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StabilizerState

class qiskit.quantum_info.StabilizerState(data, validate=True)

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Bases: QuantumState

StabilizerState class. Stabilizer simulator using the convention from reference [1]. Based on the internal class Clifford.

from qiskit import QuantumCircuit
from qiskit.quantum_info import StabilizerState, Pauli
 
# Bell state generation circuit
qc = QuantumCircuit(2)
qc.h(0)
qc.cx(0, 1)
stab = StabilizerState(qc)
 
# Print the StabilizerState
print(stab)
 
# Calculate the StabilizerState measurement probabilities dictionary
print (stab.probabilities_dict())
 
# Calculate expectation value of the StabilizerState
print (stab.expectation_value(Pauli('ZZ')))
StabilizerState(StabilizerTable: ['+XX', '+ZZ'])
{'00': 0.5, '11': 0.5}
1

Given a list of stabilizers, qiskit.quantum_info.StabilizerState.from_stabilizer_list() returns a state stabilized by the list

from qiskit.quantum_info import StabilizerState
 
stabilizer_list = ["ZXX", "-XYX", "+ZYY"]
stab = StabilizerState.from_stabilizer_list(stabilizer_list)

References

  1. S. Aaronson, D. Gottesman, Improved Simulation of Stabilizer Circuits, Phys. Rev. A 70, 052328 (2004). arXiv:quant-ph/0406196

Initialize a StabilizerState object.

Parameters


Attributes

clifford

Return StabilizerState Clifford data

dim

Return total state dimension.

num_qubits

Return the number of qubits if a N-qubit state or None otherwise.


Methods

conjugate

conjugate()

GitHub

Return the conjugate of the operator.

copy

copy()

GitHub

Make a copy of current operator.

dims

dims(qargs=None)

GitHub

Return tuple of input dimension for specified subsystems.

equiv

equiv(other)

GitHub

Return True if the two generating sets generate the same stabilizer group.

Parameters

other (StabilizerState) – another StabilizerState.

Returns

True if other has a generating set that generates the same StabilizerState.

Return type

bool

evolve

evolve(other, qargs=None)

GitHub

Evolve a stabilizer state by a Clifford operator.

Parameters

Returns

the output stabilizer state.

Return type

StabilizerState

Raises

  • QiskitError – if other is not a StabilizerState.
  • QiskitError – if the operator dimension does not match the specified StabilizerState subsystem dimensions.

expand

expand(other)

GitHub

Return the tensor product stabilizer state other ⊗ self.

Parameters

other (StabilizerState) – a stabilizer state object.

Returns

the tensor product operator other ⊗ self.

Return type

StabilizerState

Raises

QiskitError – if other is not a StabilizerState.

expectation_value

expectation_value(oper, qargs=None)

GitHub

Compute the expectation value of a Pauli operator.

Parameters

  • oper (Pauli) – a Pauli operator to evaluate expval.
  • qargs (None or list) – subsystems to apply the operator on.

Returns

the expectation value (only 0 or 1 or -1 or i or -i).

Return type

complex

Raises

QiskitError – if oper is not a Pauli operator.

from_stabilizer_list

classmethod from_stabilizer_list(stabilizers, allow_redundant=False, allow_underconstrained=False)

GitHub

Create a stabilizer state from the collection of stabilizers.

Parameters

  • stabilizers (Collection[str]) – list of stabilizer strings
  • allow_redundant (bool) – allow redundant stabilizers (i.e., some stabilizers can be products of the others)
  • allow_underconstrained (bool) – allow underconstrained set of stabilizers (i.e., the stabilizers do not specify a unique state)

Returns

a state stabilized by stabilizers.

Return type

StabilizerState

is_valid

is_valid(atol=None, rtol=None)

GitHub

Return True if a valid StabilizerState.

measure

measure(qargs=None)

GitHub

Measure subsystems and return outcome and post-measure state.

Note that this function uses the QuantumStates internal random number generator for sampling the measurement outcome. The RNG seed can be set using the seed() method.

Parameters

qargs (list or None) – subsystems to sample measurements for, if None sample measurement of all subsystems (Default: None).

Returns

the pair (outcome, state) where outcome is the

measurement outcome string label, and state is the collapsed post-measurement stabilizer state for the corresponding outcome.

Return type

tuple

probabilities

probabilities(qargs=None, decimals=None)

GitHub

Return the subsystem measurement probability vector.

Measurement probabilities are with respect to measurement in the computation (diagonal) basis.

