146 citations · 246 across the 14 of their papers we have counts for
14 papers
Persistent homology elucidates hierarchical structures responsible for mechanical properties in covalent amorphous solids
Emi Minamitani, Takenobu Nakamura, Ippei Obayashi +1
Understanding how atomic-level structures govern the mechanical properties of amorphous materials remains a fundamental challenge in solid-state physics. Under mechanical loading,…
Error evaluation of partial scattering functions obtained from contrast variation small-angle neutron scattering
Koichi Mayumi, Tatsuro Oda, Shinya Miyajima +2
Contrast variation small-angle neutron scattering (CV-SANS) is a powerful tool to evaluate the structure of multi-component systems by decomposing scattering intensities measur…
Refinement of Interval Approximations for Fully Commutative Quivers
Yasuaki Hiraoka, Ken Nakashima, Ippei Obayashi +1
A fundamental challenge in multiparameter persistent homology is the absence of a complete and discrete invariant. To address this issue, we propose an enhanced framework that real…
Persistent homology analysis with nonnegative matrix factorization for 3D voxel data of iron ore sinters
Ippei Obayashi, Masao Kimura
This paper proposes a data analysis method using persistent homology and nonnegative matrix factorization. A concatenated persistence image technique is used to extract coexisting…
Persistent homology-based descriptor for machine-learning potential of amorphous structures
Emi Minamitani, Ippei Obayashi, Koji Shimizu +1
High-accuracy prediction of the physical properties of amorphous materials is challenging in condensed-matter physics. A promising method to achieve this is machine-learning potent…
Persistent Homology Analysis for Materials Research and Persistent Homology Software: HomCloud
Ippei Obayashi, Takenobu Nakamura, Yasuaki Hiraoka
This paper introduces persistent homology, which is a powerful tool to characterize the shape of data using the mathematical concept of topology. We explain the fundamental idea of…