def optimize_1q_gates(circuit):
"""Simplify runs of single qubit gates in the QX basis.
Return a new circuit that has been optimized.
"""
qx_basis = ["u1", "u2", "u3", "cx", "id"]
dag_unroller = DagUnroller(circuit, DAGBackend(qx_basis))
unrolled = dag_unroller.expand_gates()
runs = unrolled.collect_runs(["u1", "u2", "u3", "id"])
for run in runs:
qname = unrolled.multi_graph.node[run[0]]["qargs"][0]
right_name = "u1"
right_parameters = (N(0), N(0), N(0)) # (theta, phi, lambda)
for current_node in run:
nd = unrolled.multi_graph.node[current_node]
assert nd["condition"] is None, "internal error"
assert len(nd["qargs"]) == 1, "internal error"
assert nd["qargs"][0] == qname, "internal error"
left_name = nd["name"]
assert left_name in ["u1", "u2", "u3", "id"], "internal error"
if left_name == "u1":
left_parameters = (N(0), N(0), nd["params"][0])
elif left_name == "u2":
left_parameters = (sympy.pi / 2, nd["params"][0], nd["params"][1])
elif left_name == "u3":
left_parameters = tuple(nd["params"])
else:
left_name = "u1" # replace id with u1
left_parameters = (N(0), N(0), N(0))
# Compose gates
name_tuple = (left_name, right_name)
if name_tuple == ("u1", "u1"):
# u1(lambda1) * u1(lambda2) = u1(lambda1 + lambda2)
right_parameters = (N(0), N(0), right_parameters[2] +
left_parameters[2])
elif name_tuple == ("u1", "u2"):
# u1(lambda1) * u2(phi2, lambda2) = u2(phi2 + lambda1, lambda2)
right_parameters = (sympy.pi / 2, right_parameters[1] +
left_parameters[2], right_parameters[2])
elif name_tuple == ("u2", "u1"):
# u2(phi1, lambda1) * u1(lambda2) = u2(phi1, lambda1 + lambda2)
right_name = "u2"
right_parameters = (sympy.pi / 2, left_parameters[1],
right_parameters[2] + left_parameters[2])
elif name_tuple == ("u1", "u3"):
# u1(lambda1) * u3(theta2, phi2, lambda2) =
# u3(theta2, phi2 + lambda1, lambda2)
right_parameters = (right_parameters[0], right_parameters[1] +
left_parameters[2], right_parameters[2])
elif name_tuple == ("u3", "u1"):
# u3(theta1, phi1, lambda1) * u1(lambda2) =
# u3(theta1, phi1, lambda1 + lambda2)
right_name = "u3"
right_parameters = (left_parameters[0], left_parameters[1],
right_parameters[2] + left_parameters[2])
elif name_tuple == ("u2", "u2"):
# Using Ry(pi/2).Rz(2*lambda).Ry(pi/2) =
# Rz(pi/2).Ry(pi-2*lambda).Rz(pi/2),
# u2(phi1, lambda1) * u2(phi2, lambda2) =
# u3(pi - lambda1 - phi2, phi1 + pi/2, lambda2 + pi/2)
right_name = "u3"
right_parameters = (sympy.pi - left_parameters[2] -
right_parameters[1], left_parameters[1] +
sympy.pi / 2, right_parameters[2] +
sympy.pi / 2)
elif name_tuple[1] == "nop":
right_name = left_name
right_parameters = left_parameters
else:
# For composing u3's or u2's with u3's, use
# u2(phi, lambda) = u3(pi/2, phi, lambda)
# together with the qiskit.mapper.compose_u3 method.
right_name = "u3"
# Evaluate the symbolic expressions for efficiency
left_parameters = tuple(map(lambda x: x.evalf(), list(left_parameters)))
right_parameters = tuple(map(lambda x: x.evalf(), list(right_parameters)))
right_parameters = compose_u3(left_parameters[0],
left_parameters[1],
left_parameters[2],
right_parameters[0],
right_parameters[1],
right_parameters[2])
