def test_opaque_instruction_with_label(self):
"""Test that custom opaque instruction is correctly serialized with a label"""
custom_gate = Instruction("black_box", 1, 0, [])
custom_gate.label = "My Special Black Box Instruction"
qc = QuantumCircuit(1)
qc.append(custom_gate, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circ = load(qpy_file)[0]
self.assertEqual(qc, new_circ)
self.assertEqual([x[0].label for x in qc.data], [x[0].label for x in new_circ.data])
def _parse_custom_instruction(custom_instructions, gate_name, params):
(type_str, num_qubits, num_clbits, definition) = custom_instructions[gate_name]
if type_str == "i":
inst_obj = Instruction(gate_name, num_qubits, num_clbits, params)
if definition:
inst_obj.definition = definition
elif type_str == "g":
inst_obj = Gate(gate_name, num_qubits, params)
inst_obj.definition = definition
else:
raise ValueError("Invalid custom instruction type '%s'" % type_str)
return inst_obj
def circuit_to_instruction(circuit):
"""Build an ``Instruction`` object from a ``QuantumCircuit``.
The instruction is anonymous (not tied to a named quantum register),
and so can be inserted into another circuit. The instruction will
have the same string name as the circuit.
Args:
circuit (QuantumCircuit): the input circuit.
Return:
Instruction: an instruction equivalent to the action of the
input circuit. Upon decomposition, this instruction will
yield the components comprising the original circuit.
"""
instruction = Instruction(
name=circuit.name,
num_qubits=sum([qreg.size for qreg in circuit.qregs]),
num_clbits=sum([creg.size for creg in circuit.cregs]),
params=[])
instruction.control = None
def find_bit_position(bit):
"""find the index of a given bit (Register, int) within
a flat ordered list of bits of the circuit
"""
if isinstance(bit[0], QuantumRegister):
ordered_regs = circuit.qregs
else:
ordered_regs = circuit.cregs
reg_index = ordered_regs.index(bit[0])
return sum([reg.size for reg in ordered_regs[:reg_index]]) + bit[1]
definition = circuit.data.copy()
if instruction.num_qubits > 0:
q = QuantumRegister(instruction.num_qubits, 'q')
if instruction.num_clbits > 0:
c = ClassicalRegister(instruction.num_clbits, 'c')
definition = list(
map(
lambda x:
(x[0], list(map(lambda y: (q, find_bit_position(y)), x[1])),
list(map(lambda y:
(c, find_bit_position(y)), x[2]))), definition))
instruction.definition = definition
return instruction
def test_custom_instruction(self):
"""Test that custom instruction is correctly serialized"""
custom_gate = Instruction("black_box", 1, 0, [])
custom_definition = QuantumCircuit(1)
custom_definition.h(0)
custom_definition.rz(1.5, 0)
custom_definition.sdg(0)
custom_gate.definition = custom_definition
qc = QuantumCircuit(1)
qc.append(custom_gate, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circ = load(qpy_file)[0]
self.assertEqual(qc, new_circ)
self.assertEqual(qc.decompose(), new_circ.decompose())
def to_instruction(self):
"""Convert to a Kraus or UnitaryGate circuit instruction.
If the channel is unitary it will be added as a unitary gate,
otherwise it will be added as a kraus simulator instruction.
Returns:
qiskit.circuit.Instruction: A kraus instruction for the channel.
Raises:
QiskitError: if input data is not an N-qubit CPTP quantum channel.
"""
from qiskit.circuit.instruction import Instruction
# Check if input is an N-qubit CPTP channel.
num_qubits = int(np.log2(self._input_dim))
if self._input_dim != self._output_dim or 2**num_qubits != self._input_dim:
raise QiskitError(
'Cannot convert QuantumChannel to Instruction: channel is not an N-qubit channel.'
)
if not self.is_cptp():
raise QiskitError(
'Cannot convert QuantumChannel to Instruction: channel is not CPTP.'
