Tomiya Akio 富谷昭夫

Researcher Number	50837185
Other IDs	https://orcid.org/0000-0001-9374-3716
Affiliation (Current)	2025: 東京女子大学, 現代教養学部, 専任講師
Affiliation (based on the past Project Information) *help	2025: 東京女子大学, 現代教養学部, 専任講師 2023 – 2025: 東京女子大学, 現代教養学部, 講師 2021 – 2023: 大阪国際工科専門職大学, 工科学部, 助教 2020: 国立研究開発法人理化学研究所, 仁科加速器科学研究センター, 基礎科学特別研究員
Review Section/Research Field	Principal Investigator Basic Section 15010:Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics / Transformative Research Areas, Section (II) Except Principal Investigator Basic Section 13030:Magnetism, superconductivity and strongly correlated systems-related / Transformative Research Areas, Section (II)
Keywords	Principal Investigator 格子QCD / 機械学習 / 素粒子物理学 / ニューラルネットワーク / マルコフ連鎖モンテカルロ法 / 負符号問題 / トランスフォーマー / 自己学習モンテカルロ法 / 格子ゲージ理論 / 素粒子理論 … More / 原子核物理学 / QCD相図 / 変分アルゴリズム / 量子コンピュータ / シュウィンガー模型 / 場の量子論 … More Except Principal Investigator 機械学習 / 強相関電子系 / 対称性 / ニューラルネットワーク / Transformer / 自己学習モンテカルロ法 / 物理学 Less

A Neural Network Approach to Quark-Free Lattice QCD for First-Principles StudiesPrincipal Investigator
- Principal Investigator
  
  富谷昭夫
- Project Period (FY)
  2025 – 2027
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 15010:Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics
- Research Institution
  Tokyo Woman's Christian University
Foundation of "Machine Learning Physics" --- Revolutionary Transformation of Fundame ntal Physics by A New Field Integrating Machine Learning and Physics
- Principal Investigator
  
  橋本幸士
- Project Period (FY)
  2022 – 2026
- Research Category
  
  Grant-in-Aid for Transformative Research Areas (A)
- Review Section
  
  Transformative Research Areas, Section (II)
- Research Institution
  Kyoto University
Effective models constructed by neural networks with symmetries
- Principal Investigator
  
  永井佑紀
- Project Period (FY)
  2022 – 2024
- Research Category
  
  Grant-in-Aid for Scientific Research (C)
- Review Section
  
  Basic Section 13030:Magnetism, superconductivity and strongly correlated systems-related
- Research Institution
  The University of Tokyo
  Japan Atomic Energy Agency
Unification of Computational Physics and Machine LearningPrincipal Investigator
- Principal Investigator
  
  富谷昭夫
- Project Period (FY)
  2022 – 2026
- Research Category
  
  Grant-in-Aid for Transformative Research Areas (A)
- Review Section
  
  Transformative Research Areas, Section (II)
- Research Institution
  Tokyo Woman's Christian University
  International Professional University of Technology in Osaka
Phase structure of gauge theories via digital quantum computersPrincipal Investigator
- Principal Investigator
  
  富谷昭夫
- Project Period (FY)
  2020 – 2024
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 15010:Theoretical studies related to particle-, nuclear-, cosmic ray and astro-physics
- Research Institution
  International Professional University of Technology in Osaka
  Institute of Physical and Chemical Research

All 2023 2022 2020

All Journal Article Presentation

[Journal Article] Sparse modeling approach to extract spectral functions with covariance of Euclidean-time correlators of lattice QCD2023
- Author(s)
  Junichi Takahashi, Hiroshi Ohno, Akio Tomiya
- Journal Title
  
  PoS LATTICE2023
  
  Volume: - Pages: 028-028
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-22K03539
[Journal Article] Self-learning Monte Carlo for non-Abelian gauge theory with dynamical fermions2023
- Author(s)
  Nagai Yuki、Tanaka Akinori、Tomiya Akio
- Journal Title
  
  Physical Review D
  
  Volume: 107 Issue: 5 Pages: 1-16
- DOI
  10.1103/physrevd.107.054501
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-22K03539, KAKENHI-PLANNED-22H05116, KAKENHI-PROJECT-18K11345, KAKENHI-PROJECT-18K13548, KAKENHI-PLANNED-22H05114
[Journal Article] Equivariant transformer is all you need2023
- Author(s)
  Akio Tomiya, Yuki Nagai
- Journal Title
  
