YOSHIOKA Nobuyuki

YOSHIOKA Nobuyuki is a faculty member at The University of Tokyo, Department of PHY. His research focuses on Quantum Physics and Quantum Computing, with an emphasis on quantum algorithms, quantum advantage, quantum error mitigation, and computational methods in quantum many-body theory. He is also interested in the intersection of quantum information and natural sciences, as well as machine learning approaches to quantum systems. His work has been featured in several publications and collaborations, including joint efforts with IBM Quantum. He is currently an Associate Professor at The University of Tokyo and a PRESTO Researcher.

Nobuyuki Yoshioka is a researcher at the University of Tokyo specializing in Quantum Many-body Physics, Quantum Computing, and Computational Physics. His work focuses on developing quantum algorithms and computational methods to simulate complex quantum systems, including open quantum many-body systems and topological phases. Yoshioka's research explores the intersection of machine learning and quantum mechanics, such as using neural networks to model quantum states and improve quantum error mitigation. He also investigates quantum subspace expansion and Krylov diagonalization techniques for efficient quantum simulations. His contributions aim to advance quantum computing applications in materials science and condensed matter physics.