)
# Next we convert to the Kraus representation. Since channel is CPTP we know
# that there is only a single set of Kraus operators
kraus, _ = _to_kraus(self._channel_rep, self._data, *self.dim)
# If we only have a single Kraus operator then the channel is
# a unitary channel so can be converted to a UnitaryGate. We do this by
# converting to an Operator and using its to_instruction method
if len(kraus) == 1:
return Operator(kraus[0]).to_instruction()
return Instruction('kraus', num_qubits, 0, kraus)
def test_custom_instruction_with_label(self):
"""Test that custom instruction is correctly serialized with a label"""
custom_gate = Instruction("black_box", 1, 0, [])
custom_definition = QuantumCircuit(1)
custom_definition.h(0)
custom_definition.rz(1.5, 0)
custom_definition.sdg(0)
custom_gate.definition = custom_definition
custom_gate.label = "My Special Black Box Instruction with a definition"
qc = QuantumCircuit(1)
qc.append(custom_gate, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circ = load(qpy_file)[0]
self.assertEqual(qc, new_circ)
self.assertEqual(qc.decompose(), new_circ.decompose())
self.assertEqual([x[0].label for x in qc.data], [x[0].label for x in new_circ.data])
def _parse_custom_instruction(custom_instructions, gate_name, params):
type_str, num_qubits, num_clbits, definition = custom_instructions[gate_name]
type_key = common.CircuitInstructionTypeKey(type_str)
if type_key == common.CircuitInstructionTypeKey.INSTRUCTION:
inst_obj = Instruction(gate_name, num_qubits, num_clbits, params)
if definition is not None:
inst_obj.definition = definition
return inst_obj
if type_key == common.CircuitInstructionTypeKey.GATE:
inst_obj = Gate(gate_name, num_qubits, params)
inst_obj.definition = definition
return inst_obj
if type_key == common.CircuitInstructionTypeKey.PAULI_EVOL_GATE:
return definition
raise ValueError("Invalid custom instruction type '%s'" % type_str)
def test_empty_tuple_param(self):
"""Test qpy with an instruction that contains an empty tuple."""
inst = Instruction("empty_tuple_test", 1, 0, [tuple()])
qc = QuantumCircuit(1)
qc.append(inst, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circuit = load(qpy_file)[0]
self.assertEqual(qc, new_circuit)
def test_nested_tuple_param(self):
"""Test qpy with an instruction that contains nested tuples."""
inst = Instruction("tuple_test", 1, 0, [((((0, 1), (0, 1)), 2, 3), ("A", "B", "C"))])
qc = QuantumCircuit(1)
qc.append(inst, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circuit = load(qpy_file)[0]
self.assertEqual(qc, new_circuit)
def test_opaque_instruction(self):
"""Test that custom opaque instruction is correctly serialized"""
custom_gate = Instruction("black_box", 1, 0, [])
qc = QuantumCircuit(1)
qc.append(custom_gate, [0])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circ = load(qpy_file)[0]
self.assertEqual(qc, new_circ)
def _parse_custom_operation(custom_operations, gate_name, params, version,
vectors, registers):
if version >= 5:
(
type_str,
num_qubits,
num_clbits,
definition,
num_ctrl_qubits,
ctrl_state,
base_gate_raw,
) = custom_operations[gate_name]
else:
type_str, num_qubits, num_clbits, definition = custom_operations[
gate_name]
type_key = type_keys.CircuitInstruction(type_str)
if type_key == type_keys.CircuitInstruction.INSTRUCTION:
inst_obj = Instruction(gate_name, num_qubits, num_clbits, params)
if definition is not None:
inst_obj.definition = definition
return inst_obj
if type_key == type_keys.CircuitInstruction.GATE:
inst_obj = Gate(gate_name, num_qubits, params)
inst_obj.definition = definition
return inst_obj
if version >= 5 and type_key == type_keys.CircuitInstruction.CONTROLLED_GATE:
with io.BytesIO(base_gate_raw) as base_gate_obj:
base_gate = _read_instruction(base_gate_obj, None, registers,
custom_operations, version, vectors)
if ctrl_state < 2**num_ctrl_qubits - 1:
