What is the superop simulator in Qiskit for?

If you have an ideal quantum circuit, you can easily get its superoperator representation using qiskit.quantum_info.SuperOp as follows,

qc = QuantumCircuit(1)
qc.x(0)

super_op = SuperOp(qc)
array_to_latex(super_op)

The output will be $$ left[begin{matrix} 0 & 0 & 0 & 1 0 & 0 & 1 & 0 0 & 1 & 0 & 0 1 & 0 & 0 & 0 end{matrix}right] $$

And to see how a quantum state is evolved by applying this operator:

rho1 = DensityMatrix.from_label('0')

rho2 = rho1.evolve(super_op)
rho2.draw('latex')

However, you can not use this method to get the superoperator representation of the circuit in the presence of errors. Instead, you can use superop simulator, which accepts a NoiseModel as a parameter

# Add save_superop instruction to save the simulator state to the returned results:
qc.save_superop()

# Get noise model:
provider = IBMQ.load_account()
backend = provider.get_backend('ibmq_16_melbourne')
noise_model = NoiseModel.from_backend(backend)

# Get the superoperator:
noisy_simulator = AerSimulator(method = 'superop', noise_model = noise_model)
result = noisy_simulator.run(qc).result()
super_op_array = result.data()['superop']
array_to_latex(super_op_array)

And in this case the output will be somthing like that: $$ left[begin{matrix} 0.00094 & 0 & 0 & 0.99979 0 & 0 & 0.99907 & 0 0 & 0.99907 & 0 & 0 0.99906 & 0 & 0 & 0.00021 end{matrix}right] $$