def test_validate_supported_quil_reset_qubit():
prog = Program(
RESET(2),
)
with pytest.raises(ValueError):
validate_supported_quil(prog)
assert not prog.is_supported_on_qpu()
def test_validate_supported_quil_measure_last():
prog = Program(
MEASURE(0),
H(0),
)
with pytest.raises(ValueError):
validate_supported_quil(prog)
assert not prog.is_supported_on_qpu()
def test_validate_supported_quil_multiple_measures():
prog = Program(
RESET(),
H(1),
Pragma('DELAY'),
MEASURE(1, None),
MEASURE(1, None)
)
with pytest.raises(ValueError):
validate_supported_quil(prog)
def run_and_measure(self, program: Program,
trials: int) -> Dict[int, np.ndarray]:
"""
Run the provided state preparation program and measure all qubits.
The returned data is a dictionary keyed by qubit index because qubits for a given
QuantumComputer may be non-contiguous and non-zero-indexed. To turn this dictionary
into a 2d numpy array of bitstrings, consider::
bitstrings = qc.run_and_measure(...)
bitstring_array = np.vstack([bitstrings[q] for q in qc.qubits()]).T
bitstring_array.shape # (trials, len(qc.qubits()))
.. note::
If the target :py:class:`QuantumComputer` is a noiseless :py:class:`QVM` then
only the qubits explicitly used in the program will be measured. Otherwise all
qubits will be measured. In some circumstances this can exhaust the memory
available to the simulator, and this may be manifested by the QVM failing to
respond or timeout.
.. note::
In contrast to :py:class:`QVMConnection.run_and_measure`, this method simulates
noise correctly for noisy QVMs. However, this method is slower for ``trials > 1``.
For faster noise-free simulation, consider
:py:class:`WavefunctionSimulator.run_and_measure`.
:param program: The state preparation program to run and then measure.
:param trials: The number of times to run the program.
:return: A dictionary keyed by qubit index where the corresponding value is a 1D array of
measured bits.
"""
program = program.copy()
validate_supported_quil(program)
ro = program.declare("ro", "BIT", len(self.qubits()))
measure_used = isinstance(self.qam,
QVM) and self.qam.noise_model is None
qubits_to_measure = set(
map(qubit_index, program.get_qubits()) if measure_used else self.
qubits())
for i, q in enumerate(qubits_to_measure):
program.inst(MEASURE(q, ro[i]))
program.wrap_in_numshots_loop(trials)
executable = self.compile(program)
bitstring_array = self.run(executable=executable)
bitstring_dict = {}
for i, q in enumerate(qubits_to_measure):
bitstring_dict[q] = bitstring_array[:, i]
for q in set(self.qubits()) - set(qubits_to_measure):
bitstring_dict[q] = np.zeros(trials)
return bitstring_dict
def run_and_measure(self, program: Program,
trials: int) -> Dict[int, np.ndarray]:
"""
Run the provided state preparation program and measure all qubits.
This will measure all the qubits on this QuantumComputer, not just qubits
that are used in the program.
The returned data is a dictionary keyed by qubit index because qubits for a given
QuantumComputer may be non-contiguous and non-zero-indexed. To turn this dictionary
into a 2d numpy array of bitstrings, consider::
bitstrings = qc.run_and_measure(...)
bitstring_array = np.vstack(bitstrings[q] for q in qc.qubits()).T
bitstring_array.shape # (trials, len(qc.qubits()))
.. note::
In contrast to :py:class:`QVMConnection.run_and_measure`, this method simulates
noise correctly for noisy QVMs. However, this method is slower for ``trials > 1``.
For faster noise-free simulation, consider
:py:class:`WavefunctionSimulator.run_and_measure`.
:param program: The state preparation program to run and then measure.
:param trials: The number of times to run the program.
:return: A dictionary keyed by qubit index where the corresponding value is a 1D array of
measured bits.
"""
program = program.copy()
validate_supported_quil(program)
ro = program.declare('ro', 'BIT', len(self.qubits()))
for i, q in enumerate(self.qubits()):
program.inst(MEASURE(q, ro[i]))
program.wrap_in_numshots_loop(trials)
executable = self.compile(program)
bitstring_array = self.run(executable=executable)
bitstring_dict = {}
for i, q in enumerate(self.qubits()):
bitstring_dict[q] = bitstring_array[:, i]
return bitstring_dict
def test_validate_supported_quil_suite():
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
I 0
CZ 2 3
MEASURE 2 ro[2]
MEASURE 3 ro[3]
"""))
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
I 0
CZ 2 3
MEASURE 2 ro[2]
MEASURE 3 ro[3]
"""))
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
I 0
MEASURE 0
CZ 2 3
MEASURE 2 ro[2]
X 3
MEASURE 3 ro[3]
"""))
with pytest.raises(ValueError):
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
RESET
I 0
CZ 2 3
MEASURE 2 ro[2]
MEASURE 3 ro[3]
"""))
with pytest.raises(ValueError):
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
MEASURE 2
I 0
CZ 2 3
MEASURE 2 ro[2]
MEASURE 3 ro[3]
"""))
with pytest.raises(ValueError):
validate_supported_quil(
Program("""
RESET
DECLARE ro BIT[3]
RX(-pi/4) 2
RZ(4*pi) 3
HALT
I 0
CZ 2 3
MEASURE 2 ro[2]
MEASURE 3 ro[3]
"""))
def test_validate_supported_quil_reset_first():
prog = Program(H(0), RESET())
with pytest.raises(ValueError):
validate_supported_quil(prog)
assert not prog.is_supported_on_qpu()