





"""simple docstring"""


import qiskit

def      UpperCamelCase							(SCREAMING_SNAKE_CASE = 2     ):
						UpperCamelCase				:		List[Any]				   =			qubits

						# Using Aer's simulator
						UpperCamelCase				:		int				   =			qiskit.Aer.get_backend("""aer_simulator"""     )

						# Creating a Quantum Circuit acting on the q register
						UpperCamelCase				:		Dict				   =			qiskit.QuantumCircuit(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE     )

						# Adding a H gate on qubit 0 (now q0 in superposition)
						circuit.h(0     )

						for i in range(1							,     SCREAMING_SNAKE_CASE     ):
												# Adding CX (CNOT) gate
												circuit.cx(i - 1							,     SCREAMING_SNAKE_CASE     )

						# Mapping the quantum measurement to the classical bits
						circuit.measure(list(range(SCREAMING_SNAKE_CASE     )     )							,     list(range(SCREAMING_SNAKE_CASE     )     )     )

						# Now measuring any one qubit would affect other qubits to collapse
						# their super position and have same state as the measured one.

						# Executing the circuit on the simulator
						UpperCamelCase				:		Optional[int]				   =			qiskit.execute(SCREAMING_SNAKE_CASE							,     SCREAMING_SNAKE_CASE							,     shots=1000     )

						return job.result().get_counts(SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
		print(f'''Total count for various states are: {quantum_entanglement(3)}''')










_lowercase		:  Optional[Any]			       ="""
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_lowercase		:  Union[str, Any]			       =[{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowercase		:  List[Any]			       ={
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}
