def __init__(self, data, coeffs=None):
"""Initialize an operator object.
Args:
data (Paulilist, SparsePauliOp, PauliTable): Pauli list of terms.
coeffs (np.ndarray): complex coefficients for Pauli terms.
Raises:
QiskitError: If the input data or coeffs are invalid.
"""
if isinstance(data, SparsePauliOp):
pauli_list = data._pauli_list
coeffs = data._coeffs
else:
pauli_list = PauliList(data)
if coeffs is None:
coeffs = np.ones(pauli_list.size, dtype=complex)
# Initialize PauliList
self._pauli_list = PauliList.from_symplectic(pauli_list.z, pauli_list.x)
# Initialize Coeffs
self._coeffs = np.asarray((-1j) ** pauli_list.phase * coeffs, dtype=complex)
if self._coeffs.shape != (self._pauli_list.size,):
raise QiskitError(
"coeff vector is incorrect shape for number"
" of Paulis {} != {}".format(self._coeffs.shape, self._pauli_list.size)
)
# Initialize LinearOp
super().__init__(num_qubits=self._pauli_list.num_qubits)
def pauli_basis(num_qubits, weight=False, pauli_list=False):
"""Return the ordered PauliTable or PauliList for the n-qubit Pauli basis.
Args:
num_qubits (int): number of qubits
weight (bool): if True optionally return the basis sorted by Pauli weight
rather than lexicographic order (Default: False)
pauli_list (bool): if True, the return type becomes PauliList, otherwise PauliTable.
Returns:
PauliTable, PauliList: the Paulis for the basis
"""
if pauli_list:
pauli_1q = PauliList(["I", "X", "Y", "Z"])
else:
warnings.warn(
"The pauli_basis function with PauliTable output is deprecated as of Qiskit Terra "
"0.19.0 and will be removed no sooner than 3 months after the releasedate. "
"Use PauliList by pauli_list=True instead.",
DeprecationWarning,
stacklevel=2,
)
pauli_1q = PauliTable(
np.array(
[[False, False], [True, False], [True, True], [False, True]],
dtype=bool))
if num_qubits == 1:
return pauli_1q
pauli = pauli_1q
for _ in range(num_qubits - 1):
pauli = pauli_1q.tensor(pauli)
if weight:
return pauli.sort(weight=True)
return pauli
def pauli_basis(num_qubits, weight=False, pauli_list=False):
"""Return the ordered PauliTable or PauliList for the n-qubit Pauli basis.
Args:
num_qubits (int): number of qubits
weight (bool): if True optionally return the basis sorted by Pauli weight
rather than lexicographic order (Default: False)
pauli_list (bool): if True, the return type becomes PauliList, otherwise PauliTable.
Returns:
PauliTable, PauliList: the Paulis for the basis
"""
if pauli_list:
pauli_1q = PauliList(["I", "X", "Y", "Z"])
else:
warnings.warn(
"The return type of 'pauli_basis' will change from PauliTable to PauliList in a "
"future release of Qiskit Terra. Returning PauliTable is deprecated as of "
"Qiskit Terra 0.19, and will be removed in a future release. To immediately switch "
"to the new behaviour, pass the keyword argument 'pauli_list=True'.",
FutureWarning,
stacklevel=2,
)
pauli_1q = PauliTable(
np.array(
[[False, False], [True, False], [True, True], [False, True]],
dtype=bool))
if num_qubits == 1:
return pauli_1q
pauli = pauli_1q
for _ in range(num_qubits - 1):
pauli = pauli_1q.tensor(pauli)
if weight:
return pauli.sort(weight=True)
return pauli
def compose(self, other, qargs=None, front=False):
if qargs is None:
qargs = getattr(other, "qargs", None)
if not isinstance(other, SparsePauliOp):
other = SparsePauliOp(other)
# Validate composition dimensions and qargs match
self._op_shape.compose(other._op_shape, qargs, front)
if qargs is not None:
x1, z1 = self.paulis.x[:, qargs], self.paulis.z[:, qargs]
else:
