M. Ben-Nun

6.0k total citations · 1 hit paper
67 papers, 3.8k citations indexed

About

M. Ben-Nun is a scholar working on Atomic and Molecular Physics, and Optics, Spectroscopy and Physical and Theoretical Chemistry. According to data from OpenAlex, M. Ben-Nun has authored 67 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Atomic and Molecular Physics, and Optics, 14 papers in Spectroscopy and 10 papers in Physical and Theoretical Chemistry. Recurrent topics in M. Ben-Nun's work include Spectroscopy and Quantum Chemical Studies (36 papers), Advanced Chemical Physics Studies (31 papers) and Photochemistry and Electron Transfer Studies (10 papers). M. Ben-Nun is often cited by papers focused on Spectroscopy and Quantum Chemical Studies (36 papers), Advanced Chemical Physics Studies (31 papers) and Photochemistry and Electron Transfer Studies (10 papers). M. Ben-Nun collaborates with scholars based in United States, Israel and United Kingdom. M. Ben-Nun's co-authors include Todd J. Martı́nez, R. D. Levine, Jason Quenneville, F. Molnár, Klaus Schulten, Pete Riley, Kent R. Wilson, Guy Ashkenazi, Donald G. Truhlar and Michael D. Hack and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Physical Review Letters.

In The Last Decade

M. Ben-Nun

63 papers receiving 3.7k citations

Hit Papers

Ab Initio Multiple Spawning:  Photochemistry from First P... 2000 2026 2008 2017 2000 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Ben-Nun United States 32 3.0k 882 848 422 380 67 3.8k
P. W. Langhoff United States 34 4.1k 1.4× 1.1k 1.3× 820 1.0× 252 0.6× 250 0.7× 115 4.9k
Moshe Shapiro Israel 45 7.1k 2.4× 1.9k 2.2× 470 0.6× 340 0.8× 196 0.5× 240 7.9k
M.W. Evans United Kingdom 28 2.4k 0.8× 838 1.0× 281 0.3× 75 0.2× 189 0.5× 326 3.2k
M. Beck Germany 21 2.4k 0.8× 753 0.9× 377 0.4× 72 0.2× 69 0.2× 75 3.4k
J S Briggs Germany 44 6.2k 2.1× 1.5k 1.7× 487 0.6× 109 0.3× 225 0.6× 196 7.1k
Kazuo Takatsuka Japan 34 3.9k 1.3× 894 1.0× 705 0.8× 52 0.1× 184 0.5× 192 4.4k
P. Hvelplund Denmark 49 5.8k 2.0× 3.0k 3.4× 291 0.3× 202 0.5× 412 1.1× 245 7.8k
Harry M. Quiney Australia 35 2.3k 0.8× 543 0.6× 187 0.2× 74 0.2× 191 0.5× 142 3.8k
L. S. Cederbaum Germany 37 4.9k 1.6× 1.5k 1.7× 693 0.8× 65 0.2× 136 0.4× 94 5.7k
Valérie Blanchet France 30 2.9k 1.0× 1.3k 1.4× 282 0.3× 73 0.2× 73 0.2× 87 3.4k

Countries citing papers authored by M. Ben-Nun

Since Specialization
Citations

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

Fields of papers citing papers by M. Ben-Nun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Ben-Nun. 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 M. Ben-Nun. The network helps show where M. Ben-Nun may publish in the future.

