Research on an efficient quantum state readout method using overlap-based feature extraction has been published in Physical Review A.

Research revealing the origin of shallow hole traps induced by the GaOₓ interfacial layer at GaN/SiO₂ interfaces through first-principles calculations has been published in Physical Review Materials.

Collaborative research by Quemix and Sumitomo Rubber Industries on a Fourier space readout method for efficiently recovering functions encoded in quantum states has been published in Quantum Science and Technology. The method may preserve quantum computational speedups during the readout process.

Research on X-ray absorption spectrum (XAS) calculations using quantum computers has been published in Physical Review Applied. The work was conducted in collaboration with Honda R&D Co., Ltd. and was also presented at Q2B Tokyo 2025.

In collaboration with NGK Insulators, Quemix demonstrated the effectiveness of quantum computing in generating machine learning potentials. The study proposed an improved Equivariant Quantum Neural Network (QNN) and identified key technical challenges. The results are published in Physical Review A.

Published in Physical Review A, this study proposes AIQT—a quantum-native framework that enables efficient and expressive learning of quantum transformations by interpolating between multiple operations with only a few parameters.

A paper by Homma et al. from Quemix has been published in Physical Review B. This study proposes a parameter-free DFT-1/2 method that eliminates the need for additional self-consistent calculations, enabling efficient and accurate evaluation of semiconductor band gaps and defect levels.

https://journals.jps.jp/doi/10.7566/JPSJ.94.044802 A paper by Quemix has been published in the Journal of the Physical Society of Japan. In this study, we tackled the crystal structure problem (CSP) using a combination of factorization machines and quantum annealing (FMQA). CSP aims to optimally arrange atoms based on the chemical composition of materials. We examined the capability of FMQA to efficiently sample optimal crystal configurations by minimizing energy under differ

A paper by Huang Xinchi et al. of Quemix has been published in Quantum Information Processing.

A paper by Taichi Kosugi and colleagues from Quemix has been published in Physical Review A. In this study, a novel method is proposed for

Featured in PhysRevApplied: This research introduces a novel AI model that designs efficient quantum circuits for data encoding. Using a tra