x1, z1 = self.paulis.x, self.paulis.z
x2, z2 = other.paulis.x, other.paulis.z
num_qubits = other.num_qubits
# This method is the outer version of `BasePauli.compose`.
# `x1` and `z1` have shape `(self.size, num_qubits)`.
# `x2` and `z2` have shape `(other.size, num_qubits)`.
# `x1[:, no.newaxis]` results in shape `(self.size, 1, num_qubits)`.
# `ar = ufunc(x1[:, np.newaxis], x2)` will be in shape `(self.size, other.size, num_qubits)`.
# So, `ar.reshape((-1, num_qubits))` will be in shape `(self.size * other.size, num_qubits)`.
# Ref: https://numpy.org/doc/stable/user/theory.broadcasting.html
phase = np.add.outer(self.paulis._phase,
other.paulis._phase).reshape(-1)
if front:
q = np.logical_and(x1[:, np.newaxis], z2).reshape((-1, num_qubits))
else:
q = np.logical_and(z1[:, np.newaxis], x2).reshape((-1, num_qubits))
# `np.mod` will be applied to `phase` in `SparsePauliOp.__init__`
phase = phase + 2 * q.sum(axis=1, dtype=np.uint8)
x3 = np.logical_xor(x1[:, np.newaxis], x2).reshape((-1, num_qubits))
z3 = np.logical_xor(z1[:, np.newaxis], z2).reshape((-1, num_qubits))
if qargs is None:
pauli_list = PauliList(BasePauli(z3, x3, phase))
else:
x4 = np.repeat(self.paulis.x, other.size, axis=0)
z4 = np.repeat(self.paulis.z, other.size, axis=0)
x4[:, qargs] = x3
z4[:, qargs] = z3
pauli_list = PauliList(BasePauli(z4, x4, phase))
# note: the following is a faster code equivalent to
# `coeffs = np.kron(self.coeffs, other.coeffs)`
# since `self.coeffs` and `other.coeffs` are both 1d arrays.
coeffs = np.multiply.outer(self.coeffs, other.coeffs).ravel()
return SparsePauliOp(pauli_list, coeffs, copy=False)
def sum(ops):
"""Sum of SparsePauliOps.
This is a specialized version of the builtin ``sum`` function for SparsePauliOp
with smaller overhead.
Args:
ops (list[SparsePauliOp]): a list of SparsePauliOps.
Returns:
SparsePauliOp: the SparsePauliOp representing the sum of the input list.
Raises:
QiskitError: if the input list is empty.
QiskitError: if the input list includes an object that is not SparsePauliOp.
QiskitError: if the numbers of qubits of the objects in the input list do not match.
"""
if len(ops) == 0:
raise QiskitError("Input list is empty")
if not all(isinstance(op, SparsePauliOp) for op in ops):
raise QiskitError(
"Input list includes an object that is not SparsePauliOp")
for other in ops[1:]:
ops[0]._op_shape._validate_add(other._op_shape)
z = np.vstack([op.paulis.z for op in ops])
x = np.vstack([op.paulis.x for op in ops])
phase = np.hstack([op.paulis._phase for op in ops])
pauli_list = PauliList(BasePauli(z, x, phase))
coeffs = np.hstack([op.coeffs for op in ops])
return SparsePauliOp(pauli_list,
coeffs,
ignore_pauli_phase=True,
copy=False)
def compose(self, other, qargs=None, front=False):
if qargs is None:
qargs = getattr(other, "qargs", None)
if not isinstance(other, SparsePauliOp):
other = SparsePauliOp(other)
# Validate composition dimensions and qargs match
self._op_shape.compose(other._op_shape, qargs, front)
if qargs is not None:
x1, z1 = self.paulis.x[:, qargs], self.paulis.z[:, qargs]
else:
