laurencap
commented
7 months ago Hi @Thevendran. I was able to successfully run your code on a simulator backend. ~The Rigetti device is not available right now, so I plan to try reproducing the error on OQC tomorrow.~ Edit: I can repro without device availability. I'm looking into it.
For the record, here is the code I ran:
from qiskit.primitives import BackendSampler
from qiskit_algorithms.minimum_eigensolvers import QAOA
from qiskit_algorithms.optimizers import COBYLA
from qiskit_optimization.algorithms import MinimumEigenOptimizer
from qiskit_optimization.problems import QuadraticProgram
from qiskit_optimization.translators import from_docplex_mp
from qiskit_braket_provider import AWSBraketProvider, BraketLocalBackend
from docplex.mp.model import Model
mdl = Model("docplex model")
x0 = mdl.binary_var("x0")
x1 = mdl.binary_var("x1")
x2 = mdl.binary_var("x2")
mdl.minimize(-30*x0**2 + 14*x0*x1 + 14*x0*x2 - 35*x1**2 + 14*x1*x2 - 29*x2**2)
mod = from_docplex_mp(mdl)
sampler = BackendSampler(
# backend=AWSBraketProvider().get_backend("Lucy"),
backend=BraketLocalBackend(),
skip_transpilation=False,
options={"shots": 100}
)
qaoa = QAOA(sampler=sampler, optimizer=COBYLA())
qaoa_solver = MinimumEigenOptimizer(qaoa)
result = qaoa_solver.solve(mod)with the local backend, result gives: <MinimumEigenOptimizationResult: fval=-52.0, x0=1.0, x1=1.0, x2=1.0, status=SUCCESS>.
rmshaffer
yitchen-tim
jcjaskula-aws
Hi.
I am facing issues in running QAOA algorithm against Rigetti backend. Following is the optimization code that I am using.
sampler = BackendSampler( backend=AWSBraketProvider().get_backend("Aspen-M-3"), skip_transpilation=False, options={"shots": 100} ) qaoa = QAOA(sampler=sampler, optimizer=COBYLA()) qaoa_solver = MinimumEigenOptimizer(qaoa) result = qaoa_solver.solve(qp)
I am facing the following 2 issues:
Issue #1 When the number of binary variables is more than 2, I am getting the following error:
Observable's qubit count 1 and the size of the target qubit set QubitSet([Qubit(4), Qubit(0)]) must be equalExample quadratic function that triggered the issue :
Minimize -30*x0^2 + 14*x0*x1 + 14*x0*x2 - 35*x1^2 + 14*x1*x2 - 29*x2^2Issue #2 As the number of binary variables increases gradually (for ex. 10 variables), I am getting the following different error:
QiskitError: "Cannot unroll the circuit to the given basis, dict_keys(['measure', 'cz', 'cx', 'cp', 'h', 'id', 'p', 'rx', 'ry', 'rz', 's', 'sdg', 'swap', 't', 'tdg', 'x', 'y', 'z']). Instruction measure not found in equivalence library and no rule found to expand."Example quadratic function that triggered the issue:
Minimize -36*x0^2 + 16*x0*x1 + 16*x0*x2 + 16*x0*x3 + 16*x0*x4 + 16*x0*x5 + 16*x0*x6 - 41*x1^2 + 16*x1*x2 + 16*x1*x3 + 16*x1*x4 + 16*x1*x7 + 16*x1*x8 - 43*x2^2 + 16*x2*x3 + 16*x2*x5 + 16*x2*x7 + 16*x2*x9 - 42*x3^2 + 16*x3*x6 + 16*x3*x8 + 16*x3*x9 - 35*x4^2 + 16*x4*x5 + 16*x4*x6 + 16*x4*x7 + 16*x4*x8 - 42*x5^2 + 16*x5*x6 + 16*x5*x7 + 16*x5*x9 - 40*x6^2 + 16*x6*x8 + 16*x6*x9 - 40*x7^2 + 16*x7*x8 + 16*x7*x9 - 35*x8^2 + 16*x8*x9 - 41*x9^2Please help suggest a solution.