AerDensityMatrix#

class AerDensityMatrix(data, dims=None, **configs)[source]#

Bases: DensityMatrix

AerDensityMatrix class This class inherits DensityMatrix.

Parameters:

  • or (data (np.array or list or Statevector or AerStatevector or DensityMatrix) – AerDensityMatrix or QuantumCircuit or qiskit.circuit.Instruction): Data from which the densitymatrix can be constructed. This can be either a complex vector, another densitymatrix or statevector or a QuantumCircuit or Instruction (Operator is not supported in the current implementation). If the data is a circuit or instruction, the densitymatrix is constructed by assuming that all qubits are initialized to the zero state.

  • dims (int or tuple or list) – Optional. The subsystem dimension of the state (See additional information).

  • configs (kwargs) – configurations of AerDensityMatrix. _aer_state and method are valid.

Raises:

AerError – if input data is not valid.

Additional Information:

The dims kwarg is used to AerDensityMatrix constructor.

Attributes

atol = 1e-08#
data#

Return data.

dim#

Return total state dimension.

num_qubits#

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

rtol = 1e-05#
settings#

Return settings.

Methods

__mul__(other)[source]#
conjugate()[source]#

Return the conjugate of the density matrix.

copy()[source]#

Make a copy of current operator.

dims(qargs=None)[source]#

Return tuple of input dimension for specified subsystems.

draw(output: str | None = None, **drawer_args)[source]#

Return a visualization of the Statevector.

repr: ASCII TextMatrix of the state’s __repr__.

text: ASCII TextMatrix that can be printed in the console.

latex: An IPython Latex object for displaying in Jupyter Notebooks.

latex_source: Raw, uncompiled ASCII source to generate array using LaTeX.

qsphere: Matplotlib figure, rendering of density matrix using plot_state_qsphere().

hinton: Matplotlib figure, rendering of density matrix using plot_state_hinton().

bloch: Matplotlib figure, rendering of density matrix using plot_bloch_multivector().

Parameters:

  • output (str) – Select the output method to use for drawing the state. Valid choices are repr, text, latex, latex_source, qsphere, hinton, or bloch. Default is repr. Default can be changed by adding the line state_drawer = <default> to ~/.qiskit/settings.conf under [default].

  • drawer_args – Arguments to be passed directly to the relevant drawing function or constructor (TextMatrix(), array_to_latex(), plot_state_qsphere(), plot_state_hinton() or plot_bloch_multivector()). See the relevant function under qiskit.visualization for that function’s documentation.

Returns:

matplotlib.Figure or str or TextMatrix or IPython.display.Latex: Drawing of the Statevector.

Raises:

ValueError – when an invalid output method is selected.

evolve(other: Operator | QuantumChannel | Instruction | QuantumCircuit, qargs: list[int] | None = None) → DensityMatrix[source]#

Evolve a quantum state by an operator.

Parameters:

  • QuantumChannel (other (Operator or) – or Instruction or Circuit): The operator to evolve by.

  • qargs (list) – a list of QuantumState subsystem positions to apply the operator on.

Returns:

the output density matrix.

Return type:

DensityMatrix

Raises:

QiskitError – if the operator dimension does not match the specified QuantumState subsystem dimensions.

expand(other)[source]#

Return the tensor product state other ⊗ self. :param other: a quantum state object. :type other: AerDensityMatrix

Returns:

the tensor product state other ⊗ self.

Return type:

AerDensityMatrix

Raises:

QiskitError – if other is not a quantum state.

expectation_value(oper: Operator, qargs: None | list[int] = None) → complex[source]#

Compute the expectation value of an operator.

Parameters:

  • oper (Operator) – an operator to evaluate expval.

  • qargs (None or list) – subsystems to apply the operator on.

Returns:

the expectation value.

Return type:

complex

classmethod from_instruction(instruction)[source]#

Return the output density matrix of an instruction.

The statevector is initialized in the state \(|{0,\ldots,0}\rangle\) of the same number of qubits as the input instruction or circuit, evolved by the input instruction, and the output statevector returned.

