R. Nora

4.5k total citations
51 papers, 857 citations indexed

About

R. Nora is a scholar working on Nuclear and High Energy Physics, Geophysics and Mechanics of Materials. According to data from OpenAlex, R. Nora has authored 51 papers receiving a total of 857 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Nuclear and High Energy Physics, 20 papers in Geophysics and 17 papers in Mechanics of Materials. Recurrent topics in R. Nora's work include Laser-Plasma Interactions and Diagnostics (42 papers), High-pressure geophysics and materials (20 papers) and Nuclear Physics and Applications (14 papers). R. Nora is often cited by papers focused on Laser-Plasma Interactions and Diagnostics (42 papers), High-pressure geophysics and materials (20 papers) and Nuclear Physics and Applications (14 papers). R. Nora collaborates with scholars based in United States, France and Israel. R. Nora's co-authors include R. Betti, B. K. Spears, J. L. Peterson, K. S. Anderson, S. Brandon, J. E. Field, Kelli Humbird, A. R. Christopherson, A. Bose and K. M. Woo and has published in prestigious journals such as Science, Physical Review Letters and Review of Scientific Instruments.

In The Last Decade

R. Nora

46 papers receiving 832 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Nora United States 18 707 376 298 253 163 51 857
C. J. Forrest United States 15 554 0.8× 163 0.4× 152 0.5× 173 0.7× 262 1.6× 70 686
R. De Angelis Italy 16 549 0.8× 362 1.0× 211 0.7× 101 0.4× 135 0.8× 76 735
D. Klír Czechia 19 1.0k 1.5× 492 1.3× 297 1.0× 124 0.5× 360 2.2× 136 1.1k
P.-Y. Chang United States 17 1.0k 1.5× 542 1.4× 309 1.0× 368 1.5× 66 0.4× 37 1.2k
E. S. Dodd United States 19 1.0k 1.5× 569 1.5× 620 2.1× 188 0.7× 118 0.7× 49 1.2k
P. Kubeš Czechia 19 1.1k 1.6× 482 1.3× 293 1.0× 106 0.4× 381 2.3× 158 1.2k
Vladimir Khudik United States 17 789 1.1× 527 1.4× 509 1.7× 153 0.6× 65 0.4× 60 926
A. L. Velikovich United States 18 733 1.0× 383 1.0× 412 1.4× 138 0.5× 51 0.3× 51 872
R. Miklaszewski Poland 16 536 0.8× 277 0.7× 310 1.0× 63 0.2× 174 1.1× 64 932
Cristián Pavéz Chile 15 588 0.8× 189 0.5× 223 0.7× 45 0.2× 267 1.6× 77 798

Countries citing papers authored by R. Nora

Since Specialization
Citations

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

Fields of papers citing papers by R. Nora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R. Nora

