Makoto Takamoto

539 total citations
26 papers, 295 citations indexed

About

Makoto Takamoto is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Computational Mechanics. According to data from OpenAlex, Makoto Takamoto has authored 26 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Astronomy and Astrophysics, 10 papers in Nuclear and High Energy Physics and 3 papers in Computational Mechanics. Recurrent topics in Makoto Takamoto's work include Pulsars and Gravitational Waves Research (6 papers), Ionosphere and magnetosphere dynamics (5 papers) and Solar and Space Plasma Dynamics (5 papers). Makoto Takamoto is often cited by papers focused on Pulsars and Gravitational Waves Research (6 papers), Ionosphere and magnetosphere dynamics (5 papers) and Solar and Space Plasma Dynamics (5 papers). Makoto Takamoto collaborates with scholars based in Japan, Germany and France. Makoto Takamoto's co-authors include Shu‐ichiro Inutsuka, Takunori Harada, Masayuki Watanabe, Hiroshi Hayakawa, Tsuyoshi Inoue, Hitoshi Imaoka, A. Lazarian, Chiho Nonaka, Yukinao Akamatsu and Yoko Hieda and has published in prestigious journals such as The Astrophysical Journal, Journal of Computational Physics and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Makoto Takamoto

23 papers receiving 277 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Makoto Takamoto Japan 11 135 103 60 37 25 26 295
Rubén Díaz Argentina 15 473 3.5× 84 0.8× 27 0.5× 5 0.1× 18 0.7× 51 593
D. Herbison-Evans Australia 9 93 0.7× 21 0.2× 57 0.9× 43 1.2× 12 0.5× 25 330
Arpita Roy United States 13 380 2.8× 11 0.1× 35 0.6× 9 0.2× 30 1.2× 44 489
M. T. Hussein Egypt 13 77 0.6× 110 1.1× 27 0.5× 12 0.3× 129 5.2× 43 342
Takayuki Hirayama Japan 10 118 0.9× 143 1.4× 21 0.3× 49 1.3× 2 0.1× 39 261
W. Davidson New Zealand 10 217 1.6× 112 1.1× 48 0.8× 27 0.7× 5 0.2× 67 375
Mario Argeri Italy 7 27 0.2× 235 2.3× 101 1.7× 19 0.5× 58 2.3× 8 413
Daniel Durand Canada 7 254 1.9× 24 0.2× 9 0.1× 3 0.1× 10 0.4× 16 308
L. Wai United States 5 83 0.6× 99 1.0× 68 1.1× 3 0.1× 5 0.2× 9 193

Countries citing papers authored by Makoto Takamoto

Since Specialization
Citations

This map shows the geographic impact of Makoto Takamoto'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 Makoto Takamoto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Makoto Takamoto more than expected).

Fields of papers citing papers by Makoto Takamoto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Makoto Takamoto. 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 Makoto Takamoto. The network helps show where Makoto Takamoto may publish in the future.

