F. Sobreira

26.8k total citations
11 papers, 212 citations indexed

About

F. Sobreira is a scholar working on Astronomy and Astrophysics, Nuclear and High Energy Physics and Instrumentation. According to data from OpenAlex, F. Sobreira has authored 11 papers receiving a total of 212 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Astronomy and Astrophysics, 4 papers in Nuclear and High Energy Physics and 2 papers in Instrumentation. Recurrent topics in F. Sobreira's work include Cosmology and Gravitation Theories (8 papers), Galaxies: Formation, Evolution, Phenomena (7 papers) and Astronomy and Astrophysical Research (2 papers). F. Sobreira is often cited by papers focused on Cosmology and Gravitation Theories (8 papers), Galaxies: Formation, Evolution, Phenomena (7 papers) and Astronomy and Astrophysical Research (2 papers). F. Sobreira collaborates with scholars based in Brazil, United Kingdom and United States. F. Sobreira's co-authors include Ilya L. Shapiro, Guilherme de Berredo-Peixoto, S. Carneiro, C. Pigozzo, P. C. de Holanda, Alexei A. Starobinsky, H. Camacho, Asa F. L. Bluck, D. J. James and W G Hartley and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Physics Letters B.

In The Last Decade

F. Sobreira

11 papers receiving 201 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
F. Sobreira Brazil 7 173 79 47 30 20 11 212
Caroline Heneka Germany 9 185 1.1× 78 1.0× 48 1.0× 18 0.6× 8 0.4× 20 214
M. Ramatsoku South Africa 11 304 1.8× 110 1.4× 76 1.6× 21 0.7× 8 0.4× 22 336
A. Charbonnier Brazil 7 253 1.5× 162 2.1× 69 1.5× 15 0.5× 19 0.9× 11 308
Conor McPartland United States 9 235 1.4× 48 0.6× 71 1.5× 14 0.5× 13 0.7× 12 266
A. Zanichelli Italy 9 283 1.6× 89 1.1× 101 2.1× 14 0.5× 8 0.4× 26 291
Kate Storey-Fisher United States 9 197 1.1× 50 0.6× 73 1.6× 17 0.6× 9 0.5× 13 237
Cristiano G. Sabiu South Korea 12 307 1.8× 100 1.3× 76 1.6× 9 0.3× 20 1.0× 24 330
Camille Avestruz United States 8 243 1.4× 49 0.6× 104 2.2× 10 0.3× 12 0.6× 27 264
Long-Long Feng China 13 287 1.7× 50 0.6× 59 1.3× 8 0.3× 9 0.5× 42 326
Martin Eriksen Spain 11 205 1.2× 31 0.4× 83 1.8× 16 0.5× 26 1.3× 23 243

Countries citing papers authored by F. Sobreira

Since Specialization
Citations

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

Fields of papers citing papers by F. Sobreira

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Sobreira

This figure shows the co-authorship network connecting the top 25 collaborators of F. Sobreira. A scholar is included among the top collaborators of F. Sobreira 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 F. Sobreira. F. Sobreira is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
2.
Conselice, Christopher J., Alfonso Aragón‐Salamanca, Nan Li, et al.. (2020). Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging. Monthly Notices of the Royal Astronomical Society. 493(3). 4209–4228. 66 indexed citations
3.
Carneiro, S., P. C. de Holanda, C. Pigozzo, & F. Sobreira. (2019). Is the H0 tension suggesting a fourth neutrino generation?. Physical review. D. 100(2). 27 indexed citations
4.
Sobreira, F., et al.. (2018). On higher derivative corrections to the R+R2 inflationary model. Journal of Cosmology and Astroparticle Physics. 2018(12). 7–7. 20 indexed citations
5.
Rosenfeld, R., et al.. (2018). Forecasts for warm dark matter from photometric galaxy surveys. Monthly Notices of the Royal Astronomical Society. 481(1). 1290–1299. 3 indexed citations
6.
Sobreira, F., Christoph Tremmel, & Dean J. Krusienski. (2018). Modeling the Visual Pathway for Stimulus Optimization in Brain-Computer Interfaces. 1672–1675. 1 indexed citations
7.
Zhai, Zhongxu, Jeremy L. Tinker, ChangHoon Hahn, et al.. (2017). The Clustering of Luminous Red Galaxies at z ∼ 0.7 from EBOSS and BOSS Data. The Astrophysical Journal. 848(2). 76–76. 46 indexed citations
8.
Simoni, F. de, F. Sobreira, A. Carnero Rosell, et al.. (2013). Large-scale analysis of the SDSS-III DR8 photometric luminous galaxies angular correlation function. Monthly Notices of the Royal Astronomical Society. 435(4). 3017–3027. 14 indexed citations
9.
Sobreira, F., et al.. (2011). Effective potential in curved space and cut-off regularizations. Physics Letters B. 705(3). 273–278. 9 indexed citations
10.
Sobreira, F., F. de Simoni, R. Rosenfeld, et al.. (2011). Cosmological forecasts from photometric measurements of the angular correlation function. Physical review. D. Particles, fields, gravitation, and cosmology. 84(10). 4 indexed citations
11.
Berredo-Peixoto, Guilherme de, Ilya L. Shapiro, & F. Sobreira. (2005). SIMPLE COSMOLOGICAL MODEL WITH RELATIVISTIC GAS. Modern Physics Letters A. 20(35). 2723–2734. 21 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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