def test_automatic_deallocation_of_qubit_in_uncompute(): # Test that automatic uncomputation deallocates qubit # which was created during compute context. backend = DummyEngine(save_commands=True) eng = MainEngine(backend=backend, engine_list=[DummyEngine()]) with _compute.Compute(eng): ancilla = eng.allocate_qubit() assert ancilla[0].id != -1 Rx(0.6) | ancilla # Test that ancilla qubit has been register in MainEngine.active_qubits assert ancilla[0] in eng.active_qubits _compute.Uncompute(eng) # Test that ancilla id has been set to -1 assert ancilla[0].id == -1 # Test that ancilla is not anymore in active qubits assert not ancilla[0] in eng.active_qubits assert backend.received_commands[1].gate == Rx(0.6) assert backend.received_commands[2].gate == Rx(-0.6)
def test_toffoli_size_of_increment():
backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=backend,
engine_list=[
AutoReplacerEx(
DecompositionRuleSet(modules=[
multi_not_rules,
increment_rules,
addition_rules,
swap2cnot,
])),
LimitedCapabilityEngine(allow_toffoli=True),
])
controls = eng.allocate_qureg(40)
target = eng.allocate_qureg(35)
_ = eng.allocate_qureg(2)
Increment & controls | target
assert 1000 < len(backend.received_commands) < 10000
def test_simulator_kqubit_exception(sim):
m1 = Rx(0.3).matrix
m2 = Rx(0.8).matrix
m3 = Ry(0.1).matrix
m4 = Rz(0.9).matrix.dot(Ry(-0.1).matrix)
m = numpy.kron(m4, numpy.kron(m3, numpy.kron(m2, m1)))
class KQubitGate(BasicGate):
@property
def matrix(self):
return m
eng = MainEngine(sim, [])
qureg = eng.allocate_qureg(3)
with pytest.raises(Exception):
KQubitGate() | qureg
with pytest.raises(Exception):
H | qureg
def _expectation_value(
self,
circuit: Circuit,
hamiltonian: projectq.ops.QubitOperator,
valid_check: bool = True,
) -> complex:
if valid_check and not self.valid_circuit(circuit):
raise ValueError(
"Circuits do not satisfy all required predicates for this backend"
)
sim = Simulator()
fwd = ForwarderEngine(sim)
eng = MainEngine(backend=sim, engine_list=[fwd])
qureg = eng.allocate_qureg(circuit.n_qubits)
tk_to_projectq(eng, qureg, circuit)
eng.flush()
energy = eng.backend.get_expectation_value(hamiltonian, qureg)
return complex(energy)
def test_recognize_individual_terms():
saving_backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=saving_backend, engine_list=[])
wavefunction = eng.allocate_qureg(5)
op1 = QubitOperator("X1 Y2", 0.5)
op2 = QubitOperator("Y2 X4", -0.5)
op3 = QubitOperator("X2", 1.0)
TimeEvolution(1.0, op1 + op2) | wavefunction
TimeEvolution(1.0, op2) | wavefunction
TimeEvolution(1.0, op3) | wavefunction
cmd1 = saving_backend.received_commands[5]
cmd2 = saving_backend.received_commands[6]
cmd3 = saving_backend.received_commands[7]
assert not te.rule_individual_terms.gate_recognizer(cmd1)
assert te.rule_individual_terms.gate_recognizer(cmd2)
assert te.rule_individual_terms.gate_recognizer(cmd3)
def test_toffoli_size_of_addition():
backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=backend,
engine_list=[
AutoReplacerEx(
DecompositionRuleSet(modules=[
addition_rules,
increment_rules,
multi_not_rules,
swap2cnot,
])),
LimitedCapabilityEngine(allow_toffoli=True),
])
src = eng.allocate_qureg(50)
dst = eng.allocate_qureg(100)
Add | (src, dst)
assert 5000 < len(backend.received_commands) < 7000
def test_quantumsubtraction():
sim = Simulator()
eng = MainEngine(
sim, [AutoReplacer(rule_set),
InstructionFilter(no_math_emulation)])
qureg_a = eng.allocate_qureg(5)
