# Import necessary packages from qiskit import QuantumCircuit from qiskit.transpiler import PassManager from qiskit.transpiler.passes import * import qiskit.quantum_info as qi # Create a small quantum circuit qc = QuantumCircuit(4) qc.h(0) qc.cx(0,1) qc.cx(0,2) qc.cx(0,3) qc.measure_all() # Define a PassManager with the passes you want to use pm = PassManager([ Unroller(['u3', 'cx']), Depth(), FixedPoint('depth'), TranspilerError('unsupported gate'), OptimizationLevel(3), ]) # Apply the PassManager optimization passes to the circuit optimized_circuit = pm.run(qc) # Print the original circuit and the optimized circuit print(qc.draw()) print(optimized_circuit.draw())In this example, we created a small circuit consisting of four qubits and applied a series of passes to optimize its performance. We first defined a PassManager object that contains a set of optimization passes to be applied to the circuit. We then called the `run()` function on the PassManager object with the input circuit to obtain the optimized circuit. Finally, we printed both the original and optimized circuits using the `draw()` function. The package library used in this example is the Qiskit Python library.