def _tensor_product(self, other, reverse=False):
        """Return the tensor product channel.

        Args:
            other (QuantumChannel): a quantum channel subclass.
            reverse (bool): If False return self ⊗ other, if True return
                            if True return (other ⊗ self) [Default: False
        Returns:
            Kraus: the tensor product channel as a Kraus object.

        Raises:
            QiskitError: if other cannot be converted to a channel.
        """
        # Convert other to Kraus
        if not isinstance(other, Kraus):
            other = Kraus(other)

        # Get tensor matrix
        ka_l, ka_r = self._data
        kb_l, kb_r = other._data
        if reverse:
            input_dims = self.input_dims() + other.input_dims()
            output_dims = self.output_dims() + other.output_dims()
            kab_l = [np.kron(b, a) for a in ka_l for b in kb_l]
        else:
            input_dims = other.input_dims() + self.input_dims()
            output_dims = other.output_dims() + self.output_dims()
            kab_l = [np.kron(a, b) for a in ka_l for b in kb_l]
        if ka_r is None and kb_r is None:
            kab_r = None
        else:
            if ka_r is None:
                ka_r = ka_l
            if kb_r is None:
                kb_r = kb_l
            if reverse:
                kab_r = [np.kron(b, a) for a in ka_r for b in kb_r]
            else:
                kab_r = [np.kron(a, b) for a in ka_r for b in kb_r]
        data = (kab_l, kab_r)
        return Kraus(data, input_dims, output_dims)
Return the tensor product channel.

        Args:
            other (QuantumChannel): a quantum channel subclass.
            reverse (bool): If False return self ⊗ other, if True return
                            if True return (other ⊗ self) [Default: False
        Returns:
            Kraus: the tensor product channel as a Kraus object.

        Raises:
            QiskitError: if other cannot be converted to a channel.