<｜begin▁of▁sentence｜>### Instruction:
As an aerospace engineer, imagine you're tasked with streamlining communication channels between separate teams working on a project. You have four teams labeled A, B, C, and D, corresponding to nodes [0, 1, 2, 3]. The current communication channels are set up such that team A communicates with team B, team B with team C, and team C with team D, represented by the edge set [(0, 1), (1, 2), (2, 3)]. To make the communication more efficient, you plan to reorganize the teams into two groups: Group 1 consisting of teams A and B, and Group 2 consisting of teams C and D, corresponding to the node partition [{0, 1}, {2, 3}].

Your goal is to conceptualize a new communication graph that represents the connections between these two groups rather than individual teams. Could you illustrate how these restructured communication pathways between the new groups would be represented as edges in a quotient graph? This simplified model could then be used to optimize coordination and resource allocation between the two groups in our aerospace project. Please use NetworkX to assist in visualizing and outputting the edges of this reconfigured communication network.
### Response:
import networkx as nx

# Define a graph
H = nx.path_graph(4)

# Define a partition of the graph's nodes
partition = [{0, 1}, {2, 3}]

# Create the quotient graph based on the defined partition
Q = nx.quotient_graph(H, partition, relabel=True)

# Print the edges of the quotient graph
print(list(Q.edges()))
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