# If open controls, we need to discard the control suffix when setting the name.
gate_name = gate_name.rsplit("_", 1)[0]
inst_obj = ControlledGate(
gate_name,
num_qubits,
params,
num_ctrl_qubits=num_ctrl_qubits,
ctrl_state=ctrl_state,
base_gate=base_gate,
)
inst_obj.definition = definition
return inst_obj
if type_key == type_keys.CircuitInstruction.PAULI_EVOL_GATE:
return definition
raise ValueError("Invalid custom instruction type '%s'" % type_str)
def _create_op(self, name, params):
if name in self.standard_extension:
op = self.standard_extension[name](*params)
elif name in self.gates:
if self.gates[name]['opaque']:
# call an opaque gate
op = Gate(name=name, num_qubits=self.gates[name]['n_bits'], params=params)
else:
# call a custom gate
op = Instruction(name=name,
num_qubits=self.gates[name]['n_bits'],
num_clbits=0,
params=params)
op.definition = self._gate_rules_to_qiskit_circuit(self.gates[name],
params=params)
else:
raise QiskitError("unknown operation for ast node name %s" % name)
return op
def test_custom_instruction_with_noop_definition(self):
"""Test that a custom instruction whose definition contains no elements is serialized with a
proper definition.
Regression test of gh-7429."""
empty = QuantumCircuit(1, name="empty").to_instruction()
opaque = Instruction("opaque", 1, 0, [])
qc = QuantumCircuit(2)
qc.append(empty, [0], [])
qc.append(opaque, [1], [])
qpy_file = io.BytesIO()
dump(qc, qpy_file)
qpy_file.seek(0)
new_circ = load(qpy_file)[0]
self.assertEqual(qc, new_circ)
self.assertEqual(qc.decompose(), new_circ.decompose())
self.assertEqual(len(new_circ), 2)
self.assertIsInstance(new_circ.data[0][0].definition, QuantumCircuit)
self.assertIs(new_circ.data[1][0].definition, None)
def _copy_mutable_properties(self, instruction: Instruction) -> Instruction:
"""Copy mutable properties from ourselves onto a non-placeholder instruction.
The mutable properties are expected to be things like ``condition``, added onto a
placeholder by the :meth:`c_if` method. This mutates ``instruction``, and returns the same
instance that was passed. This is mostly intended to make writing concrete versions of
:meth:`.concrete_instruction` easy.
The complete list of mutations is:
* ``condition``, added by :meth:`c_if`.
Args:
instruction: the concrete instruction instance to be mutated.
Returns:
The same instruction instance that was passed, but mutated to propagate the tracked
changes to this class.
"""
# In general the tuple creation should be a no-op, because ``tuple(t) is t`` for tuples.
instruction.condition = None if self.condition is None else tuple(self.condition)
return instruction
def circuit_to_instruction(circuit,
parameter_map=None,
equivalence_library=None):
"""Build an ``Instruction`` object from a ``QuantumCircuit``.
The instruction is anonymous (not tied to a named quantum register),
and so can be inserted into another circuit. The instruction will
have the same string name as the circuit.
Args:
circuit (QuantumCircuit): the input circuit.
parameter_map (dict): For parameterized circuits, a mapping from
parameters in the circuit to parameters to be used in the instruction.
If None, existing circuit parameters will also parameterize the
instruction.
equivalence_library (EquivalenceLibrary): Optional equivalence library
where the converted instruction will be registered.
Raises:
QiskitError: if parameter_map is not compatible with circuit
Return:
qiskit.circuit.Instruction: an instruction equivalent to the action of the
input circuit. Upon decomposition, this instruction will
yield the components comprising the original circuit.
