<｜begin▁of▁sentence｜>### Instruction:
Given the need to simulate the growth of a network following the GN model with 10 nodes, where the probability of a new node connecting to an existing node is proportional to the existing node's degree raised to the power of 1.5, how would you create such a network and list its edges using NetworkX?
### Response:
import networkx as nx

# Generate a GN graph with 10 nodes
D = nx.gn_graph(10, seed=42)

# Convert it to an undirected graph
G = D.to_undirected()

# Print the edges of the graph
print(G.edges())

# Specify an attachment kernel and generate a GN graph with 10 nodes
kernel_func = lambda x: x ** 1.5
D_custom_kernel = nx.gn_graph(10, kernel=kernel_func, seed=42)

# Print the edges of the graph with custom kernel
print(D_custom_kernel.edges())
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