Solving Graph Coloring Problems Using Feedback-Based Algorithm for Quantum Optimization
Abstract
The feedback-based algorithm for quantum optimization (FALQON), which is an extension of the quantum approximate optimization algorithm (QAOA), is a promising approach for finding approximate solutions to combinatorial optimization problems. The FALQON avoids the optimization of variational parameters by using information derived from iterative measurements. To solve a constrained combinatorial optimization problem, it is sometimes more efficient to use an XY mixer rather than the conventional X mixer. We applied the FALQON with the XY mixer to graph coloring and investigated the expectation value of the problem Hamiltonian, success probability of graph coloring, and fair sampling for several small-scale problems. The FALQON with the XY mixer exhibited better performance than that with the X mixer.
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BibTeX
@misc{kawatomi2026solving,
title = {{Solving Graph Coloring Problems Using Feedback-Based Algorithm for Quantum Optimization}},
author = {Yuika Kawatomi and Yukina Tatsuta and Kazue Kudo},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.30991},
eprint = {2609.30991},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.30991},
}
RIS
TY - UNPB
TI - Solving Graph Coloring Problems Using Feedback-Based Algorithm for Quantum Optimization
AU - Yuika Kawatomi
AU - Yukina Tatsuta
AU - Kazue Kudo
PY - 2026
DA - 2026/09/25
PB - arXiv
DO - 10.48550/arxiv.2609.30991
UR - https://arxiv.org/abs/2609.30991
AB - The feedback-based algorithm for quantum optimization (FALQON), which is an extension of the quantum approximate optimization algorithm (QAOA), is a promising approach for finding approximate solutions to combinatorial optimization problems. The FALQON avoids the optimization of variational parameters by using information derived from iterative measurements. To solve a constrained combinatorial optimization problem, it is sometimes more efficient to use an XY mixer rather than the conventional X mixer. We applied the FALQON with the XY mixer to graph coloring and investigated the expectation value of the problem Hamiltonian, success probability of graph coloring, and fair sampling for several small-scale problems. The FALQON with the XY mixer exhibited better performance than that with the X mixer.
ER -