code: 
  
  import doctest
  
  import projectq
  from projectq.ops import H, Measure
  
  
  def       __a       (   SCREAMING_SNAKE_CASE      )      ->     int:
  
  
  
  
  
  
      '''simple docstring'''
      __UpperCAmelCase									=			quantum_engine.allocate_qubit()
      H | qubit
      Measure | qubit
      return int(SCREAMING_SNAKE_CASE      )
  
  
  if __name__ == "__main__":
         doctest.testmod()
  
         # initialises a new quantum backend
         A_		:			str										=   projectq.MainEngine()
  
         # Generate a list of 10 random numbers
         A_		:			Tuple										=   [get_random_number(quantum_engine) for _ in range(10)]
  
         # Flushes the quantum engine from memory
         quantum_engine.flush()
  
         print('Random numbers', random_numbers_list)
  
  
  
  
  
style_context: 
  
  import numpy as np
  
  
  def       __a       (   SCREAMING_SNAKE_CASE      )      ->     Tuple:
  
  
  
  
  
  
      '''simple docstring'''
      __UpperCAmelCase					,     __UpperCAmelCase									=			a.shape
      __UpperCAmelCase									=			min(SCREAMING_SNAKE_CASE       ,   SCREAMING_SNAKE_CASE      )
      __UpperCAmelCase									=			np.eye(SCREAMING_SNAKE_CASE      )
      __UpperCAmelCase									=			a.copy()
  
      for k in range(t - 1      ):
          # select a column of modified matrix A':
          __UpperCAmelCase									=			r[k:, [k]]
          # construct first basis vector
          __UpperCAmelCase									=			np.zeros_like(SCREAMING_SNAKE_CASE      )
          __UpperCAmelCase									=			1.0
          # determine scaling factor
          __UpperCAmelCase									=			np.linalg.norm(SCREAMING_SNAKE_CASE      )
          # construct vector v for Householder reflection
          __UpperCAmelCase									=			x + np.sign(x[0]      ) * alpha * ea
          v /= np.linalg.norm(SCREAMING_SNAKE_CASE      )
  
          # construct the Householder matrix
          __UpperCAmelCase									=			np.eye(m - k      ) - 2.0 * v @ v.T
          # pad with ones and zeros as necessary
          __UpperCAmelCase									=			np.block([[np.eye(SCREAMING_SNAKE_CASE      ), np.zeros((k, m - k)      )], [np.zeros((m - k, k)      ), q_k]]      )
  
          __UpperCAmelCase									=			q @ q_k.T
          __UpperCAmelCase									=			q_k @ r
  
      return q, r
  
  
  if __name__ == "__main__":
         import doctest
  
         doctest.testmod()
  
  
  
  
  