x1, z1 = self.paulis.x, self.paulis.z
x2, z2 = other.paulis.x, other.paulis.z
num_qubits = other.num_qubits
# This method is the outer version of `BasePauli.compose`.
# `x1` and `z1` have shape `(self.size, num_qubits)`.
# `x2` and `z2` have shape `(other.size, num_qubits)`.
# `x1[:, no.newaxis]` results in shape `(self.size, 1, num_qubits)`.
# `ar = ufunc(x1[:, np.newaxis], x2)` will be in shape `(self.size, other.size, num_qubits)`.
# So, `ar.reshape((-1, num_qubits))` will be in shape `(self.size * other.size, num_qubits)`.
# Ref: https://numpy.org/doc/stable/user/theory.broadcasting.html
phase = np.add.outer(self.paulis._phase,
other.paulis._phase).reshape(-1)
if front:
q = np.logical_and(x1[:, np.newaxis], z2).reshape((-1, num_qubits))
else:
q = np.logical_and(z1[:, np.newaxis], x2).reshape((-1, num_qubits))
phase = np.mod(phase + 2 * np.sum(q, axis=1), 4)
x3 = np.logical_xor(x1[:, np.newaxis], x2).reshape((-1, num_qubits))
z3 = np.logical_xor(z1[:, np.newaxis], z2).reshape((-1, num_qubits))
if qargs is None:
pauli_list = PauliList(BasePauli(z3, x3, phase))
else:
x4 = np.repeat(self.paulis.x, other.size, axis=0)
z4 = np.repeat(self.paulis.z, other.size, axis=0)
x4[:, qargs] = x3
z4[:, qargs] = z3
pauli_list = PauliList(BasePauli(z4, x4, phase))
coeffs = np.kron(self.coeffs, other.coeffs)
return SparsePauliOp(pauli_list, coeffs)
def from_sparse_list(obj, num_qubits):
"""Construct from a list of local Pauli strings and coefficients.
Each list element is a 3-tuple of a local Pauli string, indices where to apply it,
and a coefficient.
For example, the 5-qubit Hamiltonian
.. math::
H = Z_1 X_4 + 2 Y_0 Y_3
can be constructed as
.. code-block:: python
# via triples and local Paulis with indices
op = SparsePauliOp.from_sparse_list([("ZX", [1, 4], 1), ("YY", [0, 3], 2)], num_qubits=5)
# equals the following construction from "dense" Paulis
op = SparsePauliOp.from_list([("XIIZI", 1), ("IYIIY", 2)])
Args:
obj (Iterable[Tuple[str, List[int], complex]]): The list 3-tuples specifying the Paulis.
num_qubits (int): The number of qubits of the operator.
Returns:
SparsePauliOp: The SparsePauliOp representation of the Pauli terms.
Raises:
QiskitError: If the list of Paulis is empty.
QiskitError: If the number of qubits is incompatible with the indices of the Pauli terms.
"""
obj = list(obj) # To convert zip or other iterable
size = len(obj) # number of Pauli terms
if size == 0:
raise QiskitError("Input Pauli list is empty.")
coeffs = np.zeros(size, dtype=complex)
labels = np.zeros(size, dtype=f"<U{num_qubits}")
for i, (paulis, indices, coeff) in enumerate(obj):
# construct the full label based off the non-trivial Paulis and indices
label = ["I"] * num_qubits
for pauli, index in zip(paulis, indices):
if index >= num_qubits:
raise QiskitError(
f"The number of qubits ({num_qubits}) is smaller than a required index {index}."
)
label[~index] = pauli
labels[i] = "".join(label)
coeffs[i] = coeff
paulis = PauliList(labels)
return SparsePauliOp(paulis, coeffs, copy=False)
def simplify(self, atol=None, rtol=None):
"""Simplify PauliList by combining duplicates and removing zeros.
Args:
atol (float): Optional. Absolute tolerance for checking if
coefficients are zero (Default: 1e-8).
rtol (float): Optional. relative tolerance for checking if
coefficients are zero (Default: 1e-5).
Returns:
SparsePauliOp: the simplified SparsePauliOp operator.
"""
# Get default atol and rtol
if atol is None:
atol = self.atol
if rtol is None:
rtol = self.rtol
# Filter non-zero coefficients
non_zero = np.logical_not(
np.isclose(self.coeffs, 0, atol=atol, rtol=rtol))
paulis_x = self.paulis.x[non_zero]
paulis_z = self.paulis.z[non_zero]
nz_coeffs = self.coeffs[non_zero]
# Pack bool vectors into np.uint8 vectors by np.packbits
array = np.packbits(paulis_x, axis=1) * 256 + np.packbits(paulis_z,
axis=1)
indexes, inverses = unordered_unique(array)
if np.all(non_zero) and indexes.shape[0] == array.shape[0]:
# No zero operator or duplicate operator
return self.copy()
coeffs = np.zeros(indexes.shape[0], dtype=complex)
np.add.at(coeffs, inverses, nz_coeffs)
# Delete zero coefficient rows
is_zero = np.isclose(coeffs, 0, atol=atol, rtol=rtol)
# Check edge case that we deleted all Paulis
# In this case we return an identity Pauli with a zero coefficient
if np.all(is_zero):
x = np.zeros((1, self.num_qubits), dtype=bool)
z = np.zeros((1, self.num_qubits), dtype=bool)
coeffs = np.array([0j], dtype=complex)
else:
non_zero = np.logical_not(is_zero)
non_zero_indexes = indexes[non_zero]
x = paulis_x[non_zero_indexes]
z = paulis_z[non_zero_indexes]
coeffs = coeffs[non_zero]
return SparsePauliOp(PauliList.from_symplectic(z, x),
coeffs,
ignore_pauli_phase=True,
copy=False)
def _evolve_clifford(self, other, qargs=None, frame="h"):
"""Heisenberg picture evolution of a Pauli by a Clifford."""