Example:
.. jupyter-execute::
from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit
from qiskit.converters import circuit_to_instruction
%matplotlib inline
q = QuantumRegister(3, 'q')
c = ClassicalRegister(3, 'c')
circ = QuantumCircuit(q, c)
circ.h(q[0])
circ.cx(q[0], q[1])
circ.measure(q[0], c[0])
circ.rz(0.5, q[1]).c_if(c, 2)
circuit_to_instruction(circ)
"""
if parameter_map is None:
parameter_dict = {p: p for p in circuit.parameters}
else:
parameter_dict = circuit._unroll_param_dict(parameter_map)
if parameter_dict.keys() != circuit.parameters:
raise QiskitError(('parameter_map should map all circuit parameters. '
'Circuit parameters: {}, parameter_map: {}').format(
circuit.parameters, parameter_dict))
instruction = Instruction(
name=circuit.name,
num_qubits=sum([qreg.size for qreg in circuit.qregs]),
num_clbits=sum([creg.size for creg in circuit.cregs]),
params=sorted(parameter_dict.values(), key=lambda p: p.name))
instruction.condition = None
def find_bit_position(bit):
"""find the index of a given bit (Register, int) within
a flat ordered list of bits of the circuit
"""
if isinstance(bit, Qubit):
ordered_regs = circuit.qregs
else:
ordered_regs = circuit.cregs
reg_index = ordered_regs.index(bit.register)
return sum([reg.size for reg in ordered_regs[:reg_index]]) + bit.index
target = circuit.assign_parameters(parameter_dict, inplace=False)
if equivalence_library is not None:
equivalence_library.add_equivalence(instruction, target)
definition = target.data
if instruction.num_qubits > 0:
q = QuantumRegister(instruction.num_qubits, 'q')
if instruction.num_clbits > 0:
c = ClassicalRegister(instruction.num_clbits, 'c')
definition = list(
map(
lambda x:
(x[0], list(map(lambda y: q[find_bit_position(y)], x[1])),
list(map(lambda y: c[find_bit_position(y)], x[2]))), definition))
instruction.definition = definition
return instruction
def circuit_to_instruction(circuit, parameter_map=None):
"""Build an ``Instruction`` object from a ``QuantumCircuit``.
The instruction is anonymous (not tied to a named quantum register),
and so can be inserted into another circuit. The instruction will
have the same string name as the circuit.
Args:
circuit (QuantumCircuit): the input circuit.
parameter_map (dict): For parameterized circuits, a mapping from
parameters in the circuit to parameters to be used in the instruction.
If None, existing circuit parameters will also parameterize the
instruction.
Raises:
QiskitError: if parameter_map is not compatible with circuit
Return:
Instruction: an instruction equivalent to the action of the
input circuit. Upon decomposition, this instruction will
yield the components comprising the original circuit.
"""
if parameter_map is None:
parameter_map = {p: p for p in circuit.parameters}
if parameter_map.keys() != circuit.parameters:
raise QiskitError(('parameter_map should map all circuit parameters. '
'Circuit parameters: {}, parameter_map: {}').format(
circuit.parameters, parameter_map))
instruction = Instruction(name=circuit.name,
num_qubits=sum([qreg.size for qreg in circuit.qregs]),
num_clbits=sum([creg.size for creg in circuit.cregs]),
params=sorted(parameter_map.values(), key=lambda p: p.name))
instruction.control = None
def find_bit_position(bit):
"""find the index of a given bit (Register, int) within
a flat ordered list of bits of the circuit
"""
if isinstance(bit[0], QuantumRegister):
ordered_regs = circuit.qregs
else:
ordered_regs = circuit.cregs
reg_index = ordered_regs.index(bit[0])
return sum([reg.size for reg in ordered_regs[:reg_index]]) + bit[1]
target = circuit.copy()
target._substitute_parameters(parameter_map)
definition = target.data
if instruction.num_qubits > 0:
q = QuantumRegister(instruction.num_qubits, 'q')
if instruction.num_clbits > 0:
c = ClassicalRegister(instruction.num_clbits, 'c')
definition = list(map(lambda x:
(x[0],
list(map(lambda y: (q, find_bit_position(y)), x[1])),
list(map(lambda y: (c, find_bit_position(y)), x[2]))), definition))
instruction.definition = definition
return instruction
def circuit_to_instruction(circuit, parameter_map=None, equivalence_library=None, label=None):
"""Build an ``Instruction`` object from a ``QuantumCircuit``.
The instruction is anonymous (not tied to a named quantum register),
and so can be inserted into another circuit. The instruction will
have the same string name as the circuit.
Args:
circuit (QuantumCircuit): the input circuit.
parameter_map (dict): For parameterized circuits, a mapping from
parameters in the circuit to parameters to be used in the instruction.
If None, existing circuit parameters will also parameterize the
instruction.
equivalence_library (EquivalenceLibrary): Optional equivalence library
where the converted instruction will be registered.
label (str): Optional instruction label.
