https://hdl.handle.net/10481/38759 2026-04-03T18:26:27Z 2026-04-03T18:26:27Z de Haro García, Alejandro Torres Agudo, Joaquín https://hdl.handle.net/10481/111066 2026-02-17T09:37:43Z

Emergence of Chimeras States in One-dimensional Ising Model with Long-Range Diffusion de Haro García, Alejandro; Torres Agudo, Joaquín In this work, we examine the conditions for the emergence of chimera-like states in Ising systems. We study an Ising chain with periodic boundaries in contact with a thermal bath at temperature T, that induces stochastic changes in spin variables. To capture the non-locality needed for chimera formation, we introduce a model setup with non-local diffusion of spin values through the whole system. More precisely, diffusion is modeled through spin-exchange interactions between units up to a distance R, using Kawasaki dynamics. This setup mimics, e.g., neural media, as the brain, in the presence of electrical (diffusive) interactions. We explored the influence of such non-local dynamics on the emergence of complex spatiotemporal synchronization patterns of activity. Depending on system parameters we report here for the first time chimera-like states in the Ising model, characterized by relatively stable moving domains of spins with different local magnetization. We analyzed the system at T=0, both analytically and via simulations and computed the system's phase diagram, revealing rich behavior: regions with only chimeras, coexistence of chimeras and stable domains, and metastable chimeras that decay into uniform stable domains. This study offers fundamental insights into how coherent and incoherent synchronization patterns can arise in complex networked systems as it is, e.g., the brain.

Millán Vidal, Ana Paula Hanlin, Sun Torres Agudo, Joaquín https://hdl.handle.net/10481/107952 2025-11-12T13:20:25Z

Spatio-temporal activity patterns induced by triadic interactions in an in silico neural medium Millán Vidal, Ana Paula; Hanlin, Sun; Torres Agudo, Joaquín

Hurtado Gutiérrez, Rubén Hurtado Fernández, Pablo Ignacio Pérez Espigares, Carlos https://hdl.handle.net/10481/85666 2023-11-14T13:06:47Z

Spectral signatures of symmetry-breaking dynamical phase transitions Hurtado Gutiérrez, Rubén; Hurtado Fernández, Pablo Ignacio; Pérez Espigares, Carlos The research leading to these results has re- ceived funding from the fellowship FPU17/02191 and from the Projects of I+D+i Ref. PID2020- 113681GB-I00, Ref. PID2021-128970OA-I00 and Ref. FIS2017-84256-P, Ref. A-FQM-175-UGR18, Ref. P20_00173 and Ref. A-FQM-644-UGR20 fi- nanced by the Spanish Ministerio de Ciencia, In- novación y Universidades and European Regional Development Fund, Junta de Andalucía-Consejería de Economía y Conocimiento 2014-2020. We are also grateful for the the computing resources and related technical support provided by PROTEUS, the supercomputing center of Institute Carlos I in Granada, Spain.

Santos Fernández, Francisco de los Romera Gutiérrez, Elvira https://hdl.handle.net/10481/84429 2023-09-14T10:51:23Z

Quantum recurrence times in nanostructures Santos Fernández, Francisco de los; Romera Gutiérrez, Elvira We compute the classical and revival times of electron currents in several bulk nanostructured, semiconductor materials. We have used a nonparabolic Schrödinger equation to model the conduction band of semiconductors. We have calculated the classical and revival periods for quantum dots of Si, Ge and InAs quantum dots. The obtained results are of the order of tenths of nanoseconds to picoseconds, which are within reach of current technologies.

Muñoz Martínez, Miguel Ángel Villegas, Pablo Bonachela, Pablo https://hdl.handle.net/10481/70633 2021-10-04T12:32:27Z

Evolution in the Debian GNU/Linux software network: analogies and differences with gene regulatory networks Muñoz Martínez, Miguel Ángel; Villegas, Pablo; Bonachela, Pablo Biological networks exhibit intricate architectures deemed to be crucial for their functionality. In particular, gene regulatory networks, which play a key role in information processing in the cell, display non-trivial architectural features such as scale-free degree distributions, high modularity and low average distance between connected genes. Such networks result from complex evolutionary and adaptive processes difficult to track down empirically. On the other hand, there exists detailed information on the developmental (or evolutionary) stages of open-software networks that result from self-organized growth across versions. Here, we study the evolution of the Debian GNU/Linux software network, focusing on the changes of key structural and statistical features over time. Our results show that evolution has led to a network structure in which the out-degree distribution is scale-free and the in-degree distribution is a stretched exponential. In addition, while modularity, directionality of information flow, and average distance between elements grew, vulnerability decreased over time. These features resemble closely those currently shown by gene regulatory networks, suggesting the existence of common adaptive pathways for the architectural design of information-processing networks. Differences in other hierarchical aspects point to system-specific solutions to similar evolutionary challenges.