JSAI2022

Presentation information

General Session

General Session » GS-1 Fundamental AI, theory

[4K1-GS-1] Fundamental AI, theory: algorithm

Fri. Jun 17, 2022 10:00 AM - 11:40 AM Room K (Room K)

座長:戸田 貴久(電気通信大学)[現地]

11:00 AM - 11:20 AM

[4K1-GS-1-04] A Study on Variational Quantum Algorithms for Constrained Combinatorial Optimization

〇Hyakka Nakada1, Kotaro Tanahashi1 (1. Recruit Co., Ltd.)

[[Online]]

Keywords:Variational Quantum Algorithm, Combinatorial Optimization, Multiple Constraints

Combinatorial optimization has many real-world applications. As the amount of data circulation increases due to technology development, high-performance computers for larger-scale combinatorial optimizations are required. Currently, quantum computers are attracting attention as the solvers for such problems. Especially, variational quantum algorithms (VQA) are expected to work on noisy intermediate-scale quantum devices. In VQA, quantum circuits to sample combinatorial solutions are obtained by learning their variational parameters. However, in constrained optimization problems, there is a possibility that infeasible solutions appear because VQA is likely to fail to learn the proper parameters. In this report, we propose a new architecture for circuit models to enhance the learning ability. The circuit consists of three layers: initializing-layer to encode the approximate solutions, learning-constraint-layer to search for the feasible ones, and minimizing-objective-layer for the global ones. We carried out Qiskit simulations and found that proposed method showed high possibilities to sample feasible and global solutions.

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