Details of the Researcher

PHOTO

Yuka Fujiki
Section
Frontier Research Institute for Interdisciplinary Sciences
Job title
Assistant Professor
Degree

  • 博士（工学）（北海道大学）

  • 修士（工学）（北海道大学）

e-Rad No.
70912517

Research History 2

  • 2021/04 - Present
    Tohoku University　Advanced Institute for Materials Research　Assistant Professor

  • 2018/04 - 2021/03
    Hokkaido University　Graduate School of Engineering Division of Applied Physics　Japan Society for the Promotion of Science, Research Fellowship for Young Scientists (DC1)

Education 2

  • Hokkaido University　Graduate School of Engineering　Division of Applied Physics

    2016/04 - 2021/03

  • Hokkaido University　School of Engineering　Department of Applied Science and Engineering

    2012/03 - 2016/04

Research Interests 2

  • Fractal

  • Complex Networks

Research Areas 1

  • Natural sciences / Mathematical physics and basic theory / Complex Networks

Papers 5

  1. A general model of hierarchical fractal scale-free networks Peer-reviewed

    Kousuke Yakubo, Yuka Fujiki

    PLOS ONE　17　(3)　e0264589-e0264589　2022/03/21

    Publisher: Public Library of Science (PLoS)

    DOI： 10.1371/journal.pone.0264589 　

    eISSN： 1932-6203

    More details Close

    We propose a general model of unweighted and undirected networks having the scale-free property and fractal nature. Unlike the existing models of fractal scale-free networks (FSFNs), the present model can systematically and widely change the network structure. In this model, an FSFN is iteratively formed by replacing each edge in the previous generation network with a small graph called a generator. The choice of generators enables us to control the scale-free property, fractality, and other structural properties of hierarchical FSFNs. We calculate theoretically various characteristic quantities of networks, such as the exponent of the power-law degree distribution, fractal dimension, average clustering coefficient, global clustering coefficient, and joint probability describing the nearest-neighbor degree correlation. As an example of analyses of phenomena occurring on FSFNs, we also present the critical point and critical exponents of the bond-percolation transition on infinite FSFNs, which is related to the robustness of networks against edge removal. By comparing the percolation critical points of FSFNs whose structural properties are the same as each other except for the clustering nature, we clarify the effect of the clustering on the robustness of FSFNs. As demonstrated by this example, the present model makes it possible to elucidate how a specific structural property influences a phenomenon occurring on FSFNs by varying systematically the structures of FSFNs. Finally, we extend our model for deterministic FSFNs to a model of non-deterministic ones by introducing asymmetric generators and reexamine all characteristic quantities and the percolation problem for such non-deterministic FSFNs.

  2. Identification of intrinsic long-range degree correlations in complex networks Peer-reviewed

    Yuka Fujiki, Kousuke Yakubo

    Physical Review E　101　(3)　2020/03/18

    Publisher: American Physical Society (APS)

    DOI： 10.1103/physreve.101.032308 　

    ISSN： 2470-0045

    eISSN： 2470-0053

  3. General formulation of long-range degree correlations in complex networks Peer-reviewed

    Yuka Fujiki, Taro Takaguchi, Kousuke Yakubo

    Physical Review E　97　(6)　2018/06/11

    Publisher: American Physical Society (APS)

    DOI： 10.1103/physreve.97.062308 　

    ISSN： 2470-0045

    eISSN： 2470-0053

  4. Fractality and degree correlations in scale-free networks Peer-reviewed

    Yuka Fujiki, Shogo Mizutaka, Kousuke Yakubo

    The European Physical Journal B　90　(7)　2017/07

    Publisher: Springer Science and Business Media LLC

    DOI： 10.1140/epjb/e2017-80031-x 　

    ISSN： 1434-6028

    eISSN： 1434-6036

  5. Properties of the connected components in projections of random bipartite networks: effects of clique size fluctuations Peer-reviewed

