Enhancing VQE Convergence for Optimization Problems with Problem-Specific Parameterized Quantum Circuits

• Published in: IEICE Transactions on Information and Systems Vol. E106.D; no. 11; pp. 1772 - 1782
• Main Authors: MATSUO, Atsushi, SUZUKI, Yudai, HAMAMURA, Ikko, YAMASHITA, Shigeru
• Format: Journal Article
• Language: English
• Published: Tokyo The Institute of Electronics, Information and Communication Engineers 01.11.2023; Japan Science and Technology Agency
• Subjects: Algorithms; Circuits; Convergence; Optimization; optimization problem; Parameterization; problem-specific parameterized quantum circuit; VQE algorithm
• ISSN: 0916-8532; 1745-1361
• DOI: 10.1587/transinf.2023EDP7071

The Variational Quantum Eigensolver (VQE) algorithm is gaining interest for its potential use in near-term quantum devices. In the VQE algorithm, parameterized quantum circuits (PQCs) are employed to prepare quantum states, which are then utilized to compute the expectation value of a given Hamiltonian. Designing efficient PQCs is crucial for improving convergence speed. In this study, we introduce problem-specific PQCs tailored for optimization problems by dynamically generating PQCs that incorporate problem constraints. This approach reduces a search space by focusing on unitary transformations that benefit the VQE algorithm, and accelerate convergence. Our experimental results demonstrate that the convergence speed of our proposed PQCs outperforms state-of-the-art PQCs, highlighting the potential of problem-specific PQCs in optimization problems.