<｜begin▁of▁sentence｜>### Instruction:
Imagine you're analyzing a theoretical model of interconnected particles where the connections represent potential energy pathways between the particles. This model is depicted as an undirected graph, with the set of connections indicated as pairs of particles: [(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (3, 5)]. In this energy network, consider two clusters of particles represented by the sets S = {1, 2} and T = {4, 5}.

Your objective is to determine a fundamental property of this network: the normalized energy partitioning, or cut size, between these two clusters, using computational tools such as NetworkX. How could you go about calculating this normalized cut size between the sets S and T within the framework of this particle system?
### Response:
import networkx as nx
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5), (3, 5)])
S = {1, 2}
T = {4, 5}
cut_size = nx.normalized_cut_size(G, S, T, weight='weight')
print('Normalized cut size between set S and set T:', cut_size)
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