Sergio J Sciutto

6.7k total citations
33 papers, 208 citations indexed

About

Sergio J Sciutto is a scholar working on Nuclear and High Energy Physics, Condensed Matter Physics and Statistical and Nonlinear Physics. According to data from OpenAlex, Sergio J Sciutto has authored 33 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Nuclear and High Energy Physics, 6 papers in Condensed Matter Physics and 4 papers in Statistical and Nonlinear Physics. Recurrent topics in Sergio J Sciutto's work include Astrophysics and Cosmic Phenomena (18 papers), Particle physics theoretical and experimental studies (16 papers) and High-Energy Particle Collisions Research (8 papers). Sergio J Sciutto is often cited by papers focused on Astrophysics and Cosmic Phenomena (18 papers), Particle physics theoretical and experimental studies (16 papers) and High-Energy Particle Collisions Research (8 papers). Sergio J Sciutto collaborates with scholars based in Argentina, United States and Spain. Sergio J Sciutto's co-authors include A. Cillis, C. A. Garcı́a Canal, H. Fanchiotti, Matias Jorge Tueros, Jorge F. Soriano, Felix Kling, Luis A. Anchordoqui, Luis A. Anchordoqui, T. Tarutina and A. Zepeda and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical review. B, Condensed matter and Journal of Computational Physics.

In The Last Decade

Sergio J Sciutto

30 papers receiving 207 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergio J Sciutto Argentina 10 148 23 19 12 12 33 208
Peter T. Lake United States 8 133 0.9× 21 0.9× 7 0.4× 21 1.8× 28 2.3× 14 223
W.S. Toothacker United States 8 88 0.6× 24 1.0× 12 0.6× 17 1.4× 5 0.4× 18 156
B. Lundberg United States 9 244 1.6× 7 0.3× 21 1.1× 11 0.9× 5 0.4× 18 289
R. Nania Switzerland 11 216 1.5× 11 0.5× 10 0.5× 9 0.8× 3 0.3× 20 241
R. Whitman United States 9 237 1.6× 6 0.3× 21 1.1× 11 0.9× 5 0.4× 12 287
M. Caria Italy 5 50 0.3× 9 0.4× 5 0.3× 17 1.4× 12 1.0× 12 103
Darío Rodrigues Argentina 10 148 1.0× 6 0.3× 6 0.3× 13 1.1× 6 0.5× 31 233
G. Valenti Italy 11 252 1.7× 7 0.3× 10 0.5× 5 0.4× 4 0.3× 29 274

Countries citing papers authored by Sergio J Sciutto

Since Specialization
Citations

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

Fields of papers citing papers by Sergio J Sciutto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sergio J Sciutto. 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 Sergio J Sciutto. The network helps show where Sergio J Sciutto may publish in the future.

Co-authorship network of co-authors of Sergio J Sciutto

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio J Sciutto. A scholar is included among the top collaborators of Sergio J Sciutto 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 Sergio J Sciutto. Sergio J Sciutto 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.
Sciutto, Sergio J, et al.. (2023). Gauging the cosmic ray muon puzzle with the Forward Physics Facility. Proceedings Of Science. 388–388. 5 indexed citations
2.
Anchordoqui, Luis A., C. A. Garcı́a Canal, Felix Kling, Sergio J Sciutto, & Jorge F. Soriano. (2022). An explanation of the muon puzzle of ultrahigh-energy cosmic rays and the role of the Forward Physics Facility for model improvement. Journal of High Energy Astrophysics. 34. 19–32. 17 indexed citations
3.
Anchordoqui, Luis A., et al.. (2020). Through the looking-glass with ALICE into the quark-gluon plasma: A new test for hadronic interaction models used in air shower simulations. Physics Letters B. 810. 135837–135837. 9 indexed citations
4.
Sciutto, Sergio J. (2019). Air showers, hadronic models, and muon production. SHILAP Revista de lepidopterología. 210. 2007–2007. 3 indexed citations
5.
Canal, C. A. Garcı́a, J. I. Illana, M. Masip, & Sergio J Sciutto. (2016). A new observable in extensive air showers. Astroparticle Physics. 85. 50–53.
6.
Cornet, Fernando, C. A. Garcı́a Canal, A. Grau, G. Pancheri, & Sergio J Sciutto. (2015). Photoproduction total cross section and shower development. Physical review. D. Particles, fields, gravitation, and cosmology. 92(11). 1 indexed citations
7.
Sciutto, Sergio J, et al.. (2011). AIRES: AIRshower Extended Simulations. Astrophysics Source Code Library. 1 indexed citations
8.
Anchordoqui, Luis A., A. Delgado, C. A. Garcı́a Canal, & Sergio J Sciutto. (2008). Hunting long-lived gluinos at the Pierre Auger Observatory. Physical review. D. Particles, fields, gravitation, and cosmology. 77(2). 5 indexed citations
9.
Fanchiotti, H., Sergio J Sciutto, C. A. Garcı́a Canal, & C. Hojvat. (2004). ANALYSIS OF SUNSPOT NUMBER FLUCTUATIONS. Fractals. 12(4). 405–411. 4 indexed citations
10.
Tanco, Gustavo Medina, et al.. (2003). Neural Networks as a Statistic Diagnostic Tool for Mass Composition at the Highest Energies. International Cosmic Ray Conference. 2. 587. 1 indexed citations
11.
Anchordoqui, Luis A., et al.. (1999). Extensive air showers rounded up by aires + sibyll/qgsjet. CERN Bulletin. 1. 147.
12.
Cillis, A., H. Fanchiotti, C. A. Garcı́a Canal, & Sergio J Sciutto. (1999). Influence of the LPM effect and dielectric suppression on particle air showers. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 59(11). 23 indexed citations
13.
Sciutto, Sergio J. (1999). Air Shower Simulations with the AIRES System. arXiv (Cornell University). 1. 411. 1 indexed citations
14.
Sciutto, Sergio J. (1996). The shape of self-avoiding walks. Journal of Physics A Mathematical and General. 29(17). 5455–5473. 12 indexed citations
15.
Sciutto, Sergio J. (1994). Study of the shape of random walks. Journal of Physics A Mathematical and General. 27(21). 7015–7034. 14 indexed citations
16.
Sciutto, Sergio J. (1993). POWEV: a subroutine package to evaluate eigenvalues and eigenvectors of large sparse matrices. Computer Physics Communications. 77(1). 95–106. 1 indexed citations
17.
Sciutto, Sergio J. (1989). Polyfit — A package for polynomial fitting. Computer Physics Communications. 52(3). 427–442. 4 indexed citations
18.
Marconi, Umberto Marini Bettolo, et al.. (1989). Exact two-particle effective interaction and superconductivity in the two-level Hubbard model. Physical review. B, Condensed matter. 39(7). 4277–4284. 2 indexed citations
19.
Fanchiotti, H., C. A. Garcı́a Canal, & Sergio J Sciutto. (1985). Gauge Potts model with generalized action: A Monte Carlo analysis. Physical review. D. Particles, fields, gravitation, and cosmology/Physical review. D. Particles and fields. 32(4). 986–989. 2 indexed citations
20.
Fanchiotti, H., Sergio J Sciutto, & H. Vucetich. (1984). Monte Carlo calculations on the gauge Potts model. The European Physical Journal B. 55(1). 57–60. 2 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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