if qargs is None:
idx = slice(None)
num_act = self.num_qubits
else:
idx = list(qargs)
num_act = len(idx)
# Set return to I on qargs
ret = self.copy()
ret._x[:, idx] = False
ret._z[:, idx] = False
# pylint: disable=cyclic-import
from qiskit.quantum_info.operators.symplectic.pauli import Pauli
from qiskit.quantum_info.operators.symplectic.pauli_list import PauliList
# Get action of Pauli's from Clifford
if frame == "s":
adj = other.copy()
else:
adj = other.adjoint()
pauli_list = []
for z in self._z[:, idx]:
pauli = Pauli("I" * num_act)
for row in adj.stabilizer[z]:
pauli.compose(Pauli((row.Z[0], row.X[0], 2 * row.phase[0])),
inplace=True)
pauli_list.append(pauli)
ret.dot(PauliList(pauli_list), qargs=qargs, inplace=True)
pauli_list = []
for x in self._x[:, idx]:
pauli = Pauli("I" * num_act)
for row in adj.destabilizer[x]:
pauli.compose(Pauli((row.Z[0], row.X[0], 2 * row.phase[0])),
inplace=True)
pauli_list.append(pauli)
ret.dot(PauliList(pauli_list), qargs=qargs, inplace=True)
return ret
def from_list(obj):
"""Construct from a list [(pauli_str, coeffs)]"""
obj = list(obj) # To convert zip or other iterable
num_qubits = len(obj[0][0])
size = len(obj)
coeffs = np.zeros(size, dtype=complex)
labels = np.zeros(size, dtype=f"<U{num_qubits}")
for i, item in enumerate(obj):
labels[i] = item[0]
coeffs[i] = item[1]
paulis = PauliList(labels)
return SparsePauliOp(paulis, coeffs)
def compose(self, other, qargs=None, front=False):
if qargs is None:
qargs = getattr(other, "qargs", None)
if not isinstance(other, SparsePauliOp):
other = SparsePauliOp(other)
# Validate composition dimensions and qargs match
self._op_shape.compose(other._op_shape, qargs, front)
x1 = np.reshape(
np.stack(other.size * [self.paulis.x], axis=1),
(self.size * other.size, self.num_qubits),
)
z1 = np.reshape(
np.stack(other.size * [self.paulis.z], axis=1),
(self.size * other.size, self.num_qubits),
)
p1 = np.reshape(
np.stack(other.size * [self.paulis.phase], axis=1),
self.size * other.size,
)
paulis1 = PauliList.from_symplectic(z1, x1, p1)
x2 = np.reshape(
np.stack(self.size * [other.paulis.x]), (self.size * other.size, other.num_qubits)
)
z2 = np.reshape(
np.stack(self.size * [other.paulis.z]), (self.size * other.size, other.num_qubits)
)
p2 = np.reshape(
np.stack(self.size * [other.paulis.phase]),
self.size * other.size,
)
paulis2 = PauliList.from_symplectic(z2, x2, p2)
pauli_list = paulis1.compose(paulis2, qargs, front)
coeffs = np.kron(self.coeffs, other.coeffs)
return SparsePauliOp(pauli_list, coeffs)
def _multiply(self, other):
if not isinstance(other, Number):
raise QiskitError("other is not a number")
if other == 0:
# Check edge case that we deleted all Paulis
# In this case we return an identity Pauli with a zero coefficient
paulis = PauliList.from_symplectic(
np.zeros((1, self.num_qubits), dtype=bool),
np.zeros((1, self.num_qubits), dtype=bool),
)
coeffs = np.array([0j])
return SparsePauliOp(paulis, coeffs)
# Otherwise we just update the phases
return SparsePauliOp(self.paulis, other * self.coeffs)
def simplify(self, atol=None, rtol=None):
"""Simplify PauliList by combining duplicates and removing zeros.