qureg_b = eng.allocate_qureg(5)
init(eng, qureg_a, 5)
init(eng, qureg_b, 7)
SubtractQuantum() | (qureg_a, qureg_b)
assert 1. == pytest.approx(
eng.backend.get_probability([1, 0, 1, 0, 0], qureg_a))
assert 1. == pytest.approx(
eng.backend.get_probability([0, 1, 0, 0, 0], qureg_b))
def test_phase_majority_from_python():
dormouse = pytest.importorskip('dormouse')
def maj(a, b, c):
return (a and b) or (a and c) or (b and c) # pragma: no cover
sim = Simulator()
main_engine = MainEngine(sim)
qureg = main_engine.allocate_qureg(3)
All(H) | qureg
PhaseOracle(maj) | qureg
main_engine.flush()
assert np.array_equal(np.sign(sim.cheat()[1]),
[1., 1., 1., -1., 1., -1., -1., -1.])
All(Measure) | qureg
def _initialize_register(num_bit, mode='simulator'):
'''
use an engine instead of current one.
'''
import projectq.setups.default
# create a main compiler engine with a specific backend:
if mode == 'graphical':
backend = CircuitDrawer()
elif mode == 'simulator':
backend = Simulator()
else:
raise
eng = MainEngine(backend)
# initialize register
qureg = eng.allocate_qureg(num_bit)
return qureg
def test_or_one_qubit():
saving_backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=saving_backend, engine_list=[])
qubit = eng.allocate_qubit()
hamiltonian = QubitOperator("Z0", 2)
te.TimeEvolution(2.1, hamiltonian) | qubit[0]
te.TimeEvolution(3, hamiltonian) | (qubit[0],)
eng.flush()
cmd1 = saving_backend.received_commands[1]
assert cmd1.gate.hamiltonian.isclose(hamiltonian)
assert cmd1.gate.time == pytest.approx(2.1)
assert len(cmd1.qubits) == 1 and len(cmd1.qubits[0]) == 1
assert cmd1.qubits[0][0].id == qubit[0].id
cmd2 = saving_backend.received_commands[2]
assert cmd2.gate.hamiltonian.isclose(hamiltonian)
assert cmd2.gate.time == pytest.approx(3)
assert len(cmd2.qubits) == 1 and len(cmd2.qubits[0]) == 1
assert cmd2.qubits[0][0].id == qubit[0].id
def test_ffft_2modes_properly_applied(self):
eng_ft_0 = MainEngine()
reg_ft_0 = eng_ft_0.allocate_qureg(2)
eng_ffft_recursive = MainEngine()
reg_ffft_recursive = eng_ffft_recursive.allocate_qureg(2)
ffft(eng_ffft_recursive, reg_ffft_recursive, 2)
fourier_transform_0(reg_ft_0, 0, 1)
eng_ffft_recursive.flush()
eng_ft_0.flush()
All(Measure) | reg_ffft_recursive
All(Measure) | reg_ft_0
self.assertTrue(numpy.allclose(
ordered_wavefunction(eng_ffft_recursive),
ordered_wavefunction(eng_ft_0)))
def test_toffoli_size_of_bit_rotate():
rec = DummyEngine(save_commands=True)
eng = MainEngine(backend=rec,
engine_list=[
AutoReplacerEx(
DecompositionRuleSet(modules=[
swap2cnot, multi_not_rules,
reverse_bits_rules, rotate_bits_rules
])),
LimitedCapabilityEngine(allow_toffoli=True),
])
controls = eng.allocate_qureg(50)
target = eng.allocate_qureg(100)
RotateBitsGate(-3) & controls | target
RotateBitsGate(+1) & controls | target[1:]
assert 500 < len(rec.received_commands) < 5000
def run(self,
circuit: Circuit,
shots: int,
fit_to_constraints=True) -> np.ndarray:
state = self.get_state(circuit, fit_to_constraints)
fwd = ForwarderEngine(self._backend)
eng = MainEngine(backend=self._backend, engine_list=[fwd])
qb_results = []
qureg = eng.allocate_qureg(circuit.n_qubits)
for _ in range(shots):
self._backend.set_wavefunction(state, qureg)
All(Measure) | qureg
eng.flush()
results = (list(map(int, qureg)))
qb_results.append(results)
return np.asarray(qb_results)
def test_set_explicit_initial_state(self):
"""
This shows how to set the initial state of the qubits in a circuit.
