def sample_bitstrings(self,
n_samples: int,
tol_factor: float = 1e8) -> np.ndarray:
"""
Sample bitstrings from the distribution defined by the wavefunction.
Qubit 0 is at ``out[:, 0]``.
:param n_samples: The number of bitstrings to sample
:param tol_factor: Tolerance to set imaginary probabilities to zero, relative to
machine epsilon.
:return: An array of shape (n_samples, n_qubits)
"""
if self.rs is None:
raise ValueError(
"You have tried to perform a stochastic operation without setting the "
"random state of the simulator. Might I suggest using a PyQVM object?"
)
# for np.real_if_close the actual tolerance is (machine_eps * tol_factor),
# where `machine_epsilon = np.finfo(float).eps`. If we use tol_factor = 1e8, then the
# overall tolerance is \approx 2.2e-8.
probabilities = np.real_if_close(np.diagonal(self.density),
tol=tol_factor) # type: ignore
# Next set negative probabilities to zero
probabilities = np.array([0 if p < 0.0 else p for p in probabilities])
# Ensure they sum to one
probabilities = probabilities / np.sum(probabilities)
possible_bitstrings = all_bitstrings(self.n_qubits)
inds = self.rs.choice(2**self.n_qubits, n_samples, p=probabilities)
bitstrings = possible_bitstrings[inds, :]
bitstrings = np.flip(bitstrings,
axis=1) # qubit ordering: 0 on the left.
return bitstrings # type: ignore
def sample_bitstrings(self, n_samples: int) -> np.ndarray:
"""
Sample bitstrings from the distribution defined by the wavefunction.
Qubit 0 is at ``out[:, 0]``.
:param n_samples: The number of bitstrings to sample
:return: An array of shape (n_samples, n_qubits)
"""
if self.rs is None:
raise ValueError(
"You have tried to perform a stochastic operation without setting the "
"random state of the simulator. Might I suggest using a PyQVM object?"
)
probabilities = np.abs(self.wf)**2
possible_bitstrings = all_bitstrings(self.n_qubits)
inds = self.rs.choice(2**self.n_qubits, n_samples, p=probabilities)
bitstrings = possible_bitstrings[inds, :]
bitstrings = np.flip(bitstrings,
axis=1) # qubit ordering: 0 on the left.
return bitstrings # type: ignore
def sample_bitstrings(self, n_samples: int) -> np.ndarray:
"""
Sample bitstrings from the distribution defined by the wavefunction.
Qubit 0 is at ``out[:, 0]``.
:param n_samples: The number of bitstrings to sample
:return: An array of shape (n_samples, n_qubits)
"""
if self.rs is None:
raise ValueError(
"You have tried to perform a stochastic operation without setting the "
"random state of the simulator. Might I suggest using a PyQVM object?"
)
# note on reshape: it puts bitstrings in lexicographical order.
# would you look at that .. _all_bitstrings returns things in lexicographical order!
# reminder: qubit 0 is on the left in einsum simulator.
probabilities = np.abs(self.wf.reshape(-1))**2
possible_bitstrings = all_bitstrings(self.n_qubits)
inds = self.rs.choice(2**self.n_qubits, n_samples, p=probabilities)
return possible_bitstrings[inds, :]