Raises:
QiskitError: if parameter_map is not compatible with circuit
Return:
qiskit.circuit.Instruction: an instruction equivalent to the action of the
input circuit. Upon decomposition, this instruction will
yield the components comprising the original circuit.
Example:
.. jupyter-execute::
from qiskit import QuantumRegister, ClassicalRegister, QuantumCircuit
from qiskit.converters import circuit_to_instruction
%matplotlib inline
q = QuantumRegister(3, 'q')
c = ClassicalRegister(3, 'c')
circ = QuantumCircuit(q, c)
circ.h(q[0])
circ.cx(q[0], q[1])
circ.measure(q[0], c[0])
circ.rz(0.5, q[1]).c_if(c, 2)
circuit_to_instruction(circ)
"""
# pylint: disable=cyclic-import
from qiskit.circuit.quantumcircuit import QuantumCircuit
if parameter_map is None:
parameter_dict = {p: p for p in circuit.parameters}
else:
parameter_dict = circuit._unroll_param_dict(parameter_map)
if parameter_dict.keys() != circuit.parameters:
raise QiskitError(
(
"parameter_map should map all circuit parameters. "
"Circuit parameters: {}, parameter_map: {}"
).format(circuit.parameters, parameter_dict)
)
instruction = Instruction(
name=circuit.name,
num_qubits=sum(qreg.size for qreg in circuit.qregs),
num_clbits=sum(creg.size for creg in circuit.cregs),
params=[*parameter_dict.values()],
label=label,
)
instruction.condition = None
target = circuit.assign_parameters(parameter_dict, inplace=False)
if equivalence_library is not None:
equivalence_library.add_equivalence(instruction, target)
definition = target.data
regs = []
if instruction.num_qubits > 0:
q = QuantumRegister(instruction.num_qubits, "q")
regs.append(q)
if instruction.num_clbits > 0:
c = ClassicalRegister(instruction.num_clbits, "c")
regs.append(c)
qubit_map = {bit: q[idx] for idx, bit in enumerate(circuit.qubits)}
clbit_map = {bit: c[idx] for idx, bit in enumerate(circuit.clbits)}
definition = [
(inst, [qubit_map[y] for y in qargs], [clbit_map[y] for y in cargs])
for inst, qargs, cargs in definition
]
# fix condition
for rule in definition:
condition = rule[0].condition
if condition:
reg, val = condition
if isinstance(reg, Clbit):
idx = 0
for creg in circuit.cregs:
if reg not in creg:
idx += creg.size
else:
cond_reg = creg
break
rule[0].condition = (c[idx + list(cond_reg).index(reg)], val)
elif reg.size == c.size:
rule[0].condition = (c, val)
else:
raise QiskitError(
"Cannot convert condition in circuit with "
"multiple classical registers to instruction"
)
qc = QuantumCircuit(*regs, name=instruction.name)
for instr, qargs, cargs in definition:
qc._append(instr, qargs, cargs)
if circuit.global_phase:
qc.global_phase = circuit.global_phase
instruction.definition = qc
return instruction
def _experiments_to_circuits(qobj):
"""Return a list of QuantumCircuit object(s) from a qobj.