"""
initial_statevector = [
complex(0, 0), complex(0, 0), complex(1, 0), complex(0, 0),
complex(0, 0), complex(0, 0), complex(0, 0), complex(0, 0)
]
engine = MainEngine()
qubits = engine.allocate_qureg(3)
# Set the initial state to 2, which is |010> (this can also be an entire state vector if you need to get fine-grained
# or set up superpositions)
engine.flush()
engine.backend.set_wavefunction(initial_statevector, qubits)
print(engine.backend.cheat())
def test_auto_replacer_decomposition_chooser(fixture_gate_filter):
# Supply a decomposition chooser which always chooses last rule.
def test_decomp_chooser(cmd, decomposition_list):
return decomposition_list[-1]
backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=backend,
engine_list=[
_replacer.AutoReplacer(rule_set, test_decomp_chooser),
fixture_gate_filter
])
assert len(rule_set.decompositions[TestGate.__class__.__name__]) == 2
assert len(backend.received_commands) == 0
qb = eng.allocate_qubit()
TestGate | qb
eng.flush()
assert len(backend.received_commands) == 3
assert backend.received_commands[1].gate == H
def check_quantum_permutation_circuit(register_size,
permutation_func,
actions,
engine_list=()):
"""
Args:
register_size (int):
permutation_func (function(register_sizes: tuple[int],
register_vals: tuple[int]) : tuple[int]):
actions (function(eng: MainEngine, registers: list[Qureg])):
engine_list (list[projectq.cengines.BasicEngine]):
"""
sim = Simulator()
rec = DummyEngine(save_commands=True)
eng = MainEngine(backend=sim, engine_list=list(engine_list) + [rec])
reg = eng.allocate_qureg(register_size)
All(H) | reg
for i in range(len(reg)):
Rz(math.pi / 2**i) | reg[i]
pre_state = np.array(sim.cheat()[1])
# Simulate.
rec.received_commands = []
actions(eng, [reg])
actions = list(rec.received_commands)
post_state = np.array(sim.cheat()[1])
for q in reg:
Measure | q
denom = math.sqrt(len(pre_state))
pre_state *= denom
post_state *= denom
for i in range(len(pre_state)):
j = permutation_func([register_size], [i]) & ((1 << len(reg)) - 1)
if not (abs(post_state[j] - pre_state[i]) < 0.000000001):
print(commands_to_ascii_circuit(actions))
print("Input", i)
print("Expected Output", j)
print("Input Amp at " + str(i), pre_state[i])
print("Actual Amp at " + str(j), post_state[j])
assert abs(post_state[j] - pre_state[i]) < 0.000000001
def test_auto_replacer_use_inverse_decomposition():
# Check that if there is no decomposition for the gate, that
# AutoReplacer runs the decomposition for the inverse gate in reverse
# Create test gate and inverse
class NoMagicGate(BasicGate):
pass
class MagicGate(BasicGate):
def get_inverse(self):
return NoMagicGate()
def decompose_no_magic_gate(cmd):
qb = cmd.qubits
Rx(0.6) | qb
H | qb
def recognize_no_magic_gate(cmd):
return True
rule_set.add_decomposition_rule(
DecompositionRule(NoMagicGate, decompose_no_magic_gate,
recognize_no_magic_gate))
def magic_filter(self, cmd):
if cmd.gate == MagicGate():
return False
return True
backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=backend,
engine_list=[
_replacer.AutoReplacer(rule_set),
_replacer.InstructionFilter(magic_filter)
])
assert len(backend.received_commands) == 0
qb = eng.allocate_qubit()
MagicGate() | qb
