Mark D. Goodsell

2.9k total citations · 1 hit paper
39 papers, 1.2k citations indexed

About

Mark D. Goodsell is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Statistical and Nonlinear Physics. According to data from OpenAlex, Mark D. Goodsell has authored 39 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Nuclear and High Energy Physics, 10 papers in Astronomy and Astrophysics and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Mark D. Goodsell's work include Particle physics theoretical and experimental studies (38 papers), Black Holes and Theoretical Physics (16 papers) and Dark Matter and Cosmic Phenomena (14 papers). Mark D. Goodsell is often cited by papers focused on Particle physics theoretical and experimental studies (38 papers), Black Holes and Theoretical Physics (16 papers) and Dark Matter and Cosmic Phenomena (14 papers). Mark D. Goodsell collaborates with scholars based in France, Germany and Switzerland. Mark D. Goodsell's co-authors include Florian Staub, Karim Benakli, Andreas Ringwald, Michele Cicoli, Kilian Nickel, Johannes Braathen, Steven Abel, Stefan Liebler, W. Porod and Benjamin Fuks and has published in prestigious journals such as Nuclear Physics B, Physics Letters B and Computer Physics Communications.

In The Last Decade

Mark D. Goodsell

39 papers receiving 1.2k citations

Hit Papers

The type IIB string axiverse and its low-energy phenomeno... 2012 2026 2016 2021 2012 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. The type IIB string axiverse and its low-energy phenomenology
    2012 308 citations Mark D. Goodsell et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark D. Goodsell France 18 1.1k 506 65 55 31 39 1.2k
Gautam Bhattacharyya India 24 1.5k 1.3× 350 0.7× 39 0.6× 32 0.6× 39 1.3× 87 1.5k
S. Fichet Brazil 16 634 0.6× 299 0.6× 64 1.0× 79 1.4× 21 0.7× 42 692
Biswarup Mukhopadhyaya India 22 1.9k 1.6× 725 1.4× 63 1.0× 33 0.6× 62 2.0× 143 1.9k
Andrea Tesi Italy 19 977 0.9× 506 1.0× 21 0.3× 32 0.6× 27 0.9× 31 1.0k
Jeonghyeon Song South Korea 21 1.2k 1.0× 428 0.8× 26 0.4× 27 0.5× 48 1.5× 82 1.2k
Alexandre Alves Brazil 18 898 0.8× 370 0.7× 30 0.5× 28 0.5× 42 1.4× 34 915
Elisabetta Furlan Switzerland 15 921 0.8× 196 0.4× 41 0.6× 34 0.6× 23 0.7× 19 973
Frank F. Deppisch United Kingdom 25 1.9k 1.6× 221 0.4× 32 0.5× 35 0.6× 34 1.1× 60 1.9k
Debajyoti Choudhury India 24 1.9k 1.6× 498 1.0× 46 0.7× 45 0.8× 27 0.9× 121 1.9k
Ilia Gogoladze United States 28 2.1k 1.8× 856 1.7× 81 1.2× 24 0.4× 31 1.0× 87 2.1k

Countries citing papers authored by Mark D. Goodsell

Since Specialization
Citations

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

Fields of papers citing papers by Mark D. Goodsell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D. Goodsell. 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 Mark D. Goodsell. The network helps show where Mark D. Goodsell may publish in the future.

Co-authorship network of co-authors of Mark D. Goodsell

This figure shows the co-authorship network connecting the top 25 collaborators of Mark D. Goodsell. A scholar is included among the top collaborators of Mark D. Goodsell 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 Mark D. Goodsell. Mark D. Goodsell 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.
Fuks, Benjamin, et al.. (2025). A joint explanation for the soft lepton and monojet LHC excesses in the wino-bino model. The European Physical Journal C. 85(10). 1 indexed citations
2.
Fuks, Benjamin, et al.. (2025). Monojets from compressed weak frustrated dark matter. Physical review. D. 111(5). 4 indexed citations
3.
Cornell, Alan S., et al.. (2025). Improving smuon searches with neural networks. The European Physical Journal C. 85(1). 1 indexed citations
4.
Faraggi, Alon E. & Mark D. Goodsell. (2024). $$M_W$$ in string derived Z$$^\prime $$ models. The European Physical Journal C. 84(6). 2 indexed citations
5.
Fuks, Benjamin, et al.. (2024). Seeking a coherent explanation of LHC excesses for compressed spectra. The European Physical Journal C. 84(11). 6 indexed citations
6.
Goodsell, Mark D., et al.. (2023). Active learning BSM parameter spaces. The European Physical Journal C. 83(4). 8 indexed citations
7.
Benakli, Karim, et al.. (2023). W boson mass in minimal Dirac gaugino scenarios. The European Physical Journal C. 83(1). 4 indexed citations
8.
Braathen, Johannes, et al.. (2021). Expectation management. The European Physical Journal C. 81(6). 7 indexed citations
9.
10.
Braathen, Johannes, et al.. (2017). Match before you run: N is better than N-1. arXiv (Cornell University). 1 indexed citations
11.
Braathen, Johannes, Mark D. Goodsell, & Florian Staub. (2017). Supersymmetric and non-supersymmetric models without catastrophic Goldstone bosons. The European Physical Journal C. 77(11). 757–757. 41 indexed citations
12.
Goodsell, Mark D., Stefan Liebler, & Florian Staub. (2017). Generic calculation of two-body partial decay widths at the full one-loop level. The European Physical Journal C. 77(11). 758–758. 34 indexed citations
13.
Goodsell, Mark D., Kilian Nickel, & Florian Staub. (2016). The Higgs mass in the MSSM at two-loop order beyond minimal flavour violation. Physics Letters B. 758. 18–25. 6 indexed citations
14.
Goodsell, Mark D., Kilian Nickel, & Florian Staub. (2015). Two-loop Higgs mass calculations in supersymmetric models beyond the MSSM with SARAH and SPheno. The European Physical Journal C. 75(1). 65 indexed citations
15.
Goodsell, Mark D., et al.. (2015). Dark matter scenarios in a UV-complete model with Dirac gauginos. arXiv (Cornell University). 2 indexed citations
16.
Goodsell, Mark D., Kilian Nickel, & Florian Staub. (2015). Generic two-loop Higgs mass calculation from a diagrammatic approach. The European Physical Journal C. 75(6). 47 indexed citations
17.
Goodsell, Mark D., et al.. (2014). Constrained minimal Dirac gaugino supersymmetric standard model. Physical review. D. Particles, fields, gravitation, and cosmology. 90(4). 27 indexed citations
18.
Abel, Steven & Mark D. Goodsell. (2011). Easy Dirac Gauginos. Durham Research Online (Durham University). 32 indexed citations
19.
Benakli, Karim & Mark D. Goodsell. (2010). Dirac gauginos and kinetic mixing. Nuclear Physics B. 830(1-2). 315–329. 47 indexed citations
20.
Benakli, Karim & Mark D. Goodsell. (2009). Dirac gauginos in general gauge mediation. Nuclear Physics B. 816(1-2). 185–203. 74 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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