def get_tw_costs(N):
G, gamma, beta = get_test_problem(N, p=3, d=3)
composer = QtreeQAOAComposer(graph=G, gamma=gamma, beta=beta)
composer.energy_expectation_lightcone(list(G.edges())[0])
tn = QtreeTensorNet.from_qtree_gates(composer.circuit)
opt = OrderingOptimizer()
peo, _ = opt.optimize(tn)
tw = opt.treewidth
mems, flops = tn.simulation_cost(peo)
print('Max memory=', max(mems), 'Total flops=', sum(flops),
'Treewidth=', tw)
return tw, max(mems), sum(flops)
def test_qtree_smoke():
G, gamma, beta = get_test_problem()
composer = QtreeQAOAComposer(
graph=G, gamma=[np.pi/3], beta=[np.pi/4])
composer.ansatz_state()
print(composer.circuit)
assert composer.circuit
assert composer.n_qubits == G.number_of_nodes()
composer = QtreeQAOAComposer(
graph=G, gamma=[np.pi/3], beta=[np.pi/4])
composer.energy_expectation_lightcone(list(G.edges())[0])
print(composer.circuit)
assert composer.circuit
assert composer.n_qubits == G.number_of_nodes()
def add_two_nodes_to_leafs(graph):
""" Works in-place """
leaves = [n for n in graph.nodes() if graph.degree(n) <= 1]
n = graph.number_of_nodes()
for leaf in leaves:
graph.add_edges_from([(leaf, n + 1), (leaf, n + 2)])
n += 2
graph = nx.Graph()
graph.add_edges_from([(0, 1)])
for i in range(n):
add_two_nodes_to_leafs(graph)
return graph
D = 6
G = bethe_lattice(D)
for p in range(1, D + 1):
print(f'{p=}, {G.number_of_nodes()=}')
gamma, beta = [0.1] * p, [0.2] * p
composer = QtreeQAOAComposer(graph=G, gamma=gamma, beta=beta)
composer.energy_expectation_lightcone((0, 1))
tn = QtreeTensorNet.from_qtree_gates(composer.circuit)
print(f'{tn.get_line_graph().number_of_nodes()=}')
opt = OrderingOptimizer()
peo, tn = opt.optimize(tn)
treewidth = opt.treewidth
print(f"{treewidth=}")