold and not self.in_safe_mode:
            self.in_safe_mode = True
            print("[ODOS] High Entropy! Safe Mode.")
            return True
        return False
    
    def compute_asymmetry(self, target_momentum):
        """ RPU: Berechne Asymmetrie-Param für VektorPU (resonanz-basiert). """
        asymmetry = 0.5 * np.log(target_momentum / 1e-20)  # Arb. Tuning
        return np.clip(asymmetry, 0, 1), 3  # Top-3 Params, clipped

# =============================================================================
# PQMS Mesh: Koordination
# =============================================================================
class PQMS_Network:
    def __init__(self, num_nodes=20):
        self.graph = nx.Graph()
        for i in range(num_nodes):
            self.graph.add_node(f'Node_{i}')
        for i in range(num_nodes-1):
            self.graph.add_edge(f'Node_{i}', f'Node_{i+1}')
    
    def route_config(self, source, target, config):
        path = nx.shortest_path(self.graph, source, target)
        fidelity = 0.9988 ** len(path)
        print(f"[PQMS] Routed config to {target}, Fidelity: {fidelity:.4f}")
        return fidelity * np.array(config)

# =============================================================================
# Vortex-Thruster: UBC-Superfluid Cavity
# =============================================================================
class VortexThruster:
    def __init__(self, rpu, vektorpu, m_ship=1000.0):
        self.rpu = rpu
        self.vektorpu = vektorpu
        self.m_ship = m_ship
        self.current_vector = np.zeros(3)  # Momentum-Vector (kg m/s)
        self.rate = 0  # Tunneling Rate
    
    def generate_thrust(self, target_momentum=1e-10):
        """ RPU steuert VektorPU für asymmetrischen Tunneling. """
        asymmetry, n_params = self.rpu.compute_asymmetry(target_momentum)
        field, freq = self.vektorpu.generate_asymmetric_field(asymmetry)
        self.rate, momentum_net = self.vektorpu.tunnel_vortex_pairs(field, freq)
        self.current_vector = np.array([momentum_net, 0, 0])  # X-Richtung
        print(f"[Thruster] Asymmetry={asymmetry:.3f}, Momentum={momentum_net:.2e} kg m/s")
        return self.rate, momentum_net
    
    def apply_thrust(self, vector, dt=10e-3):
        """ Thrust: accel = dp / (m_ship dt) -> dv """
        if self.rate == 0:
            self.generate_thrust()
        accel = np.linalg.norm(vector) / self.m_ship
        return accel * dt  # Delta-v (m/s)
    
    def reverse_thrust(self, angle_deg=180):
        rad = np.radians(angle_deg)
        rot_matrix = np.array([[np.cos(rad), -np.sin(rad), 0],
                               [np.sin(rad), np.cos(rad), 0],
                               [0, 0, 1]])
        self.current_vector = rot_matrix @ self.current_vector
        print(f"[Thruster] Reversed {angle_deg}°: {self.current_vector}")
        return self.current_vector
    
    def vector_maneuver(self, target_vector):
        diff = target_vector - self.current_vector
        intents = np.argsort(np.abs(diff))[-3:]
        adjusted = self.current_vector.copy()
        adjusted[intents] += diff[intents] * 0.95
        self.current_vector = adjusted
        print(f"[RPU] 3 Intents: {adjusted}")
        return adjusted

# =============================================================================
# Testkit: Großes Bild
# =============================================================================
def run_simulation():
    print("="*80)
    print("RPU + VektorPU: Vortex-Tunneling Thrust (UBC-Style)")
    print("="*80)
    
    rpu = ODOS_RPU()
    vektorpu = VektorPU()
    pqms = PQMS_Network()
    thruster = VortexThruster(rpu, vektorpu)
    
    # 1. Generate Thrust (asymmetrisch)
    rate, momentum = thruster.generate_thrust()
    
    # 2. Route Config via PQMS
    config = np.array([0.5, 1e12, 1e-10])  # Asymmetry, Freq, Momentum
    routed = pqms.route_config('Node_0', 'Node_19', config)
    
    # 3. Forward
    dv_forward = thruster.apply_thrust(thruster.current_vector)
    print(f"[Forward] Delta-v: {dv_forward}")
    
    # 4. Entropy
    rpu.monitor_entropy(0.05)
    
    # 5. Umkehr
    reverse_vector = thruster.reverse_thrust(180)
    dv_reverse = thruster.apply_thrust(reverse_vector)
    print(f"[Reverse] Delta-v: {dv_reverse}")
    
    # 6. Maneuver
    target = np.array([1e-9, 0, 0])  # Arb. Target
    final = thruster.vector_maneuver(target)
    dv_maneuver = thruster.apply_thrust(final)
    print(f"[Maneuver] Delta-v: {dv_maneuver}")
    
    # Plot: Tunneling-Rate vs. Asymmetry
    asymmetry = np.linspace(0, 1, 50)
    rates = []
    for a in asymmetry:
        field, freq = vektorpu.generate_asymmetric_field(a)
        r, _ = vektorpu.tunnel_vortex_pairs(field, freq)
        rates.append(r)
    plt.plot(asymmetry, rates)
    plt.xlabel('Asymmetry')
    plt.ylabel('Tunneling Rate [/s]')
    plt.title('UBC-Style: Vortex-Paare in Superfluid-Cavity')
    plt.savefig('vortex_tunneling.png')
    plt.close()
    print("[Testkit] Plot: vortex_tunneling.png")
    
    return "Complete: Asymmetrische Felder -> Vortex-Thrust."

if __name__ == "__main__":
    result = run_simulation()
    print(result)

```