Co-authorship network of co-authors of M. Ben-Nun

This figure shows the co-authorship network connecting the top 25 collaborators of M. Ben-Nun. A scholar is included among the top collaborators of M. Ben-Nun 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 M. Ben-Nun. M. Ben-Nun 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
2.
Riley, Pete, M. Ben-Nun, Erika Palmerio, et al.. (2025). Understanding the global structure of the September 5, 2022, coronal mass ejection using sunRunner3D. Journal of Space Weather and Space Climate. 15. 17–17.
3.
Riley, Pete, et al.. (2024). Using sunRunner3D to interpret the global structure of the heliosphere from in situ measurements. Journal of Space Weather and Space Climate. 14. 12–12.
4.
Turtle, James, M. Ben-Nun, & Pete Riley. (2024). Enhancing seasonal influenza projections: A mechanistic metapopulation model for long-term scenario planning. Epidemics. 47. 100758–100758.
5.
Ben-Nun, M., Tibor Török, Erika Palmerio, et al.. (2023). Deflection of Coronal Mass Ejections in Unipolar Ambient Magnetic Fields. The Astrophysical Journal. 957(2). 74–74. 2 indexed citations
6.
Riley, Pete, Allison Riley, James Turtle, & M. Ben-Nun. (2022). COVID-19 deaths: Which explanatory variables matter the most?. PLoS ONE. 17(4). e0266330–e0266330. 4 indexed citations
7.
Riley, Pete & M. Ben-Nun. (2022). sunRunner1D: A Tool for Exploring ICME Evolution through the Inner Heliosphere. Universe. 8(9). 447–447. 5 indexed citations
8.
Turtle, James, Pete Riley, M. Ben-Nun, & Steven Riley. (2021). Accurate influenza forecasts using type-specific incidence data for small geographic units. PLoS Computational Biology. 17(7). e1009230–e1009230. 3 indexed citations
10.
Riley, Pete, et al.. (2021). COVID-19: On the Disparity in Outcomes Between Military and Civilian Populations. Military Medicine. 188(1-2). 311–315. 3 indexed citations
11.
Owens, M. J., Matthew Lang, Luke Barnard, et al.. (2020). A Computationally Efficient, Time-Dependent Model of the Solar Wind for Use as a Surrogate to Three-Dimensional Numerical Magnetohydrodynamic Simulations. Solar Physics. 295(3). 51 indexed citations
12.
Riley, Pete, M. Ben-Nun, J. A. Linker, et al.. (2015). Early Characterization of the Severity and Transmissibility of Pandemic Influenza Using Clinical Episode Data from Multiple Populations. PLoS Computational Biology. 11(9). e1004392–e1004392. 4 indexed citations
13.
Riley, Pete, M. Ben-Nun, Richard F. Armenta, et al.. (2013). Multiple Estimates of Transmissibility for the 2009 Influenza Pandemic Based on Influenza-like-Illness Data from Small US Military Populations. PLoS Computational Biology. 9(5). e1003064–e1003064. 14 indexed citations
14.
Ben-Nun, M., F. Molnár, Klaus Schulten, & Todd J. Martı́nez. (2002). The role of intersection topography in bond selectivity of cis-trans photoisomerization. Proceedings of the National Academy of Sciences. 99(4). 1769–1773. 134 indexed citations
15.
Ben-Nun, M. & Todd J. Martı́nez. (2000). Photodynamics of ethylene: ab initio studies of conical intersections. Chemical Physics. 259(2-3). 237–248. 188 indexed citations
16.
Ben-Nun, M., Jason Quenneville, & Todd J. Martı́nez. (2000). Ab Initio Multiple Spawning:  Photochemistry from First Principles Quantum Molecular Dynamics. The Journal of Physical Chemistry A. 104(22). 5161–5175. 677 indexed citations breakdown →
17.
Ben-Nun, M., F. Molnár, Hui Lü, et al.. (1998). Quantum dynamics of the femtosecond photoisomerization of retinal in bacteriorhodopsin. Faraday Discussions. 110(110). 447–462. 75 indexed citations
18.
Ben-Nun, M. & Todd J. Martı́nez. (1998). Nonadiabatic molecular dynamics: Validation of the multiple spawning method for a multidimensional problem. The Journal of Chemical Physics. 108(17). 7244–7257. 340 indexed citations
19.
Ben-Nun, M. & Todd J. Martı́nez. (1998). Direct evaluation of the Pauli repulsion energy using `classical' wavefunctions in hybrid quantum/classical potential energy surfaces. Chemical Physics Letters. 290(1-3). 289–295. 20 indexed citations
20.
Ben-Nun, M., M. Brouard, J. P. Simons, & R. D. Levine. (1993). Peripheral chemical reactions. Chemical Physics Letters. 210(4-6). 423–431. 35 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026