Long Wang

2.6k total citations · 1 hit paper
66 papers, 1.7k citations indexed

About

Long Wang is a scholar working on Astronomy and Astrophysics, Instrumentation and Statistical and Nonlinear Physics. According to data from OpenAlex, Long Wang has authored 66 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Astronomy and Astrophysics, 19 papers in Instrumentation and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Long Wang's work include Stellar, planetary, and galactic studies (30 papers), Astrophysics and Star Formation Studies (23 papers) and Astrophysical Phenomena and Observations (17 papers). Long Wang is often cited by papers focused on Stellar, planetary, and galactic studies (30 papers), Astrophysics and Star Formation Studies (23 papers) and Astrophysical Phenomena and Observations (17 papers). Long Wang collaborates with scholars based in China, Japan and Germany. Long Wang's co-authors include Rainer Spurzem, M. B. N. Kouwenhoven, Peter Berczik, Keigo Nitadori, Tereza Jeřabková, Thorsten Naab, Pavel Kroupa, S. J. Aarseth, Mirek Giersz and Junichiro Makino and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and The Astrophysical Journal.

In The Last Decade

Long Wang

62 papers receiving 1.6k citations

Hit Papers

Unveiling inflammatory and prehypertrophic cell populatio... 2024 2026 2025 2024 10 20 30 40 50

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Long Wang China 23 1.5k 441 85 53 51 66 1.7k
Junichi Baba Japan 20 815 0.5× 284 0.6× 30 0.4× 22 0.4× 28 0.5× 61 977
Katie Auchettl United States 20 1.1k 0.7× 113 0.3× 426 5.0× 17 0.3× 30 0.6× 55 1.4k
Lindsay King United States 26 1.2k 0.8× 468 1.1× 236 2.8× 186 3.5× 129 2.5× 74 1.8k
N. G. Guseva Ukraine 34 3.2k 2.1× 1.2k 2.6× 389 4.6× 8 0.2× 114 2.2× 97 3.5k
M. Kerscher Germany 16 442 0.3× 135 0.3× 112 1.3× 16 0.3× 11 0.2× 38 836
Lauren M. Weiss United States 16 1.4k 0.9× 318 0.7× 58 0.7× 2 0.0× 47 0.9× 44 1.6k
Robert J. Nemiroff United States 20 983 0.7× 111 0.3× 298 3.5× 6 0.1× 56 1.1× 96 1.4k
Robyn E. Sanderson United States 21 1.5k 1.0× 591 1.3× 244 2.9× 2 0.0× 37 0.7× 64 1.6k
R. A. Marino Germany 28 2.2k 1.5× 913 2.1× 414 4.9× 5 0.1× 83 1.6× 77 2.3k
Rok Roškar United States 25 1.9k 1.3× 822 1.9× 101 1.2× 2 0.0× 23 0.5× 34 2.0k

Countries citing papers authored by Long Wang

Since Specialization
Citations

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

Fields of papers citing papers by Long Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Long Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Long Wang. A scholar is included among the top collaborators of Long Wang 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 Long Wang. Long Wang 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.
Wang, Li, et al.. (2025). Unveiling Bifurcated Blue Straggler Sequences in NGC 2173: Insights from Binary Evolution. The Astrophysical Journal. 984(1). 52–52.
2.
Tanikawa, Ataru, et al.. (2025). Compact Binary Formation in Open Star Clusters III: Probability of Binary Black Holes Hidden Inside of Gaia Black Hole Binary. The Open Journal of Astrophysics. 8. 1 indexed citations
3.
Fujii, Michiko S., Long Wang, Ataru Tanikawa, Yutaka Hirai, & Takayuki R. Saitoh. (2024). Simulations predict intermediate-mass black hole formation in globular clusters. Science. 384(6703). 1488–1492. 24 indexed citations
4.
Low, Mordecai‐Mark Mac, Ralf S. Klessen, Eric P. Andersson, et al.. (2024). Massive star cluster formation. Astronomy and Astrophysics. 690. A94–A94. 18 indexed citations
5.
Zhou, Caicun, Jingbo Chen, Long Wang, et al.. (2024). PL02.04 Phase 3 Study of Ivonescimab (AK112) vs. Pembrolizumab as First-line Treatment for PD-L1-positive Advanced NSCLC: Primary Analysis of HARMONi-2. Journal of Thoracic Oncology. 19(10). S1–S1. 15 indexed citations
6.
Xu, Cheng, Baitian Tang, Chengyuan Li, et al.. (2024). Where do they come from?. Astronomy and Astrophysics. 684. A205–A205. 3 indexed citations
7.
Li, Chengyuan, Long Wang, Yue Wang, et al.. (2023). Multiple Stellar Populations at Less Evolved Stages. III. A Possible Helium Spread in NGC 2210. The Astrophysical Journal. 948(1). 8–8. 2 indexed citations
8.
Wang, Long & D. N. C. Lin. (2023). Tidal Disruption of Stellar Clusters and the Spatial Distribution of Their Remnants Near the Galactic Center. The Astrophysical Journal. 944(2). 140–140. 4 indexed citations
9.
Wang, Li, et al.. (2023). On the Origin of the Split Main Sequences of the Young Massive Cluster NGC 1856. The Astrophysical Journal. 949(2). 53–53. 7 indexed citations
10.
Tanikawa, Ataru, et al.. (2023). Compact binary formation in open star clusters – I. High formation efficiency of Gaia BHs and their multiplicities. Monthly Notices of the Royal Astronomical Society. 527(2). 4031–4039. 18 indexed citations
11.
Pang, Xiaoying, et al.. (2022). Investigating the UV-excess in Star Clusters with N -body Simulations: Predictions for Future CSST Observations*. Research in Astronomy and Astrophysics. 22(9). 95015–95015. 6 indexed citations
12.
Fujii, Michiko S., Kohei Hattori, Long Wang, et al.. (2022). SIRIUS Project – V. Formation of off-centre ionized bubbles associated with Orion Nebula Cluster. Monthly Notices of the Royal Astronomical Society. 514(1). 43–54. 8 indexed citations
13.
Fujii, Michiko S., et al.. (2022). SIRIUS Project – IV. The formation history of the Orion Nebula Cluster driven by clump mergers. Monthly Notices of the Royal Astronomical Society. 514(2). 2513–2526. 10 indexed citations
14.
15.
Spurzem, Rainer, Abbas Askar, Sambaran Banerjee, et al.. (2021). Preparing the next gravitational million-body simulations: evolution of single and binary stars in nbody6++gpu , mocca , and mcluster . Monthly Notices of the Royal Astronomical Society. 511(3). 4060–4089. 46 indexed citations
16.
Naab, Thorsten, Rainer Spurzem, Mirek Giersz, et al.. (2020). Intermediate mass black hole formation in compact young massive star clusters. Monthly Notices of the Royal Astronomical Society. 501(4). 5257–5273. 73 indexed citations
17.
Wang, Long, Keigo Nitadori, & Junichiro Makino. (2020). SDAR: Slow-Down Algorithmic Regularization code for solving few-body problems. Astrophysics Source Code Library. 1 indexed citations
18.
Wang, Long, Keigo Nitadori, & Junichiro Makino. (2020). A slow-down time-transformed symplectic integrator for solving the few-body problem. Monthly Notices of the Royal Astronomical Society. 493(3). 3398–3411. 39 indexed citations
19.
Giersz, Mirek, et al.. (2019). MOCCA-SURVEY Database I: Dissolution of tidally filling star clusters harboring black hole subsystem. Proceedings of the International Astronomical Union. 14(S351). 438–441. 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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