Args:
qobj (Qobj): The Qobj object to convert to QuantumCircuits
Returns:
list: A list of QuantumCircuit objects from the qobj
"""
if not qobj.experiments:
return None
circuits = []
for exp in qobj.experiments:
quantum_registers = [QuantumRegister(i[1], name=i[0]) for i in exp.header.qreg_sizes]
classical_registers = [ClassicalRegister(i[1], name=i[0]) for i in exp.header.creg_sizes]
circuit = QuantumCircuit(*quantum_registers, *classical_registers, name=exp.header.name)
qreg_dict = collections.OrderedDict()
creg_dict = collections.OrderedDict()
for reg in quantum_registers:
qreg_dict[reg.name] = reg
for reg in classical_registers:
creg_dict[reg.name] = reg
conditional = {}
for i in exp.instructions:
name = i.name
qubits = []
params = getattr(i, "params", [])
try:
for qubit in i.qubits:
qubit_label = exp.header.qubit_labels[qubit]
qubits.append(qreg_dict[qubit_label[0]][qubit_label[1]])
except Exception: # pylint: disable=broad-except
pass
clbits = []
try:
for clbit in i.memory:
clbit_label = exp.header.clbit_labels[clbit]
clbits.append(creg_dict[clbit_label[0]][clbit_label[1]])
except Exception: # pylint: disable=broad-except
pass
if hasattr(circuit, name):
instr_method = getattr(circuit, name)
if i.name in ["snapshot"]:
_inst = instr_method(
i.label, snapshot_type=i.snapshot_type, qubits=qubits, params=params
)
elif i.name == "initialize":
_inst = instr_method(params, qubits)
elif i.name == "isometry":
_inst = instr_method(*params, qubits, clbits)
elif i.name in ["mcx", "mcu1", "mcp"]:
_inst = instr_method(*params, qubits[:-1], qubits[-1], *clbits)
else:
_inst = instr_method(*params, *qubits, *clbits)
elif name == "bfunc":
conditional["value"] = int(i.val, 16)
full_bit_size = sum(creg_dict[x].size for x in creg_dict)
mask_map = {}
raw_map = {}
raw = []
for creg in creg_dict:
size = creg_dict[creg].size
reg_raw = [1] * size
if not raw:
raw = reg_raw
else:
for pos, val in enumerate(raw):
if val == 1:
raw[pos] = 0
raw = reg_raw + raw
mask = [0] * (full_bit_size - len(raw)) + raw
raw_map[creg] = mask
mask_map[int("".join(str(x) for x in mask), 2)] = creg
creg = mask_map[int(i.mask, 16)]
conditional["register"] = creg_dict[creg]
val = int(i.val, 16)
mask = raw_map[creg]
for j in reversed(mask):
if j == 0:
val = val >> 1
else:
conditional["value"] = val
break
else:
_inst = temp_opaque_instruction = Instruction(
name=name, num_qubits=len(qubits), num_clbits=len(clbits), params=params
)
circuit.append(temp_opaque_instruction, qubits, clbits)
if conditional and name != "bfunc":
_inst.c_if(conditional["register"], conditional["value"])
conditional = {}
pulse_lib = qobj.config.pulse_library if hasattr(qobj.config, "pulse_library") else []
parametric_pulses = (
qobj.config.parametric_pulses if hasattr(qobj.config, "parametric_pulses") else []
)
# The dict update method did not work here; could investigate in the future
if hasattr(qobj.config, "calibrations"):
circuit.calibrations = dict(
**circuit.calibrations, **_qobj_to_circuit_cals(qobj, pulse_lib, parametric_pulses)
)
if hasattr(exp.config, "calibrations"):
circuit.calibrations = dict(
**circuit.calibrations, **_qobj_to_circuit_cals(exp, pulse_lib, parametric_pulses)
)
circuits.append(circuit)
return circuits
def _experiments_to_circuits(qobj):
"""Return a list of QuantumCircuit object(s) from a qobj
Args:
qobj (Qobj): The Qobj object to convert to QuantumCircuits
Returns:
list: A list of QuantumCircuit objects from the qobj
"""
if qobj.experiments:
circuits = []
for x in qobj.experiments:
quantum_registers = [
QuantumRegister(i[1], name=i[0]) for i in x.header.qreg_sizes
]
classical_registers = [
ClassicalRegister(i[1], name=i[0]) for i in x.header.creg_sizes
]
circuit = QuantumCircuit(*quantum_registers,
*classical_registers,
name=x.header.name)
qreg_dict = {}
creg_dict = {}
for reg in quantum_registers:
qreg_dict[reg.name] = reg
for reg in classical_registers:
creg_dict[reg.name] = reg
for i in x.instructions:
name = i.name
if i.name == 'id':
name = 'iden'
qubits = []
params = getattr(i, 'params', [])
try:
for qubit in i.qubits:
qubit_label = x.header.qubit_labels[qubit]
qubits.append(
qreg_dict[qubit_label[0]][qubit_label[1]])
except Exception: # pylint: disable=broad-except
pass
clbits = []
try:
for clbit in i.memory:
clbit_label = x.header.clbit_labels[clbit]
clbits.append(
creg_dict[clbit_label[0]][clbit_label[1]])
except Exception: # pylint: disable=broad-except
pass
if hasattr(circuit, name):
instr_method = getattr(circuit, name)
if i.name in ['snapshot']:
instr_method(i.label,
snapshot_type=i.snapshot_type,
qubits=qubits,
params=params)
elif i.name == 'initialize':
instr_method(params, qubits)
else:
instr_method(*params, *qubits, *clbits)
else:
temp_opaque_instruction = Instruction(
name=name,
num_qubits=len(qubits),
num_clbits=len(clbits),
params=params)
circuit.append(temp_opaque_instruction, qubits, clbits)
circuits.append(circuit)
return circuits
return None
def run(self, dag):
"""Return a new circuit that has been optimized."""
