4 papers
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…
Tensor Network Generator-Enhanced Optimization for Traveling Salesman Problem
Ryo Sakai, Chen-Yu Liu
We present an application of the tensor network generator-enhanced optimization (TN-GEO) framework to address the traveling salesman problem (TSP), a fundamental combinatorial opti…
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…
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…