activity
20012025
most citedInferring long memory processes in the climate network via ordinal pattern analysis

106 citations · 1.1k across the 43 of their papers we have counts for

collaborators

44 papers

physics.soc-ph2025★ 4 cited

Structural roles and gender disparities in corruption networks

Arthur A. B. Pessa, Alvaro F. Martins, Monica V. Prates +4

Criminal activities are predominantly due to males, with females exhibiting a significantly lower involvement, especially in serious offenses. This pattern extends to organized cri…

q-bio.NC2023★ 5 cited

Parameter and coupling estimation in small groups of Izhikevich neurons

R. P. Aristides, A. J. Pons, H. A. Cerdeira +2

Nowadays, experimental techniques allow scientists to have access to large amounts of data. In order to obtain reliable information from the complex systems which produce these dat…

physics.data-an2022★ 51 cited

20 years of ordinal patterns: Perspectives and challenges

Inmaculada Leyva, Johann Martinez, Cristina Masoller +2

In 2002, in a seminal article, Christoph Bandt and Bernd Pompe proposed a new methodology for the analysis of complex time series, now known as Ordinal Analysis. The ordinal method…

physics.ao-ph2022

Perspectives on the importance of complex systems in understanding ourclimate and climate change -- The Nobel Prize in Physics 2021

Shraddha Gupta, Nikolaos Mastrantonas, Cristina Masoller +1

The Nobel Prize in Physics 2021 was awarded to Syukuro Manabe, Klaus Hasselmann, and Giorgio Parisi for their 'groundbreaking contributions to our understanding of complex systems'…

cs.ET2022★ 9 cited

Image classification using collective optical modes of an array of nanolasers

Giulio Tirabassi, Ji Kaiwen, Cristina Masoller +1

Recent advancements in nanolaser design and manufacturing open up unprecedented perspectives in terms of high integration densities and ultra-low power consumption, making these de…

physics.data-an2021★ 1 cited

Discriminating chaotic and stochastic time series using permutation entropy and artificial neural networks

B. R. R. Boaretto, R. C. Budzinski, K. L. Rossi +3

Extracting relevant properties of empirical signals generated by nonlinear, stochastic, and high-dimensional systems is a challenge of complex systems research. Open questions are…