Nahuel Freitas
- Statistical and Nonlinear Physics top 2%
- Atomic and Molecular Physics, and Optics
- Artificial Intelligence
- Civil and Structural Engineering
- Cognitive Neuroscience
- Co-authors
- Massimiliano EspositoJuan Pablo PazJean‐Charles DelvenneEsteban A. MartinezKarel ProesmansVasco CavinaH. T. QuanChristian T. Schmiegelow
- Topics
- Advanced Thermodynamics and Statistical Mechanics (18 papers)Neural dynamics and brain function (5 papers)stochastic dynamics and bifurcation (5 papers)
- Cited by
- Statistical and Nonlinear PhysicsAtomic and Molecular Physics, and OpticsArtificial Intelligence
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersNature Communications
- Partner nations
- LuxembourgArgentinaAustria
In The Last Decade
Nahuel Freitas
20 papers receiving 305 citations
Peers
Comparison fields: 5 of 35
- Statistical and Nonlinear Physics 242
- Atomic and Molecular Physics, and Optics 150
- Artificial Intelligence 80
- Civil and Structural Engineering 40
- Cognitive Neuroscience 34
Countries citing papers authored by Nahuel Freitas
This map shows the geographic impact of Nahuel Freitas'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 Nahuel Freitas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nahuel Freitas more than expected).
Fields of papers citing papers by Nahuel Freitas
This network shows the impact of papers produced by Nahuel Freitas. 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 Nahuel Freitas. The network helps show where Nahuel Freitas may publish in the future.
Co-authorship network of co-authors of Nahuel Freitas
This figure shows the co-authorship network connecting the top 25 collaborators of Nahuel Freitas. A scholar is included among the top collaborators of Nahuel Freitas 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 Nahuel Freitas. Nahuel Freitas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 11 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 25 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | 14 | |
| 10 | 18 | |
| 11 | 16 | |
| 12 | 44 | |
| 13 | 30 | |
| 14 | 13 | |
| 15 | 3 | |
| 16 | 19 | |
| 17 | 12 | |
| 18 | 34 | |
| 19 | Heat transport through ion crystals | 23 |
| 20 | 21 |
About Nahuel Freitas
Nahuel Freitas is a scholar working on Statistical and Nonlinear Physics, Atomic and Molecular Physics, and Optics and Cognitive Neuroscience, having authored 22 papers that have together received 313 indexed citations. Recurring topics across this work include Advanced Thermodynamics and Statistical Mechanics (18 papers), Neural dynamics and brain function (5 papers) and stochastic dynamics and bifurcation (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (242 citations), Atomic and Molecular Physics, and Optics (150 citations) and Artificial Intelligence (80 citations). Nahuel Freitas has collaborated with scholars based in Luxembourg, Argentina and Austria. Frequent co-authors include Massimiliano Esposito, Juan Pablo Paz, Jean‐Charles Delvenne, Esteban A. Martinez, Karel Proesmans, Vasco Cavina, H. T. Quan, Christian T. Schmiegelow, Vedran Dunjko and Giovanna Morigi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.
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.