Parameters:

instruction (qiskit.circuit.Instruction or QuantumCircuit) – instruction or circuit

Returns:

the final density matrix.

Return type:

DensityMatrix

Raises:

QiskitError – if the instruction contains invalid instructions for density matrix simulation.

static from_int(i, dims)[source]#

Return a computational basis state density matrix.

Parameters:

  • i (int) – the basis state element.

  • dims (int or tuple or list) – The subsystem dimensions of the statevector (See additional information).

Returns:

The computational basis state \(|i\rangle\!\langle i|\).

Return type:

DensityMatrix

Additional Information:

The dims kwarg can be an integer or an iterable of integers.

  • Iterable – the subsystem dimensions are the values in the list with the total number of subsystems given by the length of the list.

  • Int – the integer specifies the total dimension of the state. If it is a power of two the state will be initialized as an N-qubit state. If it is not a power of two the state will have a single d-dimensional subsystem.

classmethod from_label(label)[source]#

Return a tensor product of Pauli X,Y,Z eigenstates.

Table 2 Single-qubit state labels#

Label

Statevector

"0"

\(\begin{pmatrix} 1 & 0 \\ 0 & 0 \end{pmatrix}\)

"1"

\(\begin{pmatrix} 0 & 0 \\ 0 & 1 \end{pmatrix}\)

"+"

\(\frac{1}{2}\begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}\)

"-"

\(\frac{1}{2}\begin{pmatrix} 1 & -1 \\ -1 & 1 \end{pmatrix}\)

"r"

\(\frac{1}{2}\begin{pmatrix} 1 & -i \\ i & 1 \end{pmatrix}\)

"l"

\(\frac{1}{2}\begin{pmatrix} 1 & i \\ -i & 1 \end{pmatrix}\)
Parameters:

label (string) – a eigenstate string ket label (see table for allowed values).

Returns:

The N-qubit basis state density matrix.

Return type:

DensityMatrix

Raises:

QiskitError – if the label contains invalid characters, or the length of the label is larger than an explicitly specified num_qubits.

is_valid(atol=None, rtol=None)[source]#

Return True if trace 1 and positive semidefinite.

measure(qargs: list | None = None) → tuple[source]#

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 state for the corresponding outcome.

Return type:

tuple

metadata()[source]#

Return result metadata of an operation that executed lastly.

partial_transpose(qargs: list[int]) → DensityMatrix[source]#

Return partially transposed density matrix.

Parameters:

qargs (list) – The subsystems to be transposed.

Returns:

The partially transposed density matrix.

Return type:

DensityMatrix

probabilities(qargs: None | list[int] = None, decimals: None | int = None) → np.ndarray[source]#

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

Examples

Consider a 2-qubit product state \(\rho=\rho_1\otimes\rho_0\) with \(\rho_1=|+\rangle\!\langle+|\), \(\rho_0=|0\rangle\!\langle0|\).

from qiskit.quantum_info import DensityMatrix

rho = DensityMatrix.from_label('+0')

# Probabilities for measuring both qubits
probs = rho.probabilities()
print('probs: {}'.format(probs))

# Probabilities for measuring only qubit-0
probs_qubit_0 = rho.probabilities([0])
print('Qubit-0 probs: {}'.format(probs_qubit_0))

# Probabilities for measuring only qubit-1
probs_qubit_1 = rho.probabilities([1])
print('Qubit-1 probs: {}'.format(probs_qubit_1))

probs: [0.5 0.  0.5 0. ]
Qubit-0 probs: [1. 0.]
Qubit-1 probs: [0.5 0.5]

We can also permute the order of qubits in the qargs list to change the qubit position in the probabilities output

from qiskit.quantum_info import DensityMatrix

rho = DensityMatrix.from_label('+0')

# Probabilities for measuring both qubits
probs = rho.probabilities([0, 1])
print('probs: {}'.format(probs))

# Probabilities for measuring both qubits
# but swapping qubits 0 and 1 in output
probs_swapped = rho.probabilities([1, 0])
print('Swapped probs: {}'.format(probs_swapped))

probs: [0.5 0.  0.5 0. ]
Swapped probs: [0.5 0.5 0.  0. ]
probabilities_dict(qargs: None | list = None, decimals: None | int = None) → dict[source]#

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 (ket) form.

