Matteo Bugli

916 total citations
23 papers, 331 citations indexed

About

Matteo Bugli is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Artificial Intelligence. According to data from OpenAlex, Matteo Bugli has authored 23 papers receiving a total of 331 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Astronomy and Astrophysics, 11 papers in Nuclear and High Energy Physics and 2 papers in Artificial Intelligence. Recurrent topics in Matteo Bugli's work include Gamma-ray bursts and supernovae (9 papers), Pulsars and Gravitational Waves Research (7 papers) and Astrophysical Phenomena and Observations (6 papers). Matteo Bugli is often cited by papers focused on Gamma-ray bursts and supernovae (9 papers), Pulsars and Gravitational Waves Research (7 papers) and Astrophysical Phenomena and Observations (6 papers). Matteo Bugli collaborates with scholars based in France, Italy and Germany. Matteo Bugli's co-authors include Jérôme Guilet, L. Del Zanna, N. Bucciantini, M. Obergaulinger, Simone Landi, Emanuele Papini, R Raynaud, M. Á. Aloy, P. Cerdá–Durán and Scott C. Noble and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Astronomy and Astrophysics.

In The Last Decade

Matteo Bugli

20 papers receiving 320 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo Bugli France 10 296 166 15 11 10 23 331
C. Lynch United States 12 410 1.4× 114 0.7× 20 1.3× 17 1.5× 4 0.4× 18 421
F. Loi Italy 12 256 0.9× 168 1.0× 13 0.9× 6 0.5× 8 0.8× 30 287
D. Godoy-Rivera United States 10 339 1.1× 47 0.3× 18 1.2× 10 0.9× 7 0.7× 22 348
Helge Rottmann Germany 6 304 1.0× 167 1.0× 25 1.7× 3 0.3× 4 0.4× 17 324
E. Laplace Germany 14 555 1.9× 93 0.6× 17 1.1× 4 0.4× 34 3.4× 24 589
Róbert Andrássy Germany 11 310 1.0× 69 0.4× 24 1.6× 14 1.3× 10 1.0× 16 350
A. J. M. Thomson Australia 9 213 0.7× 118 0.7× 20 1.3× 11 1.0× 11 240
D. Blinov Greece 11 318 1.1× 225 1.4× 11 0.7× 2 0.2× 11 1.1× 56 361
T. M. O. Franzen Australia 13 327 1.1× 214 1.3× 15 1.0× 6 0.5× 4 0.4× 27 346
R. Lunnan United States 16 694 2.3× 241 1.5× 10 0.7× 2 0.2× 7 0.7× 29 715

Countries citing papers authored by Matteo Bugli

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Bugli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Bugli

This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Bugli. A scholar is included among the top collaborators of Matteo Bugli 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 Matteo Bugli. Matteo Bugli 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.
Bugli, Matteo, et al.. (2026). The PLUTO code on GPUs: A first look at Eulerian MHD methods. Astronomy and Computing. 55. 101076–101076.
2.
Bugli, Matteo, et al.. (2025). PyPLUTO: a data analysis Python package for the PLUTO code. The Journal of Open Source Software. 10(113). 8448–8448. 3 indexed citations
3.
Mignone, A., et al.. (2025). Towards 4th-order accurate 3D Magnetic Reconnection in Relativistic plasmas. Journal of Physics Conference Series. 2997(1). 12005–12005.
4.
Bugli, Matteo, et al.. (2024). Relativistic reconnection with effective resistivity. Astronomy and Astrophysics. 693. A233–A233. 4 indexed citations
5.
Bendahman, M., Isabel Goos, J. A. B. Coelho, et al.. (2024). Prospects for realtime characterization of core-collapse supernova and neutrino properties. Journal of Cosmology and Astroparticle Physics. 2024(2). 8–8. 4 indexed citations
6.
Mignone, A., et al.. (2024). A fourth-order accurate finite volume scheme for resistive relativistic MHD. Monthly Notices of the Royal Astronomical Society. 533(2). 1670–1686. 6 indexed citations
7.
Zanna, L. Del, et al.. (2024). A GPU-Accelerated Modern Fortran Version of the ECHO Code for Relativistic Magnetohydrodynamics. Fluids. 9(1). 16–16. 3 indexed citations
8.
Reichert, Moritz, Matteo Bugli, Jérôme Guilet, et al.. (2024). Nucleosynthesis in magnetorotational supernovae: impact of the magnetic field configuration. Monthly Notices of the Royal Astronomical Society. 529(4). 3197–3209. 6 indexed citations
9.
Zanna, L. Del, et al.. (2022). General Relativistic Magnetohydrodynamics Mean-Field Dynamos. Fluids. 7(2). 87–87. 6 indexed citations
10.
Guilet, Jérôme, et al.. (2022). MRI-drivenαΩ dynamos in protoneutron stars. Astronomy and Astrophysics. 667. A94–A94. 27 indexed citations
11.
Bendahman, M., Matteo Bugli, A. Coleiro, et al.. (2021). Exploring the Potential of Multi-Detector Analyses for Core-Collapse Supernova Neutrino Detection. Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021). 1090–1090. 1 indexed citations
12.
Bugli, Matteo, Jérôme Guilet, & M. Obergaulinger. (2021). Three-dimensional core-collapse supernovae with complex magnetic structures – I. Explosion dynamics. Monthly Notices of the Royal Astronomical Society. 507(1). 443–454. 34 indexed citations
13.
Bugli, Matteo, Jérôme Guilet, & M. Obergaulinger. (2020). Magnetorotational core-collapse supernovae: the impact of the magnetic field’s structure. Proceedings of the International Astronomical Union. 16(S363). 309–313.
14.
Iapichino, Luigi, et al.. (2020). Honing and proofing Astrophysical codes on the road to Exascale. Experiences from code modernization on many-core systems. Future Generation Computer Systems. 112. 93–107. 3 indexed citations
15.
Zanna, L. Del, et al.. (2020). Creation and dissipation of magnetic fields in non-ideal GRMHD simulations. Journal of Physics Conference Series. 1623. 12004–12004. 1 indexed citations
16.
Zanna, L. Del, et al.. (2019). General relativistic magnetohydrodynamic dynamo in thick accretion disks: fully nonlinear simulations. Monthly Notices of the Royal Astronomical Society. 18 indexed citations
17.
Bugli, Matteo, Jérôme Guilet, M. Obergaulinger, P. Cerdá–Durán, & M. Á. Aloy. (2019). The impact of non-dipolar magnetic fields in core-collapse supernovae. Monthly Notices of the Royal Astronomical Society. 492(1). 58–71. 39 indexed citations
18.
Bugli, Matteo, Jérôme Guilet, Ewald Müller, et al.. (2017). Papaloizou-Pringle instability suppression by the magnetorotational\n instability in relativistic accretion discs. arXiv (Cornell University). 30 indexed citations
19.
Zanna, L. Del, Emanuele Papini, Simone Landi, Matteo Bugli, & N. Bucciantini. (2016). Fast reconnection in relativistic plasmas: the magnetohydrodynamics tearing instability revisited. Monthly Notices of the Royal Astronomical Society. 460(4). 3753–3765. 56 indexed citations
20.
Bugli, Matteo, L. Del Zanna, & N. Bucciantini. (2014). Dynamo action in thick discs around Kerr black holes: high-order resistive GRMHD simulations. Monthly Notices of the Royal Astronomical Society Letters. 440(1). L41–L45. 27 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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