eng.flush()
for cmd in backend.received_commands:
print(cmd)
assert len(backend.received_commands) == 4
assert backend.received_commands[1].gate == H
assert backend.received_commands[2].gate == Rx(-0.6)
def test_simulator_expectation(sim, mapper):
engine_list = []
if mapper is not None:
engine_list.append(mapper)
eng = MainEngine(sim, engine_list=engine_list)
qureg = eng.allocate_qureg(3)
op0 = QubitOperator('Z0')
expectation = sim.get_expectation_value(op0, qureg)
assert 1. == pytest.approx(expectation)
X | qureg[0]
expectation = sim.get_expectation_value(op0, qureg)
assert -1. == pytest.approx(expectation)
H | qureg[0]
op1 = QubitOperator('X0')
expectation = sim.get_expectation_value(op1, qureg)
assert -1. == pytest.approx(expectation)
Z | qureg[0]
expectation = sim.get_expectation_value(op1, qureg)
assert 1. == pytest.approx(expectation)
X | qureg[0]
S | qureg[0]
Z | qureg[0]
X | qureg[0]
op2 = QubitOperator('Y0')
expectation = sim.get_expectation_value(op2, qureg)
assert 1. == pytest.approx(expectation)
Z | qureg[0]
expectation = sim.get_expectation_value(op2, qureg)
assert -1. == pytest.approx(expectation)
op_sum = QubitOperator('Y0 X1 Z2') + QubitOperator('X1')
H | qureg[1]
X | qureg[2]
expectation = sim.get_expectation_value(op_sum, qureg)
assert 2. == pytest.approx(expectation)
op_sum = QubitOperator('Y0 X1 Z2') + QubitOperator('X1')
X | qureg[2]
expectation = sim.get_expectation_value(op_sum, qureg)
assert 0. == pytest.approx(expectation)
op_id = .4 * QubitOperator(())
expectation = sim.get_expectation_value(op_id, qureg)
assert .4 == pytest.approx(expectation)
def test_simulator_functional_entangle(sim):
eng = MainEngine(sim, [])
qubits = eng.allocate_qureg(5)
# entangle all qubits:
H | qubits[0]
for qb in qubits[1:]:
CNOT | (qubits[0], qb)
# check the state vector:
assert .5 == pytest.approx(abs(sim.cheat()[1][0])**2)
assert .5 == pytest.approx(abs(sim.cheat()[1][31])**2)
for i in range(1, 31):
assert 0. == pytest.approx(abs(sim.cheat()[1][i]))
# unentangle all except the first 2
for qb in qubits[2:]:
CNOT | (qubits[0], qb)
# entangle using Toffolis
for qb in qubits[2:]:
Toffoli | (qubits[0], qubits[1], qb)
# check the state vector:
assert .5 == pytest.approx(abs(sim.cheat()[1][0])**2)
assert .5 == pytest.approx(abs(sim.cheat()[1][31])**2)
for i in range(1, 31):
assert 0. == pytest.approx(abs(sim.cheat()[1][i]))
# uncompute using multi-controlled NOTs
with Control(eng, qubits[0:-1]):
X | qubits[-1]
with Control(eng, qubits[0:-2]):
X | qubits[-2]
with Control(eng, qubits[0:-3]):
X | qubits[-3]
CNOT | (qubits[0], qubits[1])
H | qubits[0]
# check the state vector:
assert 1. == pytest.approx(abs(sim.cheat()[1][0])**2)
for i in range(1, 32):
assert 0. == pytest.approx(abs(sim.cheat()[1][i]))
Measure | qubits
def test_8mode_ffft_with_external_swaps_on_single_logical_state(self):
n_qubits = 8
grid = Grid(dimensions=1, length=n_qubits, scale=1.0)
eng = MainEngine()
register = eng.allocate_qureg(n_qubits)
state_index = 157
prepare_logical_state(register, state_index)
ffft(eng, register, n_qubits)
Ph(3 * numpy.pi / 4) | register[0]
eng.flush()
wvfn = ordered_wavefunction(eng)
fermion_operator = prepare_integer_fermion_operator(state_index)
