Tweak the parameter `p` of QAOA in qiskit

Question

I am solving a QUBO using QAOA. It works flawlessly with default parameters for smaller instances of the problem, but my RAM is saturated when I try to solve a problem of size 15. I suspect this can be resolved by changing the parameter p. Don't mind if it generates a wrong result as output, at least don't wanna run out of resources and end abruptly. I even checked with different simulators, but it didn't work. Mainly, want to know how to play around with the number of layers p.

Here's the code for reference:

from qiskit import Aer
from qiskit.aqua import aqua_globals, QuantumInstance
from qiskit.aqua.algorithms import QAOA
from qiskit.optimization import QuadraticProgram

qp=QuadraticProgram()
qp.from_ising(op, offset, linear=True)
aqua_globals.random_seed = 123
quantum_instance = QuantumInstance(Aer.get_backend('aer_simulator'),
                               seed_simulator=aqua_globals.random_seed,
                               seed_transpiler=aqua_globals.random_seed)
qaoa_mes = QAOA(quantum_instance=quantum_instance, initial_point=[0., 0.])
qaoa = MinimumEigenOptimizer(qaoa_mes)
result = qaoa.solve(qubo)

Also, how to get the circuit?

Answer 1

You can set p when you create the QAOA instance e.g. (without explicitly specifying a value it defaults to 1)

qaoa_mes = QAOA(quantum_instance=quantum_instance, p=5, initial_point=[0., 0.])

you can refer to the API ref. documentation for QAOA here https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.QAOA.html

Note: the above link to to the now deprecated Aqua that you are using. When you migrate off Aqua the moved/refactored QAOA is here https://qiskit.org/documentation/stubs/qiskit.algorithms.QAOA.html - as we normally use reps for the number of layers in circuits etc p was renamed to reps but as noted it still performs the same function.