# Why evalf()? This program:
# OPENQASM 2.0;
# include "qelib1.inc";
# qreg q[2];
# creg c[2];
# u3(0.518016983430947*pi,1.37051598592907*pi,1.36816383603222*pi) q[0];
# u3(1.69867232277986*pi,0.371448347747471*pi,0.461117217930936*pi) q[0];
# u3(0.294319836336836*pi,0.450325871124225*pi,1.46804720442555*pi) q[0];
# measure q -> c;
# took >630 seconds (did not complete) to optimize without
# calling evalf() at all, 19 seconds to optimize calling
# evalf() AFTER compose_u3, and 1 second to optimize
# calling evalf() BEFORE compose_u3.
# 1. Here down, when we simplify, we add f(theta) to lambda to
# correct the global phase when f(theta) is 2*pi. This isn't
# necessary but the other steps preserve the global phase, so
# we continue in that manner.
# 2. The final step will remove Z rotations by 2*pi.
# 3. Note that is_zero is true only if the expression is exactly
# zero. If the input expressions have already been evaluated
# then these final simplifications will not occur.
# TODO After we refactor, we should have separate passes for
# exact and approximate rewriting.
# Y rotation is 0 mod 2*pi, so the gate is a u1
if (right_parameters[0] % (2 * sympy.pi)).is_zero \
and right_name != "u1":
right_name = "u1"
right_parameters = (0, 0, right_parameters[1] +
right_parameters[2] +
right_parameters[0])
# Y rotation is pi/2 or -pi/2 mod 2*pi, so the gate is a u2
if right_name == "u3":
# theta = pi/2 + 2*k*pi
if ((right_parameters[0] - sympy.pi / 2) % (2 * sympy.pi)).is_zero:
right_name = "u2"
right_parameters = (sympy.pi / 2, right_parameters[1],
right_parameters[2] +
(right_parameters[0] - sympy.pi / 2))
# theta = -pi/2 + 2*k*pi
if ((right_parameters[0] + sympy.pi / 2) % (2 * sympy.pi)).is_zero:
right_name = "u2"
right_parameters = (sympy.pi / 2, right_parameters[1] +
sympy.pi, right_parameters[2] -
sympy.pi + (right_parameters[0] +
sympy.pi / 2))
# u1 and lambda is 0 mod 2*pi so gate is nop (up to a global phase)
if right_name == "u1" and (right_parameters[2] % (2 * sympy.pi)).is_zero:
right_name = "nop"
# Simplify the symbolic parameters
right_parameters = tuple(map(sympy.simplify, list(right_parameters)))
# Replace the data of the first node in the run
new_params = []
if right_name == "u1":
new_params = [right_parameters[2]]
if right_name == "u2":
new_params = [right_parameters[1], right_parameters[2]]
if right_name == "u3":
new_params = list(right_parameters)
nx.set_node_attributes(unrolled.multi_graph, name='name',
values={run[0]: right_name})
# params is a list of sympy symbols
nx.set_node_attributes(unrolled.multi_graph, name='params',
values={run[0]: new_params})
# Delete the other nodes in the run
for current_node in run[1:]:
unrolled._remove_op_node(current_node)
if right_name == "nop":
unrolled._remove_op_node(run[0])
return unrolled
def swap_mapper(circuit_graph, coupling_graph,
initial_layout=None,
basis="cx,u1,u2,u3,id", trials=20, seed=None):
"""Map a DAGCircuit onto a CouplingGraph using swap gates.
Args:
circuit_graph (DAGCircuit): input DAG circuit
coupling_graph (CouplingGraph): coupling graph to map onto
initial_layout (dict): dict from qubits of circuit_graph to qubits
of coupling_graph (optional)
basis (str): basis string specifying basis of output DAGCircuit
trials (int): number of trials.
seed (int): initial seed.
Returns:
DAGCircuit: object containing a circuit equivalent to
circuit_graph that respects couplings in coupling_graph, and
a layout dict mapping qubits of circuit_graph into qubits
of coupling_graph. The layout may differ from the initial_layout
if the first layer of gates cannot be executed on the
initial_layout. Finally, returned is the final layer qubit
permutation that is needed to add measurements back in.
Raises:
MapperError: if there was any error during the mapping or with the
parameters.
