class_docstr: Single-qubit bit flip (Pauli :math:`X`) error channel.
  
  This channel is modelled by the following Kraus matrices:
  
  .. math::
      K_0 = \sqrt{1-p} \begin{bmatrix}
              1 & 0 \\
              0 & 1
              \end{bmatrix}
  
  .. math::
      K_1 = \sqrt{p}\begin{bmatrix}
              0 & 1  \\
              1 & 0
              \end{bmatrix}
  
  where :math:`p \in [0, 1]` is the probability of a bit flip (Pauli :math:`X` error).
  
  **Details:**
  
  * Number of wires: 1
  * Number of parameters: 1
  
  Args:
      p (float): The probability that a bit flip error occurs.
      wires (Sequence[int] or int): the wire the channel acts on
      id (str or None): String representing the operation (optional)
class_docstr_tok: ["Single-qubit","bit","flip","(","Pauli",":","math",":","`","X","`",")","error","channel",".","This","channel","is","modelled","by","the","following","Kraus","matrices",":","..","math",":",":","K_0","=","\\sqrt","{","1-p","}","\\begin","{","bmatrix","}","1","&","0","\\\\","0","&","1","\\end","{","bmatrix","}","..","math",":",":","K_1","=","\\sqrt","{","p","}","\\begin","{","bmatrix","}","0","&","1","\\\\","1","&","0","\\end","{","bmatrix","}","where",":","math",":","`","p","\\in","[","0",",","1","]","`","is","the","probability","of","a","bit","flip","(","Pauli",":","math",":","`","X","`","error",")",".","*","*","Details",":","*","*","*","Number","of","wires",":","1","*","Number","of","parameters",":","1","Args",":","p","(","float",")",":","The","probability","that","a","bit","flip","error","occurs",".","wires","(","Sequence","[","int","]","or","int",")",":","the","wire","the","channel","acts","on","id","(","str","or","None",")",":","String","representing","the","operation","(","optional",")"]
docstr: Kraus matrices representing the BitFlip channel.
  
  Args:
      p (float): probability that a bit flip error occurs
  
  Returns:
      list (array): list of Kraus matrices
  
  **Example**
  
  >>> qml.BitFlip.compute_kraus_matrices(0.5)
  [array([[0.70710678, 0.        ], [0.        , 0.70710678]]),
   array([[0.        , 0.70710678], [0.70710678, 0.        ]])]
code: def compute_kraus_matrices(p):  # pylint:disable=arguments-differ
      """Kraus matrices representing the BitFlip channel.
  
      Args:
          p (float): probability that a bit flip error occurs
  
      Returns:
          list (array): list of Kraus matrices
  
      **Example**
  
      >>> qml.BitFlip.compute_kraus_matrices(0.5)
      [array([[0.70710678, 0.        ], [0.        , 0.70710678]]),
       array([[0.        , 0.70710678], [0.70710678, 0.        ]])]
      """
      if not np.is_abstract(p) and not 0.0 <= p <= 1.0:
          raise ValueError("p must be in the interval [0,1]")
  
      K0 = np.sqrt(1 - p + np.eps) * np.convert_like(
          np.cast_like(np.eye(2), p), p
      )
      K1 = np.sqrt(p + np.eps) * np.convert_like(
          np.cast_like(np.array([[0, 1], [1, 0]]), p), p
      )
      return [K0, K1]
  
imports: import warnings
  import pennylane.math
  from pennylane.operation import AnyWires, Channel
label_desc: Use image node_id 2 for calling the BitFlip obj's underlying member method code with example usage: obj.compute_kraus_matrices(p) and returns: list