Ming Sun

6.5k total citations · 2 hit papers
115 papers, 3.4k citations indexed

About

Ming Sun is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Instrumentation. According to data from OpenAlex, Ming Sun has authored 115 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 97 papers in Astronomy and Astrophysics, 21 papers in Nuclear and High Energy Physics and 14 papers in Instrumentation. Recurrent topics in Ming Sun's work include Galaxies: Formation, Evolution, Phenomena (84 papers), Astrophysical Phenomena and Observations (46 papers) and Astrophysics and Star Formation Studies (42 papers). Ming Sun is often cited by papers focused on Galaxies: Formation, Evolution, Phenomena (84 papers), Astrophysical Phenomena and Observations (46 papers) and Astrophysics and Star Formation Studies (42 papers). Ming Sun collaborates with scholars based in United States, Italy and France. Ming Sun's co-authors include Megan Donahue, G. Mark Voit, W. Forman, C. Jones, K. W. Cavagnolo, Matteo Fossati, A. Vikhlinin, A. Boselli, P. E. J. Nulsen and Michele Fumagalli and has published in prestigious journals such as Science, The Astrophysical Journal and Monthly Notices of the Royal Astronomical Society.

In The Last Decade

Ming Sun

103 papers receiving 3.3k citations

Hit Papers

CHANDRASTUDIES OF THE X-RAY GAS PROPERTIES OF GALAXY GROUPS 2009 2026 2014 2020 2009 2022 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Sun United States 30 3.2k 770 769 92 81 115 3.4k
Roberto Decarli Germany 35 4.0k 1.3× 944 1.2× 1.1k 1.5× 110 1.2× 85 1.0× 147 4.2k
John Wise United States 32 3.8k 1.2× 973 1.3× 867 1.1× 146 1.6× 80 1.0× 85 4.0k
P. Serra Italy 30 2.1k 0.7× 513 0.7× 974 1.3× 87 0.9× 55 0.7× 97 2.5k
Kristian Finlator United States 28 2.8k 0.9× 458 0.6× 1.3k 1.7× 68 0.7× 65 0.8× 54 2.9k
M. Gaspari United States 33 3.3k 1.0× 971 1.3× 724 0.9× 67 0.7× 93 1.1× 118 3.5k
Masafumi Yagi Japan 31 3.0k 1.0× 409 0.5× 1.5k 2.0× 138 1.5× 78 1.0× 108 3.3k
F. Mannucci Italy 36 4.8k 1.5× 705 0.9× 1.6k 2.1× 88 1.0× 76 0.9× 125 5.0k
A. Wolter Italy 25 2.8k 0.9× 1.4k 1.8× 538 0.7× 67 0.7× 33 0.4× 120 3.0k
Gwen C. Rudie United States 23 2.2k 0.7× 510 0.7× 716 0.9× 102 1.1× 57 0.7× 67 2.3k
M. Yoshida Japan 31 3.2k 1.0× 690 0.9× 1.1k 1.4× 168 1.8× 38 0.5× 143 3.3k

Countries citing papers authored by Ming Sun

Since Specialization
Citations

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

Fields of papers citing papers by Ming Sun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Sun

