L. de Arcangelis

6.1k total citations
136 papers, 4.3k citations indexed

About

L. de Arcangelis is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics and Cognitive Neuroscience. According to data from OpenAlex, L. de Arcangelis has authored 136 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Condensed Matter Physics, 37 papers in Statistical and Nonlinear Physics and 35 papers in Cognitive Neuroscience. Recurrent topics in L. de Arcangelis's work include Theoretical and Computational Physics (38 papers), Neural dynamics and brain function (35 papers) and earthquake and tectonic studies (32 papers). L. de Arcangelis is often cited by papers focused on Theoretical and Computational Physics (38 papers), Neural dynamics and brain function (35 papers) and earthquake and tectonic studies (32 papers). L. de Arcangelis collaborates with scholars based in Italy, France and Switzerland. L. de Arcangelis's co-authors include Hans J. Herrmann, Antonio Coniglio, S. Redner, Eugenio Lippiello, C. Godano, Hartmut Herrmann, Carla Perrone‐Capano, Fabrizio Lombardi, Emanuela Del Gado and Naeem Jan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Nature Communications.

In The Last Decade

L. de Arcangelis

134 papers receiving 4.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. de Arcangelis Italy 36 1.3k 1.0k 902 844 659 136 4.3k
Maya Paczuski United States 30 1.4k 1.1× 1.2k 1.2× 212 0.2× 563 0.7× 343 0.5× 86 3.9k
S. Ciliberto France 46 998 0.8× 3.5k 3.3× 375 0.4× 500 0.6× 899 1.4× 169 8.6k
Zeev Olami Israel 19 895 0.7× 466 0.4× 274 0.3× 478 0.6× 273 0.4× 44 2.1k
H. G. E. Hentschel United States 29 974 0.8× 1.0k 1.0× 149 0.2× 125 0.1× 690 1.0× 110 4.1k
Richard F. Voss United States 28 1.3k 1.0× 860 0.8× 416 0.5× 94 0.1× 417 0.6× 44 4.9k
J. F. J. van den Brand Belgium 49 707 0.6× 5.0k 4.8× 629 0.7× 218 0.3× 1.1k 1.6× 316 9.4k
R. P. Taylor United States 39 449 0.4× 904 0.9× 1.3k 1.4× 423 0.5× 499 0.8× 216 5.6k
√Ålvaro Corral Spain 23 383 0.3× 448 0.4× 186 0.2× 850 1.0× 136 0.2× 64 2.4k
Yasuji Sawada Japan 33 1.3k 1.0× 1.3k 1.2× 280 0.3× 46 0.1× 850 1.3× 170 4.7k
Masaki Sano Japan 39 2.6k 2.1× 2.1k 2.0× 340 0.4× 44 0.1× 1.0k 1.5× 162 8.2k

Countries citing papers authored by L. de Arcangelis

Since Specialization
Citations

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

Fields of papers citing papers by L. de Arcangelis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L. de Arcangelis. 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 L. de Arcangelis. The network helps show where L. de Arcangelis may publish in the future.

Co-authorship network of co-authors of L. de Arcangelis

This figure shows the co-authorship network connecting the top 25 collaborators of L. de Arcangelis. A scholar is included among the top collaborators of L. de Arcangelis 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 L. de Arcangelis. L. de Arcangelis 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.
Herrmann, Hans J., et al.. (2025). Inhibitory neurons and the asymmetric shape of neuronal avalanches. Physical review. E. 111(2). 24133–24133. 2 indexed citations
2.
Arcangelis, L. de, et al.. (2024). Ising-like model replicating time-averaged spiking behaviour of in vitro neuronal networks. Scientific Reports. 14(1). 7002–7002. 4 indexed citations
3.
Scarpetta, Silvia, et al.. (2022). Power spectrum and critical exponents in the 2D stochastic Wilson–Cowan model. Scientific Reports. 12(1). 21870–21870. 11 indexed citations
4.
Sarracino, Alessandro, et al.. (2022). On the scaling of avalanche shape and activity power spectrum in neuronal networks. arXiv (Cornell University). 13 indexed citations
5.
Arcangelis, L. de, et al.. (2021). Role of anaxonic local neurons in the crossover to continuously varying exponents for avalanche activity. Physical review. E. 103(4). 42402–42402. 2 indexed citations
6.
Sarracino, Alessandro, et al.. (2020). Predicting brain evoked response to external stimuli from temporal correlations of spontaneous activity. Physical Review Research. 2(3). 17 indexed citations
7.
Luković, Mirko, et al.. (2018). Critical neural networks with short- and long-term plasticity. Physical review. E. 97(3). 32312–32312. 17 indexed citations
8.
Lombardi, Fabrizio, Hans J. Herrmann, Dietmar Plenz, & L. de Arcangelis. (2016). Temporal correlations in neuronal avalanche occurrence. Scientific Reports. 6(1). 24690–24690. 33 indexed citations
9.
Russo, Raúl E., Hans J. Herrmann, & L. de Arcangelis. (2014). Brain modularity controls the critical behavior of spontaneous activity. Scientific Reports. 4(1). 4312–4312. 23 indexed citations
10.
Arcangelis, L. de, et al.. (2010). Time-energy correlations in solar flare occurrence. Springer Link (Chiba Institute of Technology). 12 indexed citations
11.
Arcangelis, L. de, et al.. (2009). THE GENERALIZED OMORI LAW: MAGNITUDE INCOMPLETENESS OR MAGNITUDE CLUSTERING. International Journal of Modern Physics B. 23(28n29). 5597–5608. 2 indexed citations
12.
Lippiello, Eugenio, L. de Arcangelis, & C. Godano. (2009). Role of Static Stress Diffusion in the Spatiotemporal Organization of Aftershocks. Physical Review Letters. 103(3). 38501–38501. 46 indexed citations
13.
Lippiello, Eugenio, C. Godano, & L. de Arcangelis. (2007). Dynamical Scaling in Branching Models for Seismicity. Physical Review Letters. 98(9). 98501–98501. 65 indexed citations
14.
Arcangelis, L. de, Carla Perrone‐Capano, & Hans J. Herrmann. (2006). Self-Organized Criticality Model for Brain Plasticity. Physical Review Letters. 96(2). 28107–28107. 181 indexed citations
15.
Arcangelis, L. de, et al.. (1996). Hydrodynamic interactions in deep bed filtration. Physics of Fluids. 8(1). 6–14. 34 indexed citations
16.
Hunter, Dan, et al.. (1993). Time-dependent critical properties of Ising models by damage spreading. Physica A Statistical Mechanics and its Applications. 196(2). 188–208. 8 indexed citations
17.
Hansen, Alex, Einar L. Hinrichsen, S Roux, Hans J. Herrmann, & L. de Arcangelis. (1990). Deterministic Growth of Diffusion-Limited Aggregation with Quenched Disorder. Europhysics Letters (EPL). 13(4). 341–347. 12 indexed citations
18.
Amitrano, C., L. de Arcangelis, Antonio Coniglio, & János Kertész. (1988). Regular versus irregular Laplacian growth: multifractal spectroscopy. Journal of Physics A Mathematical and General. 21(1). L15–L21. 1 indexed citations
19.
Arcangelis, L. de, Antonio Coniglio, & Giovanni Paladin. (1988). Comment on "Information Dimension in Random-Walk Processes". Physical Review Letters. 61(18). 2156–2156. 3 indexed citations
20.
Arcangelis, L. de & Naeem Jan. (1986). The dynamic critical exponent of the q=3 and 4 state Potts model. Journal of Physics A Mathematical and General. 19(18). L1179–L1183. 13 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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