"""
if circuit_graph.width() > coupling_graph.size():
raise MapperError("Not enough qubits in CouplingGraph")
# Schedule the input circuit
layerlist = list(circuit_graph.layers())
logger.debug("schedule:")
for i, v in enumerate(layerlist):
logger.debug(" %d: %s", i, v["partition"])
if initial_layout is not None:
# Check the input layout
circ_qubits = circuit_graph.get_qubits()
coup_qubits = coupling_graph.get_qubits()
qubit_subset = []
for k, v in initial_layout.items():
qubit_subset.append(v)
if k not in circ_qubits:
raise MapperError("initial_layout qubit %s[%d] not in input "
"DAGCircuit" % (k[0], k[1]))
if v not in coup_qubits:
raise MapperError("initial_layout qubit %s[%d] not in input "
"CouplingGraph" % (v[0], v[1]))
else:
# Supply a default layout
qubit_subset = coupling_graph.get_qubits()
qubit_subset = qubit_subset[0:circuit_graph.width()]
initial_layout = {a: b for a, b in
zip(circuit_graph.get_qubits(), qubit_subset)}
# Find swap circuit to preceed to each layer of input circuit
layout = initial_layout.copy()
layout_max_index = max(map(lambda x: x[1]+1, layout.values()))
# Construct an empty DAGCircuit with one qreg "q"
# and the same set of cregs as the input circuit
dagcircuit_output = DAGCircuit()
dagcircuit_output.name = circuit_graph.name
dagcircuit_output.add_qreg("q", layout_max_index)
for name, size in circuit_graph.cregs.items():
dagcircuit_output.add_creg(name, size)
# Make a trivial wire mapping between the subcircuits
# returned by swap_mapper_layer_update and the circuit
# we are building
identity_wire_map = {}
for j in range(layout_max_index):
identity_wire_map[("q", j)] = ("q", j)
for name, size in circuit_graph.cregs.items():
for j in range(size):
identity_wire_map[(name, j)] = (name, j)
first_layer = True # True until first layer is output
logger.debug("initial_layout = %s", layout)
# Iterate over layers
for i, layer in enumerate(layerlist):
# Attempt to find a permutation for this layer
success_flag, best_circ, best_d, best_layout, trivial_flag \
= layer_permutation(layer["partition"], layout,
qubit_subset, coupling_graph, trials, seed)
logger.debug("swap_mapper: layer %d", i)
logger.debug("swap_mapper: success_flag=%s,best_d=%s,trivial_flag=%s",
success_flag, str(best_d), trivial_flag)
# If this fails, try one gate at a time in this layer
if not success_flag:
logger.debug("swap_mapper: failed, layer %d, "
"retrying sequentially", i)
serial_layerlist = list(layer["graph"].serial_layers())
# Go through each gate in the layer
for j, serial_layer in enumerate(serial_layerlist):
success_flag, best_circ, best_d, best_layout, trivial_flag \
= layer_permutation(serial_layer["partition"],
layout, qubit_subset, coupling_graph,
trials, seed)
logger.debug("swap_mapper: layer %d, sublayer %d", i, j)
logger.debug("swap_mapper: success_flag=%s,best_d=%s,"
"trivial_flag=%s",
success_flag, str(best_d), trivial_flag)
# Give up if we fail again
if not success_flag:
raise MapperError("swap_mapper failed: " +
"layer %d, sublayer %d" % (i, j) +
", \"%s\"" %
serial_layer["graph"].qasm(
no_decls=True,
aliases=layout))
# If this layer is only single-qubit gates,
# and we have yet to see multi-qubit gates,
# continue to the next inner iteration
if trivial_flag and first_layer:
logger.debug("swap_mapper: skip to next sublayer")
continue
# Update the record of qubit positions for each inner iteration
layout = best_layout
# Update the QASM
dagcircuit_output.compose_back(
swap_mapper_layer_update(j,
first_layer,
best_layout,
best_d,
best_circ,
serial_layerlist),
identity_wire_map)
# Update initial layout
if first_layer:
initial_layout = layout
first_layer = False
else:
# Update the record of qubit positions for each iteration
layout = best_layout
# Update the QASM
dagcircuit_output.compose_back(
swap_mapper_layer_update(i,
first_layer,
best_layout,
best_d,
best_circ,
layerlist),
identity_wire_map)
# Update initial layout
if first_layer:
initial_layout = layout
first_layer = False
# This is the final layout that we need to correctly replace
# any measurements that needed to be removed before the swap
last_layout = layout
# If first_layer is still set, the circuit only has single-qubit gates
# so we can use the initial layout to output the entire circuit
if first_layer:
layout = initial_layout
for i, layer in enumerate(layerlist):
dagcircuit_output.compose_back(layer["graph"], layout)
# Parse openqasm_output into DAGCircuit object
dag_unrolled = DagUnroller(dagcircuit_output,
DAGBackend(basis.split(",")))
dagcircuit_output = dag_unrolled.expand_gates()
return dagcircuit_output, initial_layout, last_layout