Minimum Eigen Optimizer Solve Function "list index out of range"

[OuCheng-Fu]

Informations

• Qiskit version: 0.43.0
• Python version: 3.9
• Operating system: Linux

What is the current behavior?

I try to solve a QUBO problem by QAOA, and implement it on Qiskit by this code

Implement the reduction of variables mentioned in the Adrew Lucas Paper

mdl_red = Model(name="TSP-Variable Reduction") m = n y = {(j, l): mdl_red.binaryvar(name=f"y{j}_{l}") for j in range(m) for l in range(m) if j!=0 and l!=0}

tsp_func_red = mdl_red.sum( 1.0 y[(j, l)] y[(w, (l + 1) % m)] for j in range(m) for w in range(m) for l in range(m) if j != w and j!=0 and l!=0 and w!=0 and (l+1)%m != 0)

mdl_red.minimize(tsp_func_red + y[(1, 1)] + y[(1, 5)] + y[(2, 1)] + y[(2, 5)] + y[(3, 1)] + y[(3, 5)] + y[(4, 1)] + y[(4, 5)] + y[(5, 1)] + y[(5, 5)]) for j in range(1,m): mdl_red.add_constraint(mdl_red.sum(y[(j, l)] for l in range(1,m)) == 1) for l in range(1,m): mdl_red.add_constraint(mdl_red.sum(y[(j, l)] for j in range(1,m)) == 1) qp_red = from_docplex_mp(mdl_red)

print(qp_red.prettyprint())

Construct Hamiltonian from TSP module

Output QUBO Hamiltonian

from qiskit_optimization.converters import QuadraticProgramToQubo qp2qubo_red = QuadraticProgramToQubo() qubo_red = qp2qubo_red.convert(qp_red) qubitOp_red, offset = qubo_red.to_ising() print("Offset:", offset) print("Ising Hamiltonian:") print(str(qubitOp_red))

from qiskit.utils import algorithm_globals from qiskit.algorithms.minimum_eigensolvers import QAOA, NumPyMinimumEigensolver from qiskit.algorithms.optimizers import COBYLA from qiskit.primitives import Sampler from qiskit_optimization.algorithms import ( MinimumEigenOptimizer, RecursiveMinimumEigenOptimizer, SolutionSample, OptimizationResultStatus, ) from qiskit_optimization import QuadraticProgram from qiskit.visualization import plot_histogram from typing import List, Tuple algorithm_globals.random_seed = 10598 qaoa_mes = QAOA(sampler=Sampler(), optimizer=COBYLA(), initial_point=[0.0, 0.0]) exact_mes = NumPyMinimumEigensolver()

qaoa = MinimumEigenOptimizer(qaoa_mes) # using QAOA exact_2 = MinimumEigenOptimizer(exact_mes) # using the exact classical numpy minimum eigen solver

exact_result_red = exact_2.solve(qubo_red) print(exact_result_red.prettyprint())

The bolded font code has the result

objective function value: 6.0 variable values: y_1_1=0.0, y_1_2=0.0, y_1_3=0.0, y_1_4=0.0, y_1_5=1.0, y_2_1=0.0, y_2_2=0.0, y_2_3=1.0, y_2_4=0.0, y_2_5=0.0, y_3_1=1.0, y_3_2=0.0, y_3_3=0.0, y_3_4=0.0, y_3_5=0.0, y_4_1=0.0, y_4_2=0.0, y_4_3=0.0, y_4_4=1.0, y_4_5=0.0, y_5_1=0.0, y_5_2=1.0, y_5_3=0.0, y_5_4=0.0, y_5_5=0.0 status: SUCCESS

However when I implement the code qaoa_result_red = qaoa.solve(qubo_red) print(qaoa_result_red)

It resulted in the error

IndexError Traceback (most recent call last) Cell In[21], line 1 ----> 1 qaoa_result_red = qaoa.solve(qubo_red) 2 print(qaoa_result_red.prettyprint())

File ~/.conda/envs/Qiskit/lib/python3.9/site-packages/qiskit_optimization/algorithms/minimum_eigenoptimizer.py:227, in MinimumEigenOptimizer.solve(self, problem) 224 # construct operator and offset 225 operator, offset = problem.to_ising() --> 227 return self._solveinternal(operator, offset, problem, problem)

