def test_contract_trace_edges(self):
net = network.TensorNetwork(backend="tensorflow")
a = net.add_node(np.ones([4, 5, 2, 3, 4]))
b = net.add_node(np.ones([3, 2, 3, 5]))
net.connect(a[2], b[1])
net.connect(a[1], b[3])
net.connect(b[0], b[2])
net.connect(a[0], a[4])
e = a[1]
net, sizes, sizes_none = stochastic_contractor.contract_trace_edges(
net)
self.assertDictEqual(sizes, {e.node1: 30, e.node2: 10})
self.assertDictEqual(sizes_none, dict())
def test_contraction_parallel_edges(self):
net = network.TensorNetwork(backend="tensorflow")
a = net.add_node(np.ones([4, 5, 2]))
b = net.add_node(np.ones([3, 2, 3, 5]))
c = net.add_node(np.ones([
4,
]))
net.connect(a[2], b[1])
net.connect(b[0], b[2])
net.connect(a[1], b[3])
net.connect(a[0], c[0])
net = stochastic_contractor.stochastic(net, 2)
net.check_correct()
res = net.get_final_node()
self.assertAllClose(res.get_tensor(), 120)
def test_contraction_disconnected(self):
net = network.TensorNetwork(backend="tensorflow")
a = net.add_node(np.ones([4, 5, 2]))
b = net.add_node(np.ones([3, 2, 3]))
edge1 = a[0]
net.connect(a[2], b[1])
net.connect(b[0], b[2])
c = net.add_node(np.ones([3, 4]))
d = net.add_node(np.ones([4, 3]))
edge2 = c[0]
net.connect(c[1], d[0])
net = stochastic_contractor.stochastic(net, 2)
net.check_correct(check_connected=False)
node1, node2 = edge1.node1, edge2.node1
self.assertAllClose(node1.get_tensor(), 6 * np.ones([4, 5]))
self.assertAllClose(node2.get_tensor(), 4 * np.ones([3, 3]))
def test_swap_gate(): net = network.TensorNetwork(backend="jax") # Prepare input state: 0.6|00> + 0.8|10> q0_in = net.add_node(np.array([0.6, 0.8], dtype=np.float64)) q1_in = net.add_node(np.array([1, 0], dtype=np.float64)) # Prepare output state: 0.6|00> + 0.8|01> q0_out = net.add_node(np.array([1, 0], dtype=np.float64)) q1_out = net.add_node(np.array([0.6, 0.8], dtype=np.float64)) # Build quantum circuit: three CNOTs implement a SWAP copy_node_1, q0_t1, q1_t1 = add_cnot(net, q0_in[0], q1_in[0]) copy_node_2, q1_t2, q0_t2 = add_cnot(net, q1_t1, q0_t1) copy_node_3, q0_t3, q1_t3 = add_cnot(net, q0_t2, q1_t2) net.connect(q0_t3, q0_out[0]) net.connect(q1_t3, q1_out[0]) # Contract the network, first Bucket Elimination, then naive to complete. contraction_order = (copy_node_1, copy_node_2, copy_node_3) net = bucket(net, contraction_order) net = naive(net) result = net.get_final_node() # Verify that SWAP has turned |10> into |01> and kept |00> unchanged. np.testing.assert_allclose(result.get_tensor(), 1.0)
def test_cnot_gate(): net = network.TensorNetwork(backend="numpy") # Prepare input state: |11> q0_in = net.add_node(np.array([0, 1], dtype=np.float64)) q1_in = net.add_node(np.array([0, 1], dtype=np.float64)) # Prepare output state: |10> q0_out = net.add_node(np.array([0, 1], dtype=np.float64)) q1_out = net.add_node(np.array([1, 0], dtype=np.float64)) # Build quantum circuit copy_node, q0_t1, q1_t1 = add_cnot(net, q0_in[0], q1_in[0]) net.connect(q0_t1, q0_out[0]) net.connect(q1_t1, q1_out[0]) # Contract the network, first using Bucket Elimination, then once # no more copy tensors are left to exploit, fall back to the naive # contractor. contraction_order = (copy_node,) net = bucket(net, contraction_order) net = naive(net) result = net.get_final_node() # Verify that CNOT has turned |11> into |10>. np.testing.assert_allclose(result.get_tensor(), 1.0)
def _build_network(
tensors: Sequence[Tensor], network_structure: Sequence[Sequence]
) -> Tuple[network.TensorNetwork, Dict[Any, network_components.Edge]]:
tn = network.TensorNetwork()
nodes = []
edges = {}
for i, (tensor, edge_lbls) in enumerate(zip(tensors, network_structure)):
if len(tensor.shape) != len(edge_lbls):
raise ValueError(
"Incorrect number of edge labels specified tensor {}".format(i))
node = tn.add_node(tensor, name="tensor_{}".format(i))
nodes.append(node)
for (axis_num, edge_lbl) in enumerate(edge_lbls):
if edge_lbl not in edges:
e = node[axis_num]
e.set_name(str(edge_lbl))
edges[edge_lbl] = e
else:
# This will raise an error if the edges are not dangling.
e = tn.connect(edges[edge_lbl], node[axis_num], name=str(edge_lbl))
edges[edge_lbl] = e
return tn, edges
def test_cost_contract_between_no_shared_edges(backend):
net = network.TensorNetwork(backend=backend)
a = net.add_node(np.ones((2, 3, 4, 5)))
b = net.add_node(np.ones((7, 3, 9, 5)))
with pytest.raises(ValueError):
cost_calculators.cost_contract_between(a, b)
