hardware

# 硬件集成 本指南涵盖了通过 Cirq 的设备接口和服务提供商在真实量子硬件上运行量子电路的方法。 ## 设备表示 ### 设备类 python import cirq # 定义具有连接性的设备 class MyDevice(cirq.Device): def __init__(self, qubits, connectivity): self.qubits = qubits self.connectivity = connectivity @property def metadata(self): return cirq.DeviceMetadata( self.qubits, self.connectivity ) def validate_operation(self, operation): # 检查操作在该设备上是否有效 if len(operation.qubits) == 2: q0, q1 = operation.qubits if (q0, q1) not in self.connectivity: raise ValueError(f"量子比特 {q0} 和 {q1} 未连接") ### 设备约束 python # 检查设备元数据 device = cirq_google.Sycamore # 获取量子比特拓扑 qubits = device.metadata.qubit_set print(f"可用量子比特: {len(qubits)}") # 检查连接性 for q0 in qubits: neighbors = device.metadata.nx_graph.neighbors(q0) print(f"{q0} 连接至: {list(neighbors)}") # 验证电路是否符合设备要求 try: device.validate_circuit(circuit) print("电路对该设备有效") except ValueError as e: print(f"无效电路: {e}") ## 量子比特选择 ### 最佳量子比特选择 python import cirq_google # 获取校准指标 processor = cirq_google.get_engine().get_processor('weber') calibration = processor.get_current_calibration() # 查找具有最低错误率的量子比特 def select_best_qubits(calibration, n_qubits): """选择具有最佳单量子比特门保真度的 n 个量子比特。""" qubit_fidelities = {} for qubit in calibration.keys(): if 'single_qubit_rb_average_error_per_gate' in calibration[qubit]: error = calibration[qubit]['single_qubit_rb_average_error_per_gate'] qubit_fidelities[qubit] = 1 - error # 按保真度排序 best_qubits = sorted( qubit_fidelities.items(), key=lambda x: x[1], reverse=True )[:n_qubits] return [q for q, _ in best_qubits] best_qubits = select_best_qubits(calibration, n_qubits=10) ### 拓扑感知选择 python def select_connected_qubits(device, n_qubits): """选择形成路径或网格的连接量子比特。""" graph = device.metadata.nx_graph # 查找连接的子图 import networkx as nx for node in graph