# Swap 01234567 to 45670123 for fourier_transform. Additionally,
# the FFFT's ordering is 04261537, so swap 04261537 to 01234567,
# and then 01234567 to 45670123.
swap_mode_list = ([1, 3, 5, 2, 4, 1, 3, 5] +
[3, 2, 4, 1, 3, 5, 0, 2, 4, 6, 1, 3, 5, 2, 4, 3])
for mode in swap_mode_list:
fermion_operator = normal_ordered(fermion_operator)
fermion_operator = swap_adjacent_fermionic_modes(
fermion_operator, mode)
ffft_result = fourier_transform(fermion_operator, grid, spinless=True)
ffft_result = normal_ordered(ffft_result)
# After the FFFT, swap 45670123 -> 01234567.
swap_mode_list = [3, 2, 4, 1, 3, 5, 0, 2, 4, 6, 1, 3, 5, 2, 4, 3]
for mode in swap_mode_list:
ffft_result = swap_adjacent_fermionic_modes(ffft_result, mode)
converted_wvfn = numpy.zeros(2**n_qubits, dtype=complex)
for term in ffft_result.terms:
index = sum(2**site[0] for site in term)
converted_wvfn[index] = ffft_result.terms[term]
All(Measure) | register
self.assertTrue(numpy.allclose(wvfn, converted_wvfn))
def test_backend_get_probabilities_method(matplotlib_setup):
class MyBackend(BasicEngine):
def get_probabilities(self, qureg):
return {'000': 0.5, '111': 0.5}
def is_available(self, cmd):
return True
def receive(self, command_list):
for cmd in command_list:
if not isinstance(cmd.gate, FlushGate):
assert isinstance(cmd.gate, AllocateQubitGate)
eng = MainEngine(backend=MyBackend(), verbose=True)
qureg = eng.allocate_qureg(3)
eng.flush()
_, _, prob = histogram(eng.backend, qureg)
assert prob['000'] == 0.5
assert prob['111'] == 0.5
def test_recognize_correct_gates():
saving_backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=saving_backend)
qubit = eng.allocate_qubit()
ctrl_qubit = eng.allocate_qubit()
eng.flush()
Rx(0.3) | qubit
with Control(eng, ctrl_qubit):
Rx(0.4) | qubit
eng.flush(deallocate_qubits=True)
assert rx2rz._recognize_RxNoCtrl(saving_backend.received_commands[3])
assert not rx2rz._recognize_RxNoCtrl(saving_backend.received_commands[4])
def test_4mode_ffft_with_external_swaps_all_logical_states(self):
n_qubits = 4
grid = Grid(dimensions=1, length=n_qubits, scale=1.0)
for i in range(2**n_qubits):
eng = MainEngine()
register = eng.allocate_qureg(n_qubits)
prepare_logical_state(register, i)
ffft(eng, register, n_qubits)
Ph(3 * numpy.pi / 4) | register[0]
eng.flush()
wvfn = ordered_wavefunction(eng)
fermion_operator = prepare_integer_fermion_operator(i)