    Yuka Fujiki, Shogo Mizutaka

    Applied Network Science　9　(1)　2024/12

    DOI： 10.1007/s41109-024-00664-w 　

    eISSN： 2364-8228

Misc. 5

  1. Properties of the largest connected components of networks: Effects of clique size fluctuations

    藤木結香, 水高将吾

    日本物理学会講演概要集(CD-ROM)　77　(2)　2022

    ISSN： 2189-079X

  2. Correlated structure in projection of bipartite networks

    水高将吾, 藤木結香

    日本物理学会講演概要集(CD-ROM)　77　(2)　2022

    ISSN： 2189-079X

  3. General relations between probabilities characterizing long-range degree correlations

    Fujiki Yuka, Takaguchi Taro, Yakubo Kousuke

    Meeting Abstracts of the Physical Society of Japan　71　2976-2976　2016

    Publisher: The Physical Society of Japan

    DOI： 10.11316/jpsgaiyo.71.2.0_2976 　

  4. 21aBS-6 Long-range degree correlations in the (u,v)-flower

    Fujiki Y., Yakubo K.

    Meeting Abstracts of the Physical Society of Japan　71　2993-2993　2016

    Publisher: The Physical Society of Japan (JPS)

    DOI： 10.11316/jpsgaiyo.71.1.0_2993 　

    ISSN： 2189-079X

  5. 21aBS-5 Spearman's rank correlation coefficient between degrees of adjacent nodes in complex networks

    Yakubo K., Fujiki Y., Mizutaka S.

    Meeting Abstracts of the Physical Society of Japan　71　2992-2992　2016

    Publisher: The Physical Society of Japan (JPS)

    DOI： 10.11316/jpsgaiyo.71.1.0_2992 　

    ISSN： 2189-079X

Presentations 18

  1. 2次隣接ノード間の次数相関によるネットワークの頑強性への影響

    藤木結香, Stefan Junk

    ネットワーク生態学グループ創立20周年記念シンポジウム　2025/03/08

  2. 単連結な隣接相関ランダムネットワークの生成

    藤木結香

    ネットワーク科学研究会2024　2025/03

  3. Generating nearest-neighbor correlated random networks whose giant connected component exhibits a given degree-degree correlation

    Yuka Fujiki

    2024/09/16

  4. Degree correlations beyond nearest neighbors in complex networks International-presentation Invited

    Yuka Fujiki

    The International Workshop on Complex Systems and Their Interdisciplinary Applications　2024/08/06

  5. Effect of second nearest neighbor degree correlations on network robustness International-presentation

    Yuka Fujiki, Stefan Junk

    International School and Conference on Network Science (NetSci 2024)　2024/06/19

  6. 身の回りのネットワークは何次元？〜人間関係からインターネットまで〜

    藤木結香

    KISTEC先端科学技術セミナー「そこにも、数学。 -社会と技術をつなぐ、もうひとつの『ことば』-」　2024/03/14

  7. Robustness of networks with long-range degree correlations up to network distance l=2

    Yuka Fujiki, Stefan Junk

    2023/09/16

  8. Structural properties of fractal scale-free networks formed by a general hierarchical model International-presentation

    Yuka Fujiki, Kousuke Yakubo

    28th International Conference on Statistical Physics　2023/08/08

  9. Causal Inference for Power Grid Dynamics International-presentation

    Hiroshi Suito, Hiroyasu Ando, Yuka Fujiki, Hiroyuki Higuchi

    CM3 - Transport Conference 2023

  10. Sampling networks with degree-degree correlation up to network distance l=2

    Yuka Fujiki, Stefan Junk

    Roles of Heterogeneity in Nonequilibrium Collective Dynamics 2022 (RHINO2022)

  11. Effect of degree-degree correlations at distance 2 on robustness of real-world networks

    Stefan Junk, Yuka Fujiki

    Roles of Heterogeneity in Nonequilibrium Collective Dynamics 2022 (RHINO2022)

  12. Structural properties of a generalized model of fractal scale-free networks Invited

    Yuka Fujiki

    Roles of heterogeneity in non-equilibrium collective dynamics 2021 (RHINO 2021)

