def convert_measurements(self,
backend_result,
target_qubits=None) -> QubitWaveFunction:
"""
Transform backend evaluation results into QubitWaveFunction
Parameters
----------
backend_result:
the return value of backend simulation.
Returns
-------
QubitWaveFunction
results transformed to tequila native QubitWaveFunction
"""
result = QubitWaveFunction()
# todo there are faster ways
for k, v in backend_result.frequencies(binary=True).items():
converted_key = BitString.from_bitstring(
other=BitStringLSB.from_binary(binary=k))
result._state[converted_key] = v
if target_qubits is not None:
mapped_target = [self.qubit_map[q].number for q in target_qubits]
mapped_full = [
self.qubit_map[q].number for q in self.abstract_qubits
]
keymap = KeyMapRegisterToSubregister(subregister=mapped_target,
register=mapped_full)
result = result.apply_keymap(keymap=keymap)
return result
def convert_measurements(self,
backend_result,
target_qubits=None) -> QubitWaveFunction:
"""
map backend results to QubitWaveFunction
Parameters
----------
backend_result:
the result returned directly qiskit simulation.
Returns
-------
QubitWaveFunction:
measurements converted into wave function form.
"""
qiskit_counts = backend_result.result().get_counts()
result = QubitWaveFunction()
# todo there are faster ways
for k, v in qiskit_counts.items():
converted_key = BitString.from_bitstring(
other=BitStringLSB.from_binary(binary=k))
result._state[converted_key] = v
if target_qubits is not None:
mapped_target = [self.qubit_map[q].number for q in target_qubits]
mapped_full = [
self.qubit_map[q].number for q in self.abstract_qubits
]
keymap = KeyMapRegisterToSubregister(subregister=mapped_target,
register=mapped_full)
result = result.apply_keymap(keymap=keymap)
return result
def convert_measurements(self, backend_result) -> QubitWaveFunction:
"""0.
:param qiskit_counts: qiskit counts as dictionary, states are binary in little endian (LSB)
:return: Counts in OpenVQE format, states are big endian (MSB)
"""
qiskit_counts = backend_result.result().get_counts()
result = QubitWaveFunction()
# todo there are faster ways
for k, v in qiskit_counts.items():
converted_key = BitString.from_bitstring(
other=BitStringLSB.from_binary(binary=k))
result._state[converted_key] = v
return result
def do_simulate(self,
variables,
initial_state=0,
*args,
**kwargs) -> QubitWaveFunction:
"""
Helper function for performing simulation.
Parameters
----------
variables:
variables to pass to the circuit for simulation.
initial_state:
indicate initial state on which the unitary self.circuit should act.
args
kwargs
Returns
-------
QubitWaveFunction:
the result of simulation.
"""
if self.noise_model is None:
qiskit_backend = self.retrieve_device('statevector_simulator')
else:
raise TequilaQiskitException(
"wave function simulation with noise cannot be performed presently"
)
optimization_level = None
if "optimization_level" in kwargs:
optimization_level = kwargs['optimization_level']
opts = None
if initial_state != 0:
array = numpy.zeros(shape=[2**self.n_qubits])
i = BitStringLSB.from_binary(
BitString.from_int(integer=initial_state,
nbits=self.n_qubits).binary)
print(initial_state, " -> ", i)
array[i.integer] = 1.0
opts = {"initial_statevector": array}
print(opts)
backend_result = qiskit.execute(experiments=self.circuit,
optimization_level=optimization_level,
backend=qiskit_backend,
parameter_binds=[self.resolver],
backend_options=opts).result()
return QubitWaveFunction.from_array(arr=backend_result.get_statevector(
self.circuit),
numbering=self.numbering)
def convert_measurements(self, backend_result) -> QubitWaveFunction:
"""
map backend results to QubitWaveFunction
Parameters
----------
backend_result:
the result returned directly qiskit simulation.
Returns
-------
QubitWaveFunction:
measurements converted into wave function form.
"""
qiskit_counts = backend_result.result().get_counts()
result = QubitWaveFunction()
# todo there are faster ways
for k, v in qiskit_counts.items():
converted_key = BitString.from_bitstring(
other=BitStringLSB.from_binary(binary=k))
result._state[converted_key] = v
return result
def test_endianness():
tests = [
"000111", "111000", "101010", "010101", "10010010001",
"111100101000010"
]
for string in tests:
bits = len(string)
i1 = BitString.from_int(int(string, 2))
i2 = BitString.from_binary(binary=string)
assert (i1 == i2)
i11 = BitStringLSB.from_int(int(string, 2))
i22 = BitStringLSB.from_binary(binary=string[::-1])
assert (i11 == i22)
assert (i11.integer == i1.integer)
assert (i22.integer == i2.integer)
assert (i11.integer == i2.integer)
assert (i1 == BitString.from_bitstring(i11))
assert (i1 == BitString.from_bitstring(i22))
assert (i2 == BitString.from_bitstring(i11))
def do_simulate(self,
variables,
initial_state=0,
*args,
**kwargs) -> QubitWaveFunction:
if self.noise_model is None:
qiskit_backend = self.get_backend(*args, **kwargs)
if qiskit_backend != qiskit.Aer.get_backend(
name="statevector_simulator"):
raise TequilaQiskitException(
"quiskit_backend for simulations without samples (full wavefunction simulations) need to be the statevector_simulator. Received: qiskit_backend={}"
.format(qiskit_backend))
else:
raise TequilaQiskitException(
"wave function simulation with noise cannot be performed presently"
)
optimization_level = None
if "optimization_level" in kwargs:
optimization_level = kwargs['optimization_level']
opts = None
if initial_state != 0:
array = numpy.zeros(shape=[2**self.n_qubits])
i = BitStringLSB.from_binary(
BitString.from_int(integer=initial_state,
nbits=self.n_qubits).binary)
print(initial_state, " -> ", i)
array[i.integer] = 1.0
opts = {"initial_statevector": array}
print(opts)
backend_result = qiskit.execute(experiments=self.circuit,
optimization_level=optimization_level,
backend=qiskit_backend,
parameter_binds=[self.resolver],
backend_options=opts).result()
return QubitWaveFunction.from_array(arr=backend_result.get_statevector(
self.circuit),
numbering=self.numbering)