File ~/.conda/envs/Qiskit/lib/python3.9/site-packages/qiskit_optimization/algorithms/minimum_eigen_optimizer.py:271, in MinimumEigenOptimizer._solve_internal(self, operator, offset, converted_problem, original_problem) 260 return MinimumEigenOptimizationResult( 261 x=None, 262 fval=None, (...) 267 min_eigen_solver_result=eigen_result, 268 ) 270 # translate result back to integers and eventually maximization --> 271 samples, best_raw = self._interpret_samples(original_problem, raw_samples, self._converters) 272 return cast( 273 MinimumEigenOptimizationResult, 274 self._interpret( (...) 282 ), 283 )

File ~/.conda/envs/Qiskit/lib/python3.9/site-packages/qiskit_optimization/algorithms/optimization_algorithm.py:522, in OptimizationAlgorithm._interpret_samples(cls, problem, raw_samples, converters) 516 samples.append(SolutionSample(x, fval, probability, status)) 518 sorted_samples = sorted( 519 samples, 520 key=lambda v: (v.status.value, problem.objective.sense.value * v.fval), 521 ) --> 522 best_raw = raw_samples[index[tuple(sorted_samples[0].x)]] 523 return sorted_samples, best_raw

IndexError: list index out of range

I tried to search the source code from https://qiskit.org/ecosystem/optimization/_modules/qiskit_optimization/algorithms/minimum_eigen_optimizer.html#MinimumEigenOptimizer.solve

I found the code from the source, and the error comes from samples, best_raw = self._interpret_samples(original_problem, raw_samples, self._converters) but I can't find the source of function _interpret_samples() Where is that function? What is the problem

Steps to reproduce the problem

Reference: https://qiskit.org/ecosystem/optimization/_modules/qiskit_optimization/algorithms/minimum_eigen_optimizer.html#MinimumEigenOptimizer.solve

https://github.com/Qiskit/qiskit-optimization/blob/stable/0.5/docs/tutorials/03_minimum_eigen_optimizer.ipynb

Reproduce it as my code mentioned above

What is the expected behavior?

I have tried the same problem on a graph of 4 vertices, and it should have the result like

objective function value: 6.0 variable values: y_1_1=0.0, y_1_2=0.0, y_1_3=0.0, y_1_4=0.0, y_1_5=1.0, y_2_1=0.0, y_2_2=0.0, y_2_3=1.0, y_2_4=0.0, y_2_5=0.0, y_3_1=1.0, y_3_2=0.0, y_3_3=0.0, y_3_4=0.0, y_3_5=0.0, y_4_1=0.0, y_4_2=0.0, y_4_3=0.0, y_4_4=1.0, y_4_5=0.0, y_5_1=0.0, y_5_2=1.0, y_5_3=0.0, y_5_4=0.0, y_5_5=0.0 status: SUCCESS

Suggested solutions

Where can I find the source code of the function? And what is the real issue?

[OuCheng-Fu]

I have tried it again on the example of 4 vertices with the same code,

qaoa_result_red = qaoa.solve(qubo_red) print(qaoa_result_red)

it worked on my Windows 10 computer as the picture However, when I try the same code on 6-vertex graph on a larger computer with 1.47TB memory, it ran for 15 hours (see picture below) and resulted in error message "list index out of range", like the following pictures How can I solve this problem? (By the way, it failed on my Windows 10 computer because it takes too much memory:)

[woodsp-ibm]

You should raise this as an issue on qiskit-optimization where the eigenoptimizer and tutorial are maintained. This repo is just for the set of tutorials for Qiskit around circuits and algorithms, i.e the set you can see here in this repo and any issues related to the applications e.g. optimization, nature, machine-learning and their respective tutorials should be raised in their repo.

[OuCheng-Fu]

You should raise this as an issue on qiskit-optimization where the eigenoptimizer and tutorial are maintained. This repo is just for the set of tutorials for Qiskit around circuits and algorithms, i.e the set you can see here in this repo and any issues related to the applications e.g. optimization, nature, machine-learning and their respective tutorials should be raised in their repo.

Thank you. I opened a new issue here: https://github.com/qiskit-community/qiskit-optimization/issues/532

[woodsp-ibm]

Thanks. I'll close this one here - I used to be able to transfer the issues from here but the application repos were recently moved from Qiskit to qiskit-community organization and I can no longer do that.