runs = dag.collect_runs(["u1", "u2", "u3", "id"])
for run in runs:
run_qarg = dag.node(run[0])["qargs"][0]
right_name = "u1"
right_parameters = (0, 0, 0) # (theta, phi, lambda)
for current_node in run:
node = dag.node(current_node)
left_name = node["name"]
if (node["condition"] is not None or len(node["qargs"]) != 1
or node["qargs"][0] != run_qarg
or left_name not in ["u1", "u2", "u3", "id"]):
raise MapperError("internal error")
if left_name == "u1":
left_parameters = (0, 0, node["op"].params[0])
elif left_name == "u2":
left_parameters = (np.pi / 2, node["op"].params[0],
node["op"].params[1])
elif left_name == "u3":
left_parameters = tuple(node["op"].params)
else:
left_name = "u1" # replace id with u1
left_parameters = (0, 0, 0)
# If there are any sympy objects coming from the gate convert
# to numpy.
left_parameters = tuple([float(x) for x in left_parameters])
# Compose gates
name_tuple = (left_name, right_name)
if name_tuple == ("u1", "u1"):
# u1(lambda1) * u1(lambda2) = u1(lambda1 + lambda2)
right_parameters = (0, 0, right_parameters[2] +
left_parameters[2])
elif name_tuple == ("u1", "u2"):
# u1(lambda1) * u2(phi2, lambda2) = u2(phi2 + lambda1, lambda2)
right_parameters = (np.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 = (np.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 = (np.pi - left_parameters[2] -
right_parameters[1],
left_parameters[1] + np.pi / 2,
right_parameters[2] + np.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
right_parameters = Optimize1qGates.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 np.mod(right_parameters[0], (2 * np.pi)) == 0 \
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 np.mod((right_parameters[0] - np.pi / 2),
(2 * np.pi)) == 0:
right_name = "u2"
right_parameters = (np.pi / 2, right_parameters[1],
right_parameters[2] +
(right_parameters[0] - np.pi / 2))
# theta = -pi/2 + 2*k*pi
if np.mod((right_parameters[0] + np.pi / 2),
(2 * np.pi)) == 0:
right_name = "u2"
right_parameters = (np.pi / 2,
right_parameters[1] + np.pi,
right_parameters[2] - np.pi +
(right_parameters[0] + np.pi / 2))
# u1 and lambda is 0 mod 2*pi so gate is nop (up to a global phase)
if right_name == "u1" and np.mod(right_parameters[2],
(2 * np.pi)) == 0:
right_name = "nop"
# Replace the data of the first node in the run
new_op = Instruction("", [], [], [])
if right_name == "u1":
new_op = U1Gate(right_parameters[2], run_qarg)
if right_name == "u2":
new_op = U2Gate(right_parameters[1], right_parameters[2],
run_qarg)
if right_name == "u3":
new_op = U3Gate(*right_parameters, run_qarg)
dag.node(run[0])['name'] = right_name
dag.node(run[0])['op'] = new_op
# Delete the other nodes in the run
for current_node in run[1:]:
dag._remove_op_node(current_node)
if right_name == "nop":
dag._remove_op_node(run[0])
return dag
def _experiments_to_circuits(qobj):
"""Return a list of QuantumCircuit object(s) from a qobj.
