Countries citing papers authored by Masahito Hayashi
Since
Specialization
Citations
This map shows the geographic impact of Masahito Hayashi'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 Masahito Hayashi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masahito Hayashi more than expected).
Fields of papers citing papers by Masahito Hayashi
This network shows the impact of papers produced by Masahito Hayashi. 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 Masahito Hayashi. The network helps show where Masahito Hayashi may publish in the future.
Co-authorship network of co-authors of Masahito Hayashi
This figure shows the co-authorship network connecting the top 25 collaborators of Masahito Hayashi.
A scholar is included among the top collaborators of Masahito Hayashi 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 Masahito Hayashi. Masahito Hayashi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Watanabe, Shun & Masahito Hayashi. (2014). Finite-length Analysis on Tail probability and Simple Hypothesis Testing for Markov Chain. arXiv (Cornell University). 196–200.3 indexed citations
15.
Hayashi, Masahito & Toyohiro Tsurumaru. (2013). More Efficient Privacy Amplification with Non-Uniform Random Seeds via Dual Universal Hash Function.. arXiv (Cornell University).1 indexed citations
16.
Tomamichel, Marco, Mario Berta, & Masahito Hayashi. (2013). A duality relation connecting different quantum generalizations of the conditional R\'enyi entropy. arXiv (Cornell University).4 indexed citations
17.
Hayashi, Masahito, et al.. (2013). Asymptotics of Classical and LOCC Conversions and Its Application to LOCC Cloning. arXiv (Cornell University).
18.
Hayashi, Masahito & Ryutaroh Matsumoto. (2011). Universally Attainable Error and Information Exponents for the Broadcast Channels with Confidential Messages. arXiv (Cornell University).1 indexed citations
19.
Hayashi, Masahito. (2010). Tight exponential evaluation for universal composablity with privacy amplification and its applications. arXiv (Cornell University).2 indexed citations
20.
Hayashi, Masahito. (2010). Tight exponential evaluation for information theoretical secrecy based on universal composablity. arXiv (Cornell University).4 indexed citations
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.