code: def pauli_eigs(n):
      r"""Eigenvalues for :math:`A^{\otimes n}`, where :math:`A` is
      Pauli operator, or shares its eigenvalues.
  
      As an example if n==2, then the eigenvalues of a tensor product consisting
      of two matrices sharing the eigenvalues with Pauli matrices is returned.
  
      Args:
          n (int): the number of qubits the matrix acts on
      Returns:
          list: the eigenvalues of the specified observable
      """
      if n == 1:
          return np.array([1, -1])
      return np.concatenate([pauli_eigs(n - 1), -pauli_eigs(n - 1)])
  
file_path: pennylane/pennylane/utils.py
imports: from collections.abc import Iterable
  import functools
  import inspect
  import numbers
  import numpy
  import pennylane
label_desc: Use image node_id 6 for calling a global function with example usage: pauli_eigs(n) and returns: np, np