4 papers
Geometric Quantum Physics Informed Neural Network
Wai-Hong Tam, Reza Safari, Hiromichi Matsuyama
Quantum physics-informed neural networks (QPINNs) have recently emerged as a promising framework for the solution of partial differential equations (PDEs), with several studies rep…
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…
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…