┌──────────────────────────────────────────────┐
│ QUBIT LÓGICO FRACTAL CRIOGÉNICO │
│ │
│ NANO-CLUSTER 1 │
│ - Modo vibracional │
│ - Modo eletrónico │
│ - Modo fotónico interno │
│ │
│ NANO-CLUSTER 2 │
│ - Redundância física │
│ - Blindagem térmica │
│ │
│ ... │
│ │
│ NANO-CLUSTER N │
│ - Correção de erros embutida │
│ - Decoerência distribuída │
└──────────────────────────────────────────────┘
import numpy as np
import matplotlib.pyplot as plt
# -----------------------------
# 1. Nano-cluster model
# -----------------------------
class NanoCluster:
def __init__(self, temp_mK=10, noise_level=0.001):
self.temp = temp_mK
self.noise = noise_level
# Internal quantum modes (conceptual)
self.vibrational = np.random.rand() * 0.1
self.electronic = np.random.rand() * 0.1
self.photonic = np.random.rand() * 0.1
# Initial state (Bloch sphere representation)
self.theta = np.pi/4
self.phi = np.pi/3
def evolve(self, dt):
# Decoherence decreases with lower temperature and redundancy
decoherence = self.noise * (self.temp / 10.0)
# Random phase drift
self.phi += np.random.randn() * decoherence * dt
# Slight amplitude damping
self.theta += np.random.randn() * decoherence * dt
# Keep values bounded
self.theta = np.clip(self.theta, 0, np.pi)
self.phi = np.mod(self.phi, 2*np.pi)
def state_vector(self):
# Convert Bloch angles to qubit state vector
return np.array([
np.cos(self.theta/2),
np.exp(1j*self.phi) * np.sin(self.theta/2)
])
# -----------------------------
# 2. Logical fractal qubit
# -----------------------------
class FractalLogicalQubit:
def __init__(self, n_clusters=50):
self.clusters = [NanoCluster() for _ in range(n_clusters)]
self.n = n_clusters
def evolve(self, dt):
for c in self.clusters:
c.evolve(dt)
def logical_state(self):
# Average state vector across all nano-clusters
states = np.array([c.state_vector() for c in self.clusters])
return np.mean(states, axis=0)
def coherence(self):
# Coherence = magnitude of average Bloch vector
state = self.logical_state()
return np.abs(np.vdot(state, state))
# -----------------------------
# 3. Simulation
# -----------------------------
qubit = FractalLogicalQubit(n_clusters=200)
timesteps = 500
dt = 0.1
coherence_values = []
for t in range(timesteps):
qubit.evolve(dt)
coherence_values.append(qubit.coherence())
# -----------------------------
# 4. Plot results
# -----------------------------
plt.figure(figsize=(10,5))
plt.plot(coherence_values, label="Coerência lógica fractal")
plt.xlabel("Tempo (unidades arbitrárias)")
plt.ylabel("Coerência")
plt.title("Simulação de Qubit Lógico Fractal Criogénico")
plt.legend()
plt.grid(True)
plt.show()