Parameters

  • qargs (None or list) – subsystems to return probabilities for, if None return for all subsystems (Default: None).
  • decimals (None or int) – the number of decimal places to round values. If None no rounding is done (Default: None).

Returns

The Numpy vector array of probabilities.

Return type

np.array

probabilities_dict

probabilities_dict(qargs=None, decimals=None)

GitHub

Return the subsystem measurement probability dictionary.

Measurement probabilities are with respect to measurement in the computation (diagonal) basis.

This dictionary representation uses a Ket-like notation where the dictionary keys are qudit strings for the subsystem basis vectors. If any subsystem has a dimension greater than 10 comma delimiters are inserted between integers so that subsystems can be distinguished.

Parameters

  • qargs (None or list) – subsystems to return probabilities for, if None return for all subsystems (Default: None).
  • decimals (None or int) – the number of decimal places to round values. If None no rounding is done (Default: None).

Returns

The measurement probabilities in dict (key) form.

Return type

dict

probabilities_dict_from_bitstring

probabilities_dict_from_bitstring(outcome_bitstring, qargs=None, decimals=None)

GitHub

Return the subsystem measurement probability dictionary utilizing a targeted outcome_bitstring to perform the measurement for. This will calculate a probability for only a single targeted outcome_bitstring value, giving a performance boost over calculating all possible outcomes.

Measurement probabilities are with respect to measurement in the computation (diagonal) basis.

This dictionary representation uses a Ket-like notation where the dictionary keys are qudit strings for the subsystem basis vectors. If any subsystem has a dimension greater than 10 comma delimiters are inserted between integers so that subsystems can be distinguished.

Parameters

  • outcome_bitstring (None or str) – targeted outcome bitstring to perform a measurement calculation for, this will significantly reduce the number of calculation performed (Default: None)
  • qargs (None or list) – subsystems to return probabilities for, if None return for all subsystems (Default: None).
  • decimals (None or int) – the number of decimal places to round values. If None no rounding is done (Default: None)

Returns

The measurement probabilities in dict (ket) form.

Return type

dict[str, float]

purity

purity()

GitHub

Return the purity of the quantum state, which equals to 1, since it is always a pure state.

Returns

the purity (should equal 1).

Return type

float

Raises

QiskitError – if input is not a StabilizerState.

reset

reset(qargs=None)

GitHub

Reset state or subsystems to the 0-state.

Parameters

qargs (list or None) – subsystems to reset, if None all subsystems will be reset to their 0-state (Default: None).

Returns

the reset state.

Return type

StabilizerState

Additional Information:

If all subsystems are reset this will return the ground state on all subsystems. If only some subsystems are reset this function will perform a measurement on those subsystems and evolve the subsystems so that the collapsed post-measurement states are rotated to the 0-state. The RNG seed for this sampling can be set using the seed() method.

sample_counts

sample_counts(shots, qargs=None)

GitHub

Sample a dict of qubit measurement outcomes in the computational basis.

Parameters

  • shots (int) – number of samples to generate.
  • qargs (None or list) – subsystems to sample measurements for, if None sample measurement of all subsystems (Default: None).

Returns

sampled counts dictionary.

Return type

Counts

Additional Information:

This function samples measurement outcomes using the measure probabilities() for the current state and qargs. It does not actually implement the measurement so the current state is not modified.

The seed for random number generator used for sampling can be set to a fixed value by using the stats seed() method.

sample_memory

sample_memory(shots, qargs=None)

GitHub

Sample a list of qubit measurement outcomes in the computational basis.

Parameters

  • shots (int) – number of samples to generate.
  • qargs (None or list) – subsystems to sample measurements for, if None sample measurement of all subsystems (Default: None).

Returns

list of sampled counts if the order sampled.

Return type

np.array

Additional Information:

This function implements the measurement measure() method.

The seed for random number generator used for sampling can be set to a fixed value by using the stats seed() method.

seed

seed(value=None)

GitHub

Set the seed for the quantum state RNG.

tensor

tensor(other)

GitHub

Return the tensor product stabilizer state self ⊗ other.

Parameters

other (StabilizerState) – a stabilizer state object.

Returns

the tensor product operator self ⊗ other.

Return type

StabilizerState

Raises

QiskitError – if other is not a StabilizerState.

to_operator

to_operator()

GitHub

Convert state to matrix operator class

Return type

Operator

trace

trace()

GitHub

Return the trace of the stabilizer state as a density matrix, which equals to 1, since it is always a pure state.

Returns

the trace (should equal 1).

Return type

float

Raises

QiskitError – if input is not a StabilizerState.

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