Co-authorship network of co-authors of Makoto Takamoto

This figure shows the co-authorship network connecting the top 25 collaborators of Makoto Takamoto. A scholar is included among the top collaborators of Makoto Takamoto 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 Makoto Takamoto. Makoto Takamoto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zaverkin, Viktor, Federico Errica, Francesco Alesiani, et al.. (2024). Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentials. npj Computational Materials. 10(1). 25 indexed citations
2.
Flemisch, Bernd, Melanie Herschel, Dirk Pflüger, et al.. (2024). Research Data Management in Simulation Science: Infrastructure, Tools, and Applications. Datenbank-Spektrum. 24(2). 97–105. 1 indexed citations
3.
Niepert, Mathias, et al.. (2022). PDEBench: An Extensive Benchmark for Scientific Machine Learning. 1596–1611.
4.
5.
Takamoto, Makoto, et al.. (2020). An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation. 67–72. 23 indexed citations
6.
Takamoto, Makoto. (2018). Evolution of three-dimensional relativistic current sheets and development of self-generated turbulence. Monthly Notices of the Royal Astronomical Society. 476(3). 4263–4271. 10 indexed citations
7.
Takamoto, Makoto & A. Lazarian. (2017). Strong coupling of Alfvén and fast modes in compressible relativistic magnetohydrodynamic turbulence in magnetically dominated plasmas. Monthly Notices of the Royal Astronomical Society. 472(4). 4542–4550. 16 indexed citations
8.
Fujimoto, Keizo & Makoto Takamoto. (2016). Ion and electron dynamics generating the Hall current in the exhaust far downstream of the reconnection x-line. Physics of Plasmas. 23(1). 7 indexed citations
9.
Takamoto, Makoto, et al.. (2016). COMPRESSIBLE RELATIVISTIC MAGNETOHYDRODYNAMIC TURBULENCE IN MAGNETICALLY DOMINATED PLASMAS AND IMPLICATIONS FOR A STRONG-COUPLING REGIME. The Astrophysical Journal Letters. 831(2). L11–L11. 24 indexed citations
10.
Takamoto, Makoto, J. Pétri, & Hubert Baty. (2015). Thermal synchrotron radiation from RRMHD simulations of the double tearing mode reconnection – application to the Crab flares. Monthly Notices of the Royal Astronomical Society. 454(3). 2972–2980. 4 indexed citations
11.
Takamoto, Makoto, et al.. (2015). TURBULENT RECONNECTION IN RELATIVISTIC PLASMAS AND EFFECTS OF COMPRESSIBILITY. The Astrophysical Journal. 815(1). 16–16. 27 indexed citations
12.
Okawa, H., et al.. (2014). An alternative numerical method for the stationary pulsar magnetosphere. Publications of the Astronomical Society of Japan. 66(1). 4 indexed citations
13.
Akamatsu, Yukinao, Shu‐ichiro Inutsuka, Chiho Nonaka, & Makoto Takamoto. (2013). A new scheme of causal viscous hydrodynamics for relativistic heavy-ion collisions: A Riemann solver for quark–gluon plasma. Journal of Computational Physics. 256. 34–54. 14 indexed citations
14.
Takamoto, Makoto, Tsuyoshi Inoue, & Shu‐ichiro Inutsuka. (2012). ENHANCED DISSIPATION RATE OF MAGNETIC FIELD IN STRIPED PULSAR WINDS BY THE EFFECT OF TURBULENCE. The Astrophysical Journal. 755(1). 76–76. 7 indexed citations
15.
Takamoto, Makoto & Shu‐ichiro Inutsuka. (2010). The relativistic kinetic dispersion relation: Comparison of the relativistic Bhatnagar–Gross–Krook model and Grad’s 14-moment expansion. Physica A Statistical Mechanics and its Applications. 389(21). 4580–4603. 19 indexed citations
16.
Kageura, Mitsuyoshi, et al.. (1994). Demonstration of oxidation dyes on human hair. Forensic Science International. 64(1). 1–8. 12 indexed citations
17.
Kageura, Mitsuyoshi, et al.. (1991). Identification of human hair stained with oxidation hair dyes by gas chromatographic-mass spectrometric analysis. Forensic Science International. 52(1). 5–11. 12 indexed citations
18.
Kageura, Mitsuyoshi, et al.. (1988). Detection of toluene in a putrefied human body.. PubMed. 42(4-5). 354–7. 1 indexed citations
19.
Hara, Kenji, Mitsuyoshi Kageura, Yoko Hieda, Makoto Takamoto, & S. Kashimura. (1988). Application of wide-bore capillary gas chromatography to analyze volatile compounds in body fluids.. PubMed. 42(2). 142–6. 1 indexed citations
20.
Takayama, Hiroaki, Takahiro Suzuki, Makoto Takamoto, & Toshihiko Okamoto. (1979). ChemInform Abstract: DOUBLE‐CYCLIZATION REACTIONS OF 1‐DIBENZYLAMINO‐2‐PROPANONE AND RELATED COMPOUNDS. Chemischer Informationsdienst. 10(9). 1 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.

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