# Reorder the modes for correct input to the FFFT.
# Swap 0123 to 2301 for fourier_transform. Additionally, the
# FFFT's ordering is 0213, so connect 0213 -> 0123 -> 2301.
swap_mode_list = [1] + [1, 0, 2, 1]
for mode in swap_mode_list:
fermion_operator = normal_ordered(fermion_operator)
fermion_operator = swap_adjacent_fermionic_modes(
fermion_operator, mode)
ffft_result = fourier_transform(fermion_operator,
grid,
spinless=True)
ffft_result = normal_ordered(ffft_result)
swap_mode_list = [1, 0, 2, 1] # After FFFT, swap 2301 -> 0123
for mode in swap_mode_list:
ffft_result = swap_adjacent_fermionic_modes(ffft_result, mode)
converted_wvfn = numpy.zeros(2**n_qubits, dtype=complex)
for term in ffft_result.terms:
index = sum(2**site[0] for site in term)
converted_wvfn[index] = ffft_result.terms[term]
All(Measure) | register
self.assertTrue(numpy.allclose(wvfn, converted_wvfn))
def test_simulator_functional_measurement(sim):
eng = MainEngine(sim, [])
qubits = eng.allocate_qureg(5)
# entangle all qubits:
H | qubits[0]
for qb in qubits[1:]:
CNOT | (qubits[0], qb)
All(Measure) | qubits
bit_value_sum = sum([int(qubit) for qubit in qubits])
assert bit_value_sum == 0 or bit_value_sum == 5
qb1 = WeakQubitRef(engine=eng, idx=qubits[0].id)
qb2 = WeakQubitRef(engine=eng, idx=qubits[1].id)
with pytest.raises(ValueError):
eng.backend._handle(
Command(engine=eng, gate=Measure, qubits=([qb1], ),
controls=[qb2]))
def test_modmultiplier(): sim = Simulator() eng = MainEngine(sim, [AutoReplacer(), InstructionFilter(no_math_emulation)]) qureg = eng.allocate_qureg(4) init(eng, qureg, 4) MultiplyByConstantModN(3, 7) | qureg assert 1. == pytest.approx(abs(sim.cheat()[1][5])) init(eng, qureg, 5) # reset init(eng, qureg, 7) MultiplyByConstantModN(4, 13) | qureg assert 1. == pytest.approx(abs(sim.cheat()[1][2])) Measure | qureg
def test_auto_replacer_searches_parent_class_for_rule():
class DerivedSomeGate(SomeGateClass):
pass
def test_gate_filter_func(self, cmd):
if (cmd.gate == X or cmd.gate == H
or isinstance(cmd.gate, ClassicalInstructionGate)):
return True
return False
i_filter = _replacer.InstructionFilter(test_gate_filter_func)
backend = DummyEngine(save_commands=True)
eng = MainEngine(backend=backend,
engine_list=[_replacer.AutoReplacer(rule_set), i_filter])
qb = eng.allocate_qubit()
DerivedSomeGate() | qb
eng.flush()
received_gate = backend.received_commands[1].gate
assert received_gate == X or received_gate == H
def test_modadder(): sim = Simulator() eng = MainEngine(sim, [AutoReplacer(), InstructionFilter(no_math_emulation)]) qureg = eng.allocate_qureg(4) init(eng, qureg, 4) AddConstantModN(3, 6) | qureg assert 1. == pytest.approx(abs(sim.cheat()[1][1])) init(eng, qureg, 1) # reset init(eng, qureg, 7) AddConstantModN(10, 13) | qureg assert 1. == pytest.approx(abs(sim.cheat()[1][4])) Measure | qureg
def test_qubit_lines_classicalvsquantum1():
drawer = _drawer.CircuitDrawer()
eng = MainEngine(drawer, [])
old_tolatex = _drawer.to_latex
_drawer.to_latex = lambda x: x
qubit1 = eng.allocate_qubit()
H | qubit1
Measure | qubit1
X | qubit1
circuit_lines = drawer.get_latex()
_drawer.to_latex = old_tolatex
settings = _to_latex.get_default_settings()
code = _to_latex._body(circuit_lines, settings)
assert code.count("edge[") == 4
def test_qureg_measure_exception():
