雅則 大矢

100 total papers · 790 total citations
2 papers, 484 citations indexed

About

雅則 大矢 is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Infectious Diseases. According to data from OpenAlex, 雅則 大矢 has authored 2 papers receiving a total of 484 indexed citations (citations by other indexed papers that have themselves been cited), including 1 paper in Artificial Intelligence, 1 paper in Electrical and Electronic Engineering and 0 papers in Infectious Diseases. Recurrent topics in 雅則 大矢's work include Cryptographic Implementations and Security (1 paper), graph theory and CDMA systems (1 paper) and Coding theory and cryptography (1 paper) 雅則 大矢 is often cited by papers focused on Cryptographic Implementations and Security (1 paper), graph theory and CDMA systems (1 paper) and Coding theory and cryptography (1 paper) 雅則 大矢 collaborates with scholars based in Italy 雅則 大矢's co-authors include Dėnes Petz and Luigi Accardi and has published in prestigious journals such as Cineca Institutional Research Information System (Tor Vergata University).

In The Last Decade

雅則 大矢

2 papers receiving 459 citations

Hit Papers

Quantum Entropy and Its Use 1993 2026 2004 2015 1993 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. Quantum Entropy and Its Use
    1993 482 citations 雅則 大矢, Dėnes Petz profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
雅則 大矢 315 240 194 83 53 2 484
Donald Bures 294 0.9× 263 1.1× 106 0.5× 77 0.9× 37 0.7× 7 451
Dimitri Gioev 301 1.0× 99 0.4× 107 0.6× 133 1.6× 53 1.0× 8 495
D. Petz 278 0.9× 258 1.1× 189 1.0× 80 1.0× 95 1.8× 23 493
M. Arık 286 0.9× 111 0.5× 283 1.5× 50 0.6× 30 0.6× 9 510
Matthew J. Donald 310 1.0× 245 1.0× 99 0.5× 34 0.4× 18 0.3× 14 421
Ruth Shir 311 1.0× 112 0.5× 210 1.1× 13 0.2× 11 0.2× 14 434
David Shale 141 0.4× 40 0.2× 143 0.7× 266 3.2× 93 1.8× 17 476
S. Schlieder 260 0.8× 66 0.3× 154 0.8× 92 1.1× 29 0.5× 16 504
Christian Grosche 306 1.0× 31 0.1× 224 1.2× 71 0.9× 36 0.7× 22 420
A. I. Oksak 152 0.5× 27 0.1× 157 0.8× 120 1.4× 50 0.9× 14 416

Countries citing papers authored by 雅則 大矢

Since Specialization
Citations

This map shows the geographic impact of 雅則 大矢's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by 雅則 大矢 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites 雅則 大矢 more than expected).

Fields of papers citing papers by 雅則 大矢

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by 雅則 大矢. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by 雅則 大矢. The network helps show where 雅則 大矢 may publish in the future.

Co-authorship network of co-authors of 雅則 大矢

This figure shows the co-authorship network connecting the top 25 collaborators of 雅則 大矢. A scholar is included among the top collaborators of 雅則 大矢 based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with 雅則 大矢. 雅則 大矢 is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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2026