This figure shows the co-authorship network connecting the top 25 collaborators of R. Nora. A scholar is included among the top collaborators of R. Nora 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 R. Nora. R. Nora 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.
Spears, B. K., S. Brandon, D. T. Casey, et al.. (2025). Predicting fusion ignition at the National Ignition Facility with physics-informed deep learning. Science. 389(6761). 727–731. 2 indexed citations
2.
Follett, R. K., A. Colaïtis, I. V. Igumenshchev, et al.. (2025). An experimentally informed design process for future inertial confinement fusion facilities. Physics of Plasmas. 32(4). 1 indexed citations
3.
MacLaren, S. A., J. L. Milovich, D. E. Fratanduono, et al.. (2024). Indirect drive ICF design study for a 3 MJ NIF enhanced yield capability. High Energy Density Physics. 52. 101134–101134. 1 indexed citations
4.
Adrian, P. J., R. M. Bionta, D. T. Casey, et al.. (2024). Diagnosing hot-spot symmetry in surrogate ignition experiments via secondary DT-neutron spectroscopy at the NIF. Physics of Plasmas. 31(8). 2 indexed citations
5.
Hurricane, O. A., D. A. Callahan, D. T. Casey, et al.. (2024). Energy Principles of Scientific Breakeven in an Inertial Fusion Experiment. Physical Review Letters. 132(6). 65103–65103. 36 indexed citations
6.
Kunimune, J. H., D. T. Casey, Bogdan Kustowski, et al.. (2024). 3D reconstruction of an inertial-confinement fusion implosion with neural networks using multiple heterogeneous data sources. Review of Scientific Instruments. 95(7). 2 indexed citations
7.
Christopherson, A. R., O. A. Hurricane, C. R. Weber, et al.. (2023). Alpha-heating analysis of burning plasma and ignition experiments on the National Ignition Facility. Physics of Plasmas. 30(6). 5 indexed citations
8.
Moore, A. S., D. J. Schlossberg, M. J. Eckart, et al.. (2022). Constraining time-dependent ion temperature measurements in inertial confinement fusion (ICF) implosions with an intermediate distance neutron time-of-flight (nToF) detector. Review of Scientific Instruments. 93(11). 113536–113536. 4 indexed citations
9.
10.
Kustowski, Bogdan, L. Massé, J. M. Koning, et al.. (2020). Engineering Robustness into Inertial Confinement Fusion Designs. Bulletin of the American Physical Society. 2020. 1 indexed citations
11.
MacGowan, B. J., O. L. Landen, D. T. Casey, et al.. (2019). Understanding 3D Asymmetries In X-ray Drive At The National Ignition Facility Using a Simple View Factor Metric. APS Division of Plasma Physics Meeting Abstracts. 2019. 1 indexed citations
12.
Amendt, Peter, D. Ho, R. Nora, Y. Ping, & V. A. Smalyuk. (2019). High-Volume and -Adiabat Capsule (``HVAC'') Ignition with Layered Gas-filled Capsules in Advanced Hohlraums. APS. 2019.
13.
Kruse, Michael, J. E. Field, James A. Gaffney, et al.. (2019). Area-Based Image Metrics Elucidate Differences Between Radiation-Hydrodynamics Simulations and NIF Experimental X-ray Images. APS Division of Plasma Physics Meeting Abstracts. 2019. 1 indexed citations
14.
Mariscal, D., P. K. Patel, S. Le Pape, et al.. (2018). Experimental investigation of the source of mode one asymmetries in indirect-drive ICF implosions. Bulletin of the American Physical Society. 2018.
15.
Nora, R., J. E. Field, C. V. Young, et al.. (2018). 3D HYDRA Capsule Studies on the Effect of Hohlraum Windows. Bulletin of the American Physical Society. 2018.
16.
Chen, Hui, T. Ma, R. Nora, et al.. (2017). On krypton-doped capsule implosion experiments at the National Ignition Facility. Physics of Plasmas. 24(7). 18 indexed citations
17.
Humbird, Kelli, Ryan G. McClarren, J. E. Field, et al.. (2017). Using deep neural networks to augment NIF post-shot analysis. Bulletin of the American Physical Society. 2017. 1 indexed citations
18.
Ma, T., P. K. Patel, M. B. Schneider, et al.. (2016). Development of a krypton-doped gas symmetry capsule platform for x-ray spectroscopy of implosion cores on the NIF. Review of Scientific Instruments. 87(11). 11E327–11E327. 14 indexed citations
19.
Humbird, Kelli, J. L. Peterson, S. Brandon, et al.. (2016). Surrogate models for identifying robust, high yield regions of parameter space for ICF implosion simulations. Bulletin of the American Physical Society. 2016. 1 indexed citations
20.
Nora, R., B. K. Spears, Riccardo Tommasini, et al.. (2015). Quantifying low-mode shell asymmetry as a means to predict ICF implosion performance on the NIF. Bulletin of the American Physical Society. 2015. 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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