  PoS LATTICE2023
  
  Volume: - Pages: 001-001
- DOI
  10.22323/1.453.0001
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-20K14479, KAKENHI-PLANNED-22H05112
[Journal Article] T-mu phase diagram using classical-quantum hybrid algorithm2023
- Author(s)
  Tomiya Akio
- Journal Title
  
  Proceedings of Science
  
  Volume: 430 Pages: 1-9
- DOI
  10.22323/1.430.0039
- Peer Reviewed / Open Access
- Data Source
  KAKENHI-PROJECT-22K03539, KAKENHI-PROJECT-20K14479
[Journal Article] Sparse modeling approach to extract spectral functions with covariance of Euclidean-time correlators of lattice QCD2023
- Author(s)
  Junichi Takahashi, Hiroshi Ohno, Akio Tomiya
- Journal Title
  
  PoS LATTICE2023
  
  Volume: - Pages: 028-028
- DOI
  10.22323/1.453.0028
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-20K14479, KAKENHI-PLANNED-22H05112
[Journal Article] Self-learning Monte Carlo with equivariant Transformer2023
- Author(s)
  Yuki Nagai, Akio Tomiya
- Journal Title
  
  -
  
  Volume: -
- Data Source
  KAKENHI-PLANNED-22H05112
[Journal Article] Equivariant transformer is all you need2023
- Author(s)
  Akio Tomiya, Yuki Nagai
- Journal Title
  
  PoS LATTICE2023
  
  Volume: - Pages: 001-001
- Peer Reviewed
- Data Source
  KAKENHI-PROJECT-22K03539
[Journal Article] GomalizingFlow.jl: A Julia package for Flow-based sampling algorithm for lattice field theory2022
- Author(s)
  Akio Tomiya, Satoshi Terasaki
- Journal Title
  
  arXiv(preprint)
  
  Volume: -
- Data Source
  KAKENHI-PLANNED-22H05112
[Journal Article] Use of Schwinger-Dyson equation in constructing an approximate trivializing map2022
- Author(s)
  Peter Boyle, Taku Izubuchi, Luchang Jin, Chulwoo Jung, Christoph Lehner, Nobuyuki Matsumoto, Akio Tomiya
- Journal Title
  
  PoS LATTICE2022
  
  Volume: -
- Peer Reviewed
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Machine learning and Lattice QCD2023
- Author(s)
  Akio Tomiya
- Organizer
  Challenges and opportunities in Lattice QCD simulations and related fields
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] "Application of Julia in Particle Physics -Toward Large-Scale Computations of Lattice QCD2023
- Author(s)
  Akio Tomiya
- Organizer
  , Julia in mathematics and physics
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Application of Julia in Particle Physics -Toward Large-Scale Computations of Lattice QCD-2023
- Author(s)
  Akio Tomiya
- Organizer
  20 June 2023, Julia in mathematics and physics
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] 機械学習を用いた格子QCDの進展2023
- Author(s)
  富谷昭夫
- Organizer
  日本物理学会2023年春季大会
- Data Source
  KAKENHI-ORGANIZER-22H05111
[Presentation] Self-learning Monte Carlo2023
- Author(s)
  Akio Tomiya
- Organizer
  Kick-off Meeting for the Accelerated Program in Fugaku
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Self-learning Monte Carlo2023
- Author(s)
  Akio Tomiya
- Organizer
  Kick-off Meeting for the Accelerated Program in Fugaku
- Data Source
  KAKENHI-PROJECT-20K14479
[Presentation] Self-learning Monte Carlo2023
- Author(s)
  Akio Tomiya
- Organizer
  Kick-off Meeting for the Accelerated Program in Fugaku
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] Development of machine learning methods for simulation of quantum theory of lattice fields2023
- Author(s)
  Akio Tomiya
- Organizer
  HPCI Computational Science Forum
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] Flow based sampling for 3- and 4-dim. model2023
- Author(s)
  Akio Tomiya
- Organizer
  The Future is non-perturbative
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] Flow based sampling for 3- and 4-dim. model", Akio Tomiya, 7 June 2023, The Future is non-perturbative2023
- Author(s)
  Akio Tomiya
- Organizer
  The Future is non-perturbative
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Equivariant transformer is all you need2023
- Author(s)
  Akio Tomiya
- Organizer
  Lattice2023
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K14479
[Presentation] Equivariant transformer is all you need2023
- Author(s)
  Akio Tomiya
- Organizer
  Lattice 2023
- Int'l Joint Research
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Use of GPT2023
- Author(s)
  Akio Tomiya
- Organizer
  Exploring GPT’s Influence on Natural Science and Mathematics
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Advances in Lattice QCD with Machine Learning2023
- Author(s)
  Akio Tomiya
- Organizer
  JPS Meeting (Symposium)
- Invited
- Data Source
  KAKENHI-PROJECT-22K03539
[Presentation] Machine Learning for Accelerating Lattice QCD Computations2022
- Author(s)
  Akio Tomiya
- Organizer
  Symposium on "Elementary Particles, Nuclei, Universe and Planets Accelerated at Fugaku
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Neural net for lattice QCD, and quantum methods for finite-temperature and density2022
- Author(s)
  Akio Tomiya
- Organizer
  Nonperturbative Analysis of Quantum Field Theory and its Applications
- Invited / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K14479
[Presentation] T-mu phase diagram using classical-quantum hybrid algorithm2022
- Author(s)
  Akio Tomiya
- Organizer
  Lattice 2022
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K14479
[Presentation] Search for phase diagram of Schwinger model using Quantum-Classical Hybrid Algorithm2022
- Author(s)
  Akio Tomiya
- Organizer
  JPS Meeting
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Recent procgress in the Application of Deep Learning to Physics2022
- Author(s)
  Akio Tomiya
- Organizer
  Japan Society of Mechanical Engineers
- Data Source
  KAKENHI-PLANNED-22H05112
[Presentation] Quantum computing for QCD phase diagram? Finite chemical potential and temperature?2020
- Author(s)
  富谷昭夫
- Organizer
  (Virtual) Kickoff meeting of C2QA center
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K14479
[Presentation] Thermal field theory with pure states2020
- Author(s)
  富谷昭夫
- Organizer
  Asia-Pacific Symposium for Lattice Field Theory (APLAT 2020)
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-20K14479