Args:
atol (float): Optional. Absolute tolerance for checking if
coefficients are zero (Default: 1e-8).
rtol (float): Optional. relative tolerance for checking if
coefficients are zero (Default: 1e-5).
Returns:
SparsePauliOp: the simplified SparsePauliOp operator.
"""
# Get default atol and rtol
if atol is None:
atol = self.atol
if rtol is None:
rtol = self.rtol
array = np.column_stack((self.paulis.x, self.paulis.z))
flatten_paulis, indexes = np.unique(array, return_inverse=True, axis=0)
coeffs = np.zeros(self.size, dtype=complex)
for i, val in zip(indexes, self.coeffs):
coeffs[i] += val
# Delete zero coefficient rows
# TODO: Add atol/rtol for zero comparison
non_zero = [
i for i in range(coeffs.size) if not np.isclose(coeffs[i], 0, atol=atol, rtol=rtol)
]
# Check edge case that we deleted all Paulis
# In this case we return an identity Pauli with a zero coefficient
if len(non_zero) == 0:
x = np.zeros((1, self.num_qubits), dtype=bool)
z = np.zeros((1, self.num_qubits), dtype=bool)
coeffs = np.array([0j], dtype=complex)
else:
x, z = (
flatten_paulis[non_zero]
.reshape((len(non_zero), 2, self.num_qubits))
.transpose(1, 0, 2)
)
coeffs = coeffs[non_zero]
return SparsePauliOp(PauliList.from_symplectic(z, x), coeffs)
def from_list(obj):
"""Construct from a list of Pauli strings and coefficients.
For example, the 5-qubit Hamiltonian
.. math::
H = Z_1 X_4 + 2 Y_0 Y_3
can be constructed as
.. code-block:: python
# via tuples and the full Pauli string
op = SparsePauliOp.from_list([("XIIZI", 1), ("IYIIY", 2)])
Args:
obj (Iterable[Tuple[str, complex]]): The list of 2-tuples specifying the Pauli terms.
Returns:
SparsePauliOp: The SparsePauliOp representation of the Pauli terms.
Raises:
QiskitError: If the list of Paulis is empty.
"""
obj = list(obj) # To convert zip or other iterable
size = len(obj) # number of Pauli terms
if size == 0:
raise QiskitError("Input Pauli list is empty.")
# determine the number of qubits
num_qubits = len(obj[0][0])
coeffs = np.zeros(size, dtype=complex)
labels = np.zeros(size, dtype=f"<U{num_qubits}")
for i, item in enumerate(obj):
labels[i] = item[0]
coeffs[i] = item[1]
paulis = PauliList(labels)
return SparsePauliOp(paulis, coeffs, copy=False)
def chop(self, tol=1e-14):
"""Set real and imaginary parts of the coefficients to 0 if ``< tol`` in magnitude.
For example, the operator representing ``1+1e-17j X + 1e-17 Y`` with a tolerance larger
than ``1e-17`` will be reduced to ``1 X`` whereas :meth:`.SparsePauliOp.simplify` would
return ``1+1e-17j X``.
If a both the real and imaginary part of a coefficient is 0 after chopping, the
corresponding Pauli is removed from the operator.
Args:
tol (float): The absolute tolerance to check whether a real or imaginary part should
be set to 0.
Returns:
SparsePauliOp: This operator with chopped coefficients.
"""
realpart_nonzero = np.abs(self.coeffs.real) > tol
imagpart_nonzero = np.abs(self.coeffs.imag) > tol
remaining_indices = np.logical_or(realpart_nonzero, imagpart_nonzero)
remaining_real = realpart_nonzero[remaining_indices]
remaining_imag = imagpart_nonzero[remaining_indices]
if len(remaining_real) == 0: # if no Paulis are left
x = np.zeros((1, self.num_qubits), dtype=bool)
z = np.zeros((1, self.num_qubits), dtype=bool)
coeffs = np.array([0j], dtype=complex)
else:
coeffs = np.zeros(np.count_nonzero(remaining_indices),
dtype=complex)
coeffs.real[remaining_real] = self.coeffs.real[realpart_nonzero]
coeffs.imag[remaining_imag] = self.coeffs.imag[imagpart_nonzero]
x = self.paulis.x[remaining_indices]
z = self.paulis.z[remaining_indices]
return SparsePauliOp(PauliList.from_symplectic(z, x),
coeffs,
ignore_pauli_phase=True,
copy=False)
def _evolve_clifford(self, other, qargs=None, frame="h"):
"""Heisenberg picture evolution of a Pauli by a Clifford."""
