activity
20242026
collaborators

10 papers

quant-ph2026

Transformers as Intrinsic Optimizers for Quantum Approximate Optimization Algorithm

Kuan-Cheng Chen, Xiaotian Xu, Hiromichi Matsuyama +3

The Quantum Approximate Optimization Algorithm (QAOA) is a leading variational framework for combinatorial optimization on noisy intermediate-scale quantum hardware, but its practi…

quant-ph2026

Quantum hardware noise learning via differentiable Kraus representation on tensor networks

Ryo Sakai, Yu Yamashiro

We present a method for learning quantum hardware noise from a measurement distribution of a single device experiment. Each noise channel is represented by automatically differenti…

quant-ph2026

Recursive QAOA for Interference-Aware Resource Allocation in Wireless Networks

Kuan-Cheng Chen, Hiromichi Matsuyama, Wei-hao Huang +1

Discrete radio resource management problems in dense wireless networks are naturally cast as quadratic unconstrained binary optimization (QUBO) programs but are difficult to solve…

quant-ph2025

Transferring linearly fixed QAOA angles: performance and real device results

Ryo Sakai, Hiromichi Matsuyama, Wai-Hong Tam +1

Quantum Approximate Optimization Algorithm (QAOA) enables solving combinatorial optimization problems on quantum computers by optimizing variational parameters for quantum circuits…

quant-ph2025

Sampling-based Quantum Optimization Algorithm with Quantum Relaxation

Hiromichi Matsuyama, Yu Yamashiro

Variational Quantum Algorithm (VQA) is a hybrid algorithm for noisy quantum devices. However, statistical fluctuations and physical noise degrade the solution quality, so it is dif…

quant-ph2025

Enhancing NDAR with Delay-Gate-Induced Amplitude Damping

Wai-Hong Tam, Hiromichi Matsuyama, Ryo Sakai +1

The Noise-Directed Adaptive Remapping (NDAR) method utilizes amplitude damping noise to enhance the performance of quantum optimization algorithms. NDAR alternates between explorat…

quant-ph2025

Solving Capacitated Vehicle Routing Problem with Quantum Alternating Operator Ansatz and Column Generation

Wei-hao Huang, Hiromichi Matsuyama, Yu Yamashiro

This study proposes a hybrid quantum-classical approach to solving the Capacitated Vehicle Routing Problem (CVRP) by integrating the Column Generation (CG) method with the Quantum…

quant-ph2024

Quantum Local Search for Traveling Salesman Problem with Path-Slicing Strategy

Chen-Yu Liu, Hiromichi Matsuyama, Wei-hao Huang +1

We present novel path-slicing strategies integrated with quantum local search to optimize solutions for the Traveling Salesman Problem (TSP), addressing the limitations of current…

quant-ph2024

Efficient Internal Strategies in Quantum Relaxation based Branch-and-Bound

Hiromichi Matsuyama, Wei-hao Huang, Kohji Nishimura +1

A combinatorial optimization problem is to find an optimal solution under the constraints. This is one of the potential applications for quantum computers. Quantum Random Access Op…

quant-ph2024

Linearly simplified QAOA parameters and transferability

Ryo Sakai, Hiromichi Matsuyama, Wai-Hong Tam +2

Quantum Approximate Optimization Algorithm (QAOA) provides a way to solve combinatorial optimization problems using quantum computers. QAOA circuits consist of time evolution opera…