def decompose_clifford(clifford):
    """Decompose a Clifford operator into a QuantumCircuit.

    Args:
        clifford (Clifford): a clifford operator.

    Return:
        QuantumCircuit: a circuit implementation of the Clifford.
    """
    # Compose a circuit which we will convert to an instruction
    circuit = QuantumCircuit(clifford.num_qubits, name=str(clifford))

    # Make a copy of Clifford as we are going to do row reduction to
    # reduce it to an identity
    clifford_cpy = clifford.copy()

    for i in range(clifford.num_qubits):
        # put a 1 one into position by permuting and using Hadamards(i,i)
        _set_qubit_x_true(clifford_cpy, circuit, i)
        # make all entries in row i except ith equal to 0
        # by using phase gate and CNOTS
        _set_row_x_zero(clifford_cpy, circuit, i)
        # treat Zs
        _set_row_z_zero(clifford_cpy, circuit, i)

    for i in range(clifford.num_qubits):
        if clifford_cpy.destabilizer.phase[i]:
            _append_z(clifford_cpy, i)
            circuit.z(i)
        if clifford_cpy.stabilizer.phase[i]:
            _append_x(clifford_cpy, i)
            circuit.x(i)
    # Next we invert the circuit to undo the row reduction and return the
    # result as a gate instruction
    return circuit.inverse()
示例#2
0
    def reset(self, qargs=None):
        """Reset state or subsystems to the 0-state.

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

        Returns:
            StabilizerState: the reset state.

        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 :meth:`seed` method.
        """
        # Resetting all qubits does not require sampling or RNG
        if qargs is None:
            return StabilizerState(
                Clifford(np.eye(2 * self.clifford.num_qubits)))

        randbits = self._rng.integers(2, size=len(qargs))
        ret = self.copy()

        for bit, qubit in enumerate(qargs):
            # Apply measurement and get classical outcome
            outcome = ret._measure_and_update(qubit, randbits[bit])

            # Use the outcome to apply X gate to any qubits left in the
            # |1> state after measure, then discard outcome.
            if outcome == 1:
                _append_x(ret.clifford, qubit)

        return ret
示例#3
0
def decompose_clifford_greedy(clifford):
    """Decompose a Clifford operator into a QuantumCircuit.

    Args:
        clifford (Clifford): a clifford operator.

    Return:
        QuantumCircuit: a circuit implementation of the Clifford.

    Raises:
        QiskitError: if symplectic Gaussian elimination fails.
    """

    num_qubits = clifford.num_qubits
    circ = QuantumCircuit(num_qubits, name=str(clifford))
    qubit_list = list(range(num_qubits))
    clifford_cpy = clifford.copy()

    # Reducing the original Clifford to identity
    # via symplectic Gaussian elimination
    while len(qubit_list) > 0:
        clifford_cpy_inv = clifford_cpy.adjoint()

        list_greedy_cost = []
        for qubit in qubit_list:
            cliff_ox = clifford_cpy.copy()
            _append_x(cliff_ox, qubit)
            cliff_ox = cliff_ox.compose(clifford_cpy_inv)

            cliff_oz = clifford_cpy.copy()
            _append_z(cliff_oz, qubit)
            cliff_oz = cliff_oz.compose(clifford_cpy_inv)

            list_pairs = []
            pauli_count = 0

            # Compute the CNOT cost in order to find the qubit with the minimal cost
            for i in qubit_list:
                typeq = _from_pair_cliffs_to_type(cliff_ox, cliff_oz, i)
                list_pairs.append(typeq)
                pauli_count += 1
            cost = _compute_greedy_cost(list_pairs)
            list_greedy_cost.append([cost, qubit])

        _, min_qubit = (sorted(list_greedy_cost))[0]

        # Gaussian elimination step for the qubit with minimal CNOT cost
        cliff_ox = clifford_cpy.copy()
        _append_x(cliff_ox, min_qubit)
        cliff_ox = cliff_ox.compose(clifford_cpy_inv)

        cliff_oz = clifford_cpy.copy()
        _append_z(cliff_oz, min_qubit)
        cliff_oz = cliff_oz.compose(clifford_cpy_inv)

        # Compute the decoupling operator of cliff_ox and cliff_oz
        decouple_circ, decouple_cliff = _calc_decoupling(
            cliff_ox, cliff_oz, qubit_list, min_qubit, num_qubits)
        circ = circ.compose(decouple_circ)

        # Now the clifford acts trivially on min_qubit
        clifford_cpy = decouple_cliff.adjoint().compose(clifford_cpy)
        qubit_list.remove(min_qubit)

    # Add the phases (Pauli gates) to the Clifford circuit
    for qubit in range(num_qubits):
        stab = clifford_cpy.stabilizer.phase[qubit]
        destab = clifford_cpy.destabilizer.phase[qubit]
        if destab and stab:
            circ.y(qubit)
        elif not destab and stab:
            circ.x(qubit)
        elif destab and not stab:
            circ.z(qubit)

    return circ