  13. Identification of fractality by assortativity invariance under renormalization

    Yuka Fujiki, Kousuke Yakubo

    International School and Conference on Networks Science 2020 (NetSci-X 2020)

  14. Detection and analysis of intrinsic long-range degree correlation

    Yuka Fujiki, Kousuke Yakubo

    Roles of Heterogeneity in Non-equilibrium collective dynamics (RHINO 2019)

  15. Detection and analysis of long-range degree correlations in complex networks

    Yuka Fujiki, Kousuke Yakubo

    The 27th International Conference on Statistical Physics (StatPhys 27)

  16. A general framework for analyzing long-range degree correlations in complex networks

    Yuka Fujiki, Kousuke Yakubo

    International School and Conference on Network Science 2018 (NetSci 2018)

  17. Degree correlations in scale-free fractal networks

    Yuka Fujiki, Kousuke Yakubo

    The 2nd Workshop on Self-Organization and Robustness of Evolving Many-Body Systems

  18. Disassortative degree mixing and fractality of scale-free networks

    Yuka Fujiki, Kousuke Yakubo

    International Conference on statistical Physics (SigmaPhi2017)

Show all Show first 5

Research Projects 4

  1. Counrty/regional-level risk assessment of sexually-transmitted infections based on sexual contact network structures including among MSM Competitive

    Offer Organization: Japan Society for the Promotion of Science

    System: Bilateral Collaborations

    Institution: Nagasaki University, University College London

    2024/04 - 2026/03

  2. 複雑ネットワークの長距離次数相関とネットワーク上の物理現象の関係解明

    藤木 結香

    Offer Organization: 日本学術振興会

    System: 科学研究費助成事業

    Category: 若手研究

    Institution: 東北大学

    2023/04 - 2026/03

  3. ""

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research Grant-in-Aid for Research Activity Start-up

    Category: Grant-in-Aid for Research Activity Start-up

    Institution: Tohoku University

    2021/08 - 2023/03

  4. 複雑ネットワークにおける長距離次数相関の定式化とフラクタル的大域構造の起源解明

    藤木 結香

    Offer Organization: 日本学術振興会

    System: 科学研究費助成事業 特別研究員奨励費

    Category: 特別研究員奨励費

    Institution: 北海道大学

    2018/04 - 2021/03

    More details Close

    次数不均一性の強いネットワークでは、次数どうしの相関関係がネットワーク上のダイナミクスやネットワークの大域的性質と密接な関係にあることが知られている。従来研究では主に隣接するノードの次数どうしの相関（隣接次数相関）が注目されてきたが、近年、隣接以上に離れたノードの次数関係(長距離次数相関)の重要性が認識され始めている。本課題研究では前年度において、長距離次数相関の一般的定式化を行い、５つの確率関数を用いた長距離次数相関の解析手法を提案した。さらに、対象とするネットワークに発現した長距離次数相関が、隣接次数相関によって引き起こされた付随的なものであるか否かを判別する方法を確立した。しかしながら、一般的定式化のために導入した5つの確率関数は3変数関数であるため、関数形の物理的意味を直感的に解釈することが難しい。よって本年度は、対象とするネットワークの長距離次数相関の強さと、隣接次数相関に対して「非付随的な」長距離次数相関の強さを表す指標を開発し、現実世界に存在する多数のネットワークに対してこの指標を計算した。その結果、インターネットと一部の交友関係ネットワークを除いた大多数の現実ネットワークに非付随的な長距離次数相関が強く現れており、特にフラクタル性を有するワールド・ワイド・ウェブやタンパク質の折り畳み構造ネットワークにおいては、特定の次数をもつノードどうしの反発傾向が強く現れることを明らかになった。さらに、ネットワークの最も一般的な構造特性である頑強性と非付随的な長距離次数相関の関係を解明するために、非付随的な長距離次数相関を有する現実ネットワークの頑強性と、付随的な隣接次数相関のみを有するネットワーク・モデルの頑強性との間の比較を行った。この結果、現実ネットワークの頑強性は非付随的な長距離次数相関によって常に低下することが明らかになった。