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T. Miyazaki

37 papers hereh-index 232.5k citations136 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author16
  • last author20

Across the 36 of 37 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci20
  • cond-mat.str-el5
  • physics.comp-ph3
  • cond-mat.mes-hall2
  • cond-mat.supr-con2
  • nucl-ex2
same name
  • T. Miyazaki — 21 papers, h 11
  • T. Miyazaki — 15 papers, h 10
  • T. Miyazaki — 6 papers, h 5
  • T. Miyazaki — 5 papers, h 18
  • T. Miyazaki — 4 papers, h 8
  • T. Miyazaki — 4 papers, h 45

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
19972026
most citedO(N) methods in electronic structure calculations

537 citations · 2.1k across the 37 of their papers we have counts for

collaborators
Showing physics.comp-phShow all

3 papers · 1 filter

physics.comp-ph2020★ 4 cited

The pseudoatomic orbital basis: electronic accuracy and soft-mode distortions in ABO3​ perovskites

Jack S. Baker, Tsuyoshi Miyazki, David R. Bowler

The perovskite oxides are known to be susceptible to structural distortions over a long wavelength when compared to their parent cubic structures. From an ab initio simulation pers…

physics.comp-ph2020★ 124 cited

Large scale and linear scaling DFT with the CONQUEST code

Ayako Nakata, Jack Baker, Shereif Mujahed +8

We survey the underlying theory behind the large-scale and linear scaling DFT code, Conquest, which shows excellent parallel scaling and can be applied to thousands of atoms with e…

physics.comp-ph2018★ 12 cited

Machine learning forces trained by Gaussian process in liquid states: Transferability to temperature and pressure

Ryo Tamura, Jianbo Lin, Tsuyoshi Miyazaki

We study a generalization performance of the machine learning (ML) model to predict the atomic forces within the density functional theory (DFT). The targets are the Si and Ge sing…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.