1. 永井佑紀 (20587026)

# of Collaborated Projects: 3 results

# of Collaborated Products: 2 results
2. 橋本幸士 (80345074)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
3. 田中章詞 (20791924)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
4. 野尻美保子 (30222201)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
5. 大槻東巳 (50201976)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
6. 広野雄士 (50998903)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
7. 福嶋健二 (60456754)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
8. 今田正俊 (70143542)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
9. 樺島祥介 (80260652)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
10. 大野浩史 (20734396)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
11. 柏浩司 (50612123)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results
12. 櫻井鉄也 (60187086)

# of Collaborated Projects: 1 results

# of Collaborated Products: 0 results

Tomiya Akio 富谷 昭夫

Research Projects

Research Products

Co-Researchers

A Neural Network Approach to Quark-Free Lattice QCD for First-Principles StudiesPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Foundation of "Machine Learning Physics" --- Revolutionary Transformation of Fundame ntal Physics by A New Field Integrating Machine Learning and Physics

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Effective models constructed by neural networks with symmetries

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Unification of Computational Physics and Machine LearningPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

Phase structure of gauge theories via digital quantum computersPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Sparse modeling approach to extract spectral functions with covariance of Euclidean-time correlators of lattice QCD2023

Author(s)

Journal Title

Data Source

[Journal Article] Self-learning Monte Carlo for non-Abelian gauge theory with dynamical fermions2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Equivariant transformer is all you need2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] T-mu phase diagram using classical-quantum hybrid algorithm2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Sparse modeling approach to extract spectral functions with covariance of Euclidean-time correlators of lattice QCD2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Self-learning Monte Carlo with equivariant Transformer2023

Author(s)

Journal Title

Data Source

[Journal Article] Equivariant transformer is all you need2023

Author(s)

Journal Title

Data Source

[Journal Article] GomalizingFlow.jl: A Julia package for Flow-based sampling algorithm for lattice field theory2022

Author(s)

Journal Title

Data Source

[Journal Article] Use of Schwinger-Dyson equation in constructing an approximate trivializing map2022

Author(s)

Journal Title

Data Source

[Presentation] Machine learning and Lattice QCD2023

Author(s)

Organizer

Data Source

[Presentation] "Application of Julia in Particle Physics -Toward Large-Scale Computations of Lattice QCD2023

Author(s)

Tomiya Akio 富谷昭夫