eng = MainEngine(backend=DummyEngine(), engine_list=[DummyEngine()])
qureg = _qubit.Qureg()
for qubit_id in [0, 1]:
qubit = _qubit.Qubit(eng, qubit_id)
qureg.append(qubit)
with pytest.raises(Exception):
qureg.__bool__()
with pytest.raises(Exception):
qureg.__int__()
def test_qubit(matplotlib_setup):
sim = Simulator()
eng = MainEngine(sim)
qubit = eng.allocate_qubit()
eng.flush()
_, _, prob = histogram(sim, qubit)
assert prob["0"] == pytest.approx(1)
assert prob["1"] == pytest.approx(0)
H | qubit
eng.flush()
_, _, prob = histogram(sim, qubit)
assert prob["0"] == pytest.approx(0.5)
Measure | qubit
eng.flush()
_, _, prob = histogram(sim, qubit)
assert prob["0"] == pytest.approx(1) or prob["1"] == pytest.approx(1)
def run_circuit(self, circuit):
"""Run a circuit and return a single Result.
Args:
circuit (dict): JSON circuit from qobj circuits list
Returns:
dict: A dictionary of results which looks something like::
{
"data":
{ #### DATA CAN BE A DIFFERENT DICTIONARY FOR EACH BACKEND ####
"counts": {'00000': XXXX, '00001': XXXXX},
"time" : xx.xxxxxxxx
},
"status": --status (string)--
}
Raises:
SimulatorError: if an error occurred.
"""
# pylint: disable=expression-not-assigned,pointless-statement
ccircuit = circuit['compiled_circuit']
self._number_of_qubits = ccircuit['header']['number_of_qubits']
self._number_of_clbits = ccircuit['header']['number_of_clbits']
self._statevector = 0
self._classical_state = 0
cl_reg_index = [] # starting bit index of classical register
cl_reg_nbits = [] # number of bits in classical register
clbit_index = 0
qobj_quregs = OrderedDict(_get_register_specs(
ccircuit['header']['qubit_labels']))
eng = MainEngine(backend=self._sim)
for cl_reg in ccircuit['header']['clbit_labels']:
cl_reg_nbits.append(cl_reg[1])
cl_reg_index.append(clbit_index)
clbit_index += cl_reg[1]
# let circuit seed override qobj default
if 'config' in circuit:
if 'seed' in circuit['config']:
if circuit['config']['seed'] is not None:
self._sim._simulator = CppSim(circuit['config']['seed'])
outcomes = []
start = time.time()
for _ in range(self._shots):
self._statevector = np.zeros(1 << self._number_of_qubits,
dtype=complex)
self._statevector[0] = 1
# initialize starting state
self._classical_state = 0
unmeasured_qubits = list(range(self._number_of_qubits))
projq_qureg_dict = OrderedDict(((key, eng.allocate_qureg(size))
for key, size in
qobj_quregs.items()))
qureg = [qubit for sublist in projq_qureg_dict.values()
for qubit in sublist]
# Do each operation in this shot
for operation in ccircuit['operations']:
if 'conditional' in operation:
mask = int(operation['conditional']['mask'], 16)
if mask > 0:
value = self._classical_state & mask
while (mask & 0x1) == 0:
mask >>= 1
value >>= 1
if value != int(operation['conditional']['val'], 16):
continue
# Check if single gate
if operation['name'] in ['U', 'u3']:
params = operation['params']
qubit = qureg[operation['qubits'][0]]
Rz(params[2]) | qubit
Ry(params[0]) | qubit
Rz(params[1]) | qubit
elif operation['name'] in ['u1']:
params = operation['params']
qubit = qureg[operation['qubits'][0]]
Rz(params[0]) | qubit
elif operation['name'] in ['u2']:
params = operation['params']
qubit = qureg[operation['qubits'][0]]
Rz(params[1] - np.pi/2) | qubit
Rx(np.pi/2) | qubit
Rz(params[0] + np.pi/2) | qubit
elif operation['name'] == 't':