Return type:

dict

purity()[source]#

Return the purity of the quantum state.

reset(qargs=None)[source]#

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:

DensityMatrix

Additional Information:

If all subsystems are reset this will return the ground state on all subsystems. If only a some subsystems are reset this function will perform evolution by the reset SuperOp of the reset subsystems.

reverse_qargs() → DensityMatrix[source]#

Return a DensityMatrix with reversed subsystem ordering.

For a tensor product state this is equivalent to reversing the order of tensor product subsystems. For a density matrix \(\rho = \rho_{n-1} \otimes ... \otimes \rho_0\) the returned state will be \(\rho_0 \otimes ... \otimes \rho_{n-1}\).

Returns:

the state with reversed subsystem order.

Return type:

DensityMatrix

sample_counts(shots: int, qargs: None | list = None) → Counts[source]#

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(shots, qargs=None)[source]#

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 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.

seed(value=None)[source]#

Set the seed for the quantum state RNG.

tensor(other)[source]#

Return the tensor product state self ⊗ other. :param other: a quantum state object. :type other: AerDensityMatrix

Returns:

the tensor product operator self ⊗ other.

Return type:

AerDensityMatrix

Raises:

QiskitError – if other is not a quantum state.

to_dict(decimals: None | int = None) → dict[source]#

Convert the density matrix to dictionary form.

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:

decimals (None or int) – the number of decimal places to round values. If None no rounding is done (Default: None).

Returns:

the dictionary form of the DensityMatrix.

Return type:

dict

Examples

The ket-form of a 2-qubit density matrix \(rho = |-\rangle\!\langle -|\otimes |0\rangle\!\langle 0|\)

from qiskit.quantum_info import DensityMatrix

rho = DensityMatrix.from_label('-0')
print(rho.to_dict())

{
    '00|00': (0.4999999999999999+0j),
    '10|00': (-0.4999999999999999-0j),
    '00|10': (-0.4999999999999999+0j),
    '10|10': (0.4999999999999999+0j)
}

For non-qubit subsystems the integer range can go from 0 to 9. For example in a qutrit system

import numpy as np
from qiskit.quantum_info import DensityMatrix

mat = np.zeros((9, 9))
mat[0, 0] = 0.25
mat[3, 3] = 0.25
mat[6, 6] = 0.25
mat[-1, -1] = 0.25
rho = DensityMatrix(mat, dims=(3, 3))
print(rho.to_dict())

{'00|00': (0.25+0j), '10|10': (0.25+0j), '20|20': (0.25+0j), '22|22': (0.25+0j)}

For large subsystem dimensions delimiters are required. The following example is for a 20-dimensional system consisting of a qubit and 10-dimensional qudit.

import numpy as np
from qiskit.quantum_info import DensityMatrix

mat = np.zeros((2 * 10, 2 * 10))
mat[0, 0] = 0.5
mat[-1, -1] = 0.5
rho = DensityMatrix(mat, dims=(2, 10))
print(rho.to_dict())

{'00|00': (0.5+0j), '91|91': (0.5+0j)}
to_operator() → Operator[source]#

Convert to Operator

to_statevector(atol=None, rtol=None)[source]#

Return a statevector from a pure density matrix. :param atol: Absolute tolerance for checking operation validity. :type atol: float :param rtol: Relative tolerance for checking operation validity. :type rtol: float

Returns:

The pure density matrix’s corresponding statevector.

Corresponds to the eigenvector of the only non-zero eigenvalue.

Return type:

AerStatevector

Raises:

QiskitError – if the state is not pure.

trace()[source]#

Return the trace of the density matrix.