Helpful_C

 Helpful explanations from COPILOT:

import numpy as np

import networkx as nx

import cirq

import matplotlib.pyplot as plt

# Set the seed for reproducibility

np.random.seed(seed=11)

# Identify working qubits from the device

device_qubits = working_device.metadata.qubit_set

working_qubits = sorted(device_qubits)[:12]

# Populate a networkx graph with working_qubits as nodes

working_graph = working_device.metadata.nx_graph.subgraph(working_qubits)

# Add random weights to edges of the graph

nx.set_edge_attributes(

    working_graph,

    {e: {"weight": np.random.randint(0, 500) / 100} for e in working_graph.edges},

)

# Draw the working_graph on a 2D grid

pos = {q: (q.col, -q.row) for q in working_graph.nodes()}

nx.draw(working_graph, pos=pos, with_labels=True, node_size=1000)

plt.show()

                                                           

Explain how the cost estimate is found?