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Sun. A scholar is included among the top collaborators of Ming Sun 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 Ming Sun. Ming Sun 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.
Seppi, R., D. Eckert, A. Finoguenov, et al.. (2025). Modelling the selection of galaxy groups with end-to-end simulations. Astronomy and Astrophysics. 699. A206–A206.
2.
Ramatsoku, M., et al.. (2025). MeerKAT HI imaging of the jellyfish galaxy ESO 137-001. Astronomy and Astrophysics. 694. A159–A159.
3.
Sun, Ming, Huijun Le, B. Épinat, et al.. (2025). A Virgo Environmental Survey Tracing Ionised Gas Emission (VESTIGE). Astronomy and Astrophysics. 705. A139–A139.
4.
Kannappan, Sheila J., Kelley M. Hess, A. J. Baker, et al.. (2025). The RESOLVE and ECO G3 Initiative: Drivers of H i Content and X-Ray Emission in Galaxy Groups. The Astrophysical Journal. 985(2). 228–228.
5.
Liu, Wenhao, Ming Sun, G. Mark Voit, et al.. (2024). X-ray cool core remnants heated by strong radio AGN feedback. Monthly Notices of the Royal Astronomical Society. 531(1). 2063–2078. 2 indexed citations
6.
Geng, Xiang, et al.. (2023). A switchable multi-wavelength mode-locked fiber laser based on a multi-mode interference device. Infrared Physics & Technology. 133. 104812–104812. 3 indexed citations
7.
Sun, Ming, Pavel Jáchym, W.L. Waldron, et al.. (2023). Tracing the kinematics of the whole ram-pressure-stripped tails in ESO 137-001. Monthly Notices of the Royal Astronomical Society. 521(4). 6266–6283. 8 indexed citations
8.
Wik, Daniel R., F. Gastaldello, Julie Hlavacek-Larrondo, et al.. (2023). NuSTAR Observations of Abell 665 and 2146: Constraints on Nonthermal Emission. The Astrophysical Journal. 954(1). 76–76. 2 indexed citations
9.
Zaritsky, Dennis, Yara L. Jaffé, Richard L. Donnerstein, et al.. (2023). An enigmatic 380 kpc long linear collimated galactic tail. Monthly Notices of the Royal Astronomical Society. 524(1). 1431–1437. 5 indexed citations
10.
Xu, Bin, et al.. (2023). Manipulation of plasmonic vortex fields using positive elliptically polarized beams. Optics & Laser Technology. 169. 110132–110132. 1 indexed citations
11.
Ge, Chong, D. Lal, Ming Sun, et al.. (2022). Chandra view of Abell 407: the central compact group of galaxies and the interaction between the radio AGN and the ICM. Monthly Notices of the Royal Astronomical Society. 511(3). 3994–4004. 3 indexed citations
12.
Ge, Chong, Ming Sun, Masafumi Yagi, et al.. (2021). The BIG X-ray tail. Monthly Notices of the Royal Astronomical Society Letters. 508(1). L69–L73. 6 indexed citations
13.
Ge, Chong, Ruo-Yu Liu, Ming Sun, et al.. (2020). Chandra and XMM–Newton observations of A2256: cold fronts, merger shocks, and constraint on the IC emission. Monthly Notices of the Royal Astronomical Society. 497(4). 4704–4717. 9 indexed citations
14.
Chon, Gayoung, H. Böhringer, Matthias Kluge, et al.. (2019). Interaction of the massive cluster system Abell 3016/3017 embedded in a cosmic filament. Springer Link (Chiba Institute of Technology). 7 indexed citations
15.
Voit, G. Mark, Arif Babul, Iu. Babyk, et al.. (2019). Circumgalactic Gas and the Precipitation Limit. IRIS UNIMORE (University of Modena and Reggio Emilia). 1 indexed citations
16.
Gaspari, M., D. Eckert, S. Ettori, et al.. (2019). The X-Ray Halo Scaling Relations of Supermassive Black Holes. The Astrophysical Journal. 884(2). 169–169. 60 indexed citations
17.
Irwin, Jimmy A., Daniel R. Wik, Ming Sun, et al.. (2016). SUZAKU X-RAY OBSERVATIONS OF THE NEAREST NON-COOL CORE CLUSTER, ANTLIA: DYNAMICALLY YOUNG BUT WITH REMARKABLY RELAXED OUTSKIRTS. The Astrophysical Journal. 829(1). 49–49. 12 indexed citations
18.
Werner, Norbert, J. B. R. Oonk, Ming Sun, et al.. (2014). The origin of cold gas in giant elliptical galaxies and its role in fuelling radio-mode AGN feedback. Monthly Notices of the Royal Astronomical Society. 439(3). 2291–2306. 94 indexed citations
19.
Mroczkowski, Tony, Mark J. Devlin, Simon Dicker, et al.. (2011). New High-Resolution Sunyaev-Zel'dovich Observations with GBT+MUSTANG. MmSAI. 82. 485. 1 indexed citations
20.
Sun, Ming. (2009). Intracluster star formation and galaxy transformation: ESO 137-001 in A3627. 11683.

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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