activity
20242026
collaborators

5 papers

cond-mat.stat-mech2026

Geometric Characteristics of Subproblems in Ising-Machine-Assisted Large Neighborhood Search

Masashi Yamashita, Shu Tanaka

Large-scale quadratic unconstrained binary optimization (QUBO) formulations of constrained combinatorial optimization problems often exceed the input-size limit of present Ising ma…

cond-mat.stat-mech2025

Evaluating the Performance of Direct Higher-Order Formulations in Combinatorial Optimization Problems

Kazuki Ikeuchi, Yoshiki Matsuda, Shu Tanaka

Ising machines, including quantum annealing machines, are promising next-generation computers for combinatorial optimization problems. However, due to hardware limitations, most Is…

cond-mat.stat-mech2025

Quick design of feasible tensor networks for constrained combinatorial optimization

Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka

Quantum computers are expected to enable fast solving of large-scale combinatorial optimization problems. However, their limitations in fidelity and the number of qubits prevent th…

quant-ph2025

Inductive Construction of Variational Quantum Circuit for Constrained Combinatorial Optimization

Hyakka Nakada, Kotaro Tanahashi, Shu Tanaka

In this study, we propose a new method for constrained combinatorial optimization using variational quantum circuits. Quantum computers are considered to have the potential to solv…

cond-mat.stat-mech2024

Advantages of fixing spins in quantum annealing

Tomohiro Hattori, Hirotaka Irie, Tadashi Kadowaki +1

Quantum annealing can efficiently obtain solutions to combinatorial optimization problems. Size-reduction methods are used to treat large-scale combinatorial optimization problems…