if frame == "s":
adj = other
else:
adj = other.adjoint()
if qargs is None:
qargs_ = slice(None)
else:
qargs_ = list(qargs)
# pylint: disable=cyclic-import
from qiskit.quantum_info.operators.symplectic.pauli_list import PauliList
num_paulis = self._x.shape[0]
ret = self.copy()
ret._x[:, qargs_] = False
ret._z[:, qargs_] = False
idx = np.concatenate((self._x[:, qargs_], self._z[:, qargs_]), axis=1)
for idx_, row in zip(
idx.T,
PauliList.from_symplectic(z=adj.table.Z, x=adj.table.X, phase=2 * adj.table.phase),
):
# most of the logic below is to properly index if self is a PauliList (2D),
# while not trying to index if the object is just a Pauli (1D).
if idx_.any():
if np.sum(idx_) == num_paulis:
ret.compose(row, qargs=qargs, inplace=True)
else:
ret[idx_] = ret[idx_].compose(row, qargs=qargs)
return ret
def table(self, value):
if not isinstance(value, PauliTable):
value = PauliTable(value)
self._pauli_list = PauliList(value)
def __init__(self,
data,
coeffs=None,
*,
ignore_pauli_phase=False,
copy=True):
"""Initialize an operator object.
Args:
data (PauliList or SparsePauliOp or PauliTable or Pauli or list or str): Pauli list of
terms. A list of Pauli strings or a Pauli string is also allowed.
coeffs (np.ndarray): complex coefficients for Pauli terms.
.. note::
If ``data`` is a :obj:`~SparsePauliOp` and ``coeffs`` is not ``None``, the value
of the ``SparsePauliOp.coeffs`` will be ignored, and only the passed keyword
argument ``coeffs`` will be used.
ignore_pauli_phase (bool): if true, any ``phase`` component of a given :obj:`~PauliList`
will be assumed to be zero. This is more efficient in cases where a
:obj:`~PauliList` has been constructed purely for this object, and it is already
known that the phases in the ZX-convention are zero. It only makes sense to pass
this option when giving :obj:`~PauliList` data. (Default: False)
copy (bool): copy the input data if True, otherwise assign it directly, if possible.
(Default: True)
Raises:
QiskitError: If the input data or coeffs are invalid.
"""
if ignore_pauli_phase and not isinstance(data, PauliList):
raise QiskitError(
"ignore_pauli_list=True is only valid with PauliList data")
if isinstance(data, SparsePauliOp):
if coeffs is None:
coeffs = data.coeffs
data = data._pauli_list
# `SparsePauliOp._pauli_list` is already compatible with the internal ZX-phase
# convention. See `BasePauli._from_array` for the internal ZX-phase convention.
ignore_pauli_phase = True
pauli_list = PauliList(
data.copy() if copy and hasattr(data, "copy") else data)
if coeffs is None:
coeffs = np.ones(pauli_list.size, dtype=complex)
else:
coeffs = np.array(coeffs, copy=copy, dtype=complex)
if ignore_pauli_phase:
# Fast path used in copy operations, where the phase of the PauliList is already known
# to be zero. This path only works if the input data is compatible with the internal
# ZX-phase convention.
self._pauli_list = pauli_list
self._coeffs = coeffs
else:
# move the phase of `pauli_list` to `self._coeffs`
phase = pauli_list._phase
count_y = pauli_list._count_y()
self._coeffs = np.asarray((-1j)**(phase - count_y) * coeffs,
dtype=complex)
pauli_list._phase = np.mod(count_y, 4)
self._pauli_list = pauli_list
if self._coeffs.shape != (self._pauli_list.size, ):
raise QiskitError("coeff vector is incorrect shape for number"
" of Paulis {} != {}".format(
self._coeffs.shape, self._pauli_list.size))
# Initialize LinearOp
super().__init__(num_qubits=self._pauli_list.num_qubits)
def paulis(self, value):
if not isinstance(value, PauliList):
value = PauliList(value)
self._pauli_list = value