Args:
qobj (Qobj): The Qobj object to convert to QuantumCircuits
Returns:
list: A list of QuantumCircuit objects from the qobj
"""
if qobj.experiments:
circuits = []
for x in qobj.experiments:
quantum_registers = [
QuantumRegister(i[1], name=i[0]) for i in x.header.qreg_sizes
]
classical_registers = [
ClassicalRegister(i[1], name=i[0]) for i in x.header.creg_sizes
]
circuit = QuantumCircuit(*quantum_registers,
*classical_registers,
name=x.header.name)
qreg_dict = collections.OrderedDict()
creg_dict = collections.OrderedDict()
for reg in quantum_registers:
qreg_dict[reg.name] = reg
for reg in classical_registers:
creg_dict[reg.name] = reg
conditional = {}
for i in x.instructions:
name = i.name
qubits = []
params = getattr(i, 'params', [])
try:
for qubit in i.qubits:
qubit_label = x.header.qubit_labels[qubit]
qubits.append(
qreg_dict[qubit_label[0]][qubit_label[1]])
except Exception: # pylint: disable=broad-except
pass
clbits = []
try:
for clbit in i.memory:
clbit_label = x.header.clbit_labels[clbit]
clbits.append(
creg_dict[clbit_label[0]][clbit_label[1]])
except Exception: # pylint: disable=broad-except
pass
if hasattr(circuit, name):
instr_method = getattr(circuit, name)
if i.name in ['snapshot']:
_inst = instr_method(i.label,
snapshot_type=i.snapshot_type,
qubits=qubits,
params=params)
elif i.name == 'initialize':
_inst = instr_method(params, qubits)
elif i.name == 'isometry':
_inst = instr_method(*params, qubits, clbits)
else:
_inst = instr_method(*params, *qubits, *clbits)
elif name == 'bfunc':
conditional['value'] = int(i.val, 16)
full_bit_size = sum([creg_dict[x].size for x in creg_dict])
mask_map = {}
raw_map = {}
raw = []
for creg in creg_dict:
size = creg_dict[creg].size
reg_raw = [1] * size
if not raw:
raw = reg_raw
else:
for pos, val in enumerate(raw):
if val == 1:
raw[pos] = 0
raw = reg_raw + raw
mask = [0] * (full_bit_size - len(raw)) + raw
raw_map[creg] = mask
mask_map[int("".join(str(x) for x in mask), 2)] = creg
creg = mask_map[int(i.mask, 16)]
conditional['register'] = creg_dict[creg]
val = int(i.val, 16)
mask = raw_map[creg]
for j in reversed(mask):
if j == 0:
val = val >> 1
else:
conditional['value'] = val
break
else:
_inst = temp_opaque_instruction = Instruction(
name=name,
num_qubits=len(qubits),
num_clbits=len(clbits),
params=params)
circuit.append(temp_opaque_instruction, qubits, clbits)
if conditional and name != 'bfunc':
_inst.c_if(conditional['register'], conditional['value'])
conditional = {}
circuits.append(circuit)
return circuits
return None
def optimize_1q_gates(circuit):
"""Simplify runs of single qubit gates in the QX basis.
Return a new circuit that has been optimized.
"""
from qiskit.transpiler.passes.mapping.unroller import Unroller
qx_basis = ["u1", "u2", "u3", "cx", "id"]
unrolled = Unroller(qx_basis).run(circuit)
runs = unrolled.collect_runs(["u1", "u2", "u3", "id"])
for run in runs:
run_qarg = 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]
left_name = nd["name"]
if (nd["condition"] is not None or len(nd["qargs"]) != 1
or nd["qargs"][0] != run_qarg
or left_name not in ["u1", "u2", "u3", "id"]):
raise MapperError("internal error")
if left_name == "u1":
left_parameters = (N(0), N(0), nd["op"].param[0])
elif left_name == "u2":
left_parameters = (sympy.pi / 2, nd["op"].param[0],
nd["op"].param[1])
elif left_name == "u3":
left_parameters = tuple(nd["op"].param)
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_op = Instruction("", [], [], [])
if right_name == "u1":
new_op = U1Gate(right_parameters[2], run_qarg)
if right_name == "u2":
new_op = U2Gate(right_parameters[1], right_parameters[2], run_qarg)
if right_name == "u3":
new_op = U3Gate(*right_parameters, run_qarg)
nx.set_node_attributes(unrolled.multi_graph,
name='name',
values={run[0]: right_name})
nx.set_node_attributes(unrolled.multi_graph,
name='op',
values={run[0]: new_op})
# 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