qubit = qureg[operation['qubits'][0]]
T | qubit
elif operation['name'] == 'h':
qubit = qureg[operation['qubits'][0]]
H | qubit
elif operation['name'] == 's':
qubit = qureg[operation['qubits'][0]]
S | qubit
elif operation['name'] in ['CX', 'cx']:
qubit0 = qureg[operation['qubits'][0]]
qubit1 = qureg[operation['qubits'][1]]
CX | (qubit0, qubit1)
elif operation['name'] in ['id', 'u0']:
pass
# Check if measure
elif operation['name'] == 'measure':
qubit_index = operation['qubits'][0]
qubit = qureg[qubit_index]
clbit = operation['clbits'][0]
Measure | qubit
bit = 1 << clbit
self._classical_state = (
self._classical_state & (~bit)) | (int(qubit)
<< clbit)
# check whether we already measured this qubit
if operation['qubits'][0] in unmeasured_qubits:
unmeasured_qubits.remove(operation['qubits'][0])
# Check if reset
elif operation['name'] == 'reset':
qubit = operation['qubits'][0]
raise SimulatorError('Reset operation not yet implemented '
'for ProjectQ C++ backend')
elif operation['name'] == 'barrier':
pass
else:
backend = self._configuration['name']
err_msg = '{0} encountered unrecognized operation "{1}"'
raise SimulatorError(err_msg.format(backend,
operation['name']))
for ind in unmeasured_qubits:
qubit = qureg[ind]
Measure | qubit
eng.flush()
# Turn classical_state (int) into bit string
state = format(self._classical_state, 'b')
outcomes.append(state.zfill(self._number_of_clbits))
# Return the results
counts = dict(Counter(outcomes))
data = {'counts': _format_result(
counts, cl_reg_index, cl_reg_nbits)}
if self._shots == 1:
# TODO: deprecated -- remove in v0.6
data['statevector'] = self._statevector
data['quantum_state'] = self._statevector
data['classical_state'] = self._classical_state
end = time.time()
return {'name': circuit['name'],
'seed': self._seed,
'shots': self._shots,
'data': data,
'status': 'DONE',
'success': True,
'time_taken': (end-start)}
# From http://dataespresso.com/en/2018/07/22/Tutorial-Generating-random-numbers-with-a-quantum-computer-Python/
from projectq.ops import H, Measure
from projectq import MainEngine
"""
This Function creates a new qubit,
applies a Hadamard gate to put it in superposition,
and then measures the qubit to get a random
1 or 0.
"""
def get_random_number(quantum_engine):
qubit = quantum_engine.allocate_qubit()
H | qubit
Measure | qubit
random_number = int(qubit)
return random_number
# This list is used to store our random numbers
random_numbers_list = []
# initialises a new quantum backend
quantum_engine = MainEngine()
# for loop to generate 10 random numbers
for i in range(10):
# calling the random number function and append the return to the list
random_numbers_list.append(get_random_number(quantum_engine))
# Flushes the quantum engine from memory
quantum_engine.flush()
print('Random numbers', random_numbers_list)
from projectq import MainEngine # import the main compiler engine
# import the operations we want to perform (Hadamard and measurement)
from projectq.ops import H, Measure
eng = MainEngine() # create a default compiler (the back-end is a simulator)
qubit = eng.allocate_qubit() # allocate 1 qubit
H | qubit # apply a Hadamard gate
Measure | qubit # measure the qubit
eng.flush() # flush all gates (and execute measurements)
print("Measured {}".format(int(qubit))) # output measurement result
