Vera-Ávila V P, Rivera-Durón R R, Orozco-López Onofre, Soriano-García M S, Sevilla-Escoboza J Ricardo, Buldú Javier M
Unidad Profesional Interdisciplinaria de Ingeniería Campus Guanajuato, Instituto Politécnico Nacional, Guanajuato, 36275, México.
Universidad Virtual del Estado de Guanajuato, C. Hermenegildo Bustos 129, Zona Centro, 36400 Purísima de Bustos, Gto.
Data Brief. 2024 Nov 16;57:111145. doi: 10.1016/j.dib.2024.111145. eCollection 2024 Dec.
Some real-world phenomena and human-made problems have been modeled as networks where the objects form pairwise interactions. However, this is a limited approach when the existence of high-order interactions is inherent in a system, such as the brain, social networks and ecosystems. The way in which these high-order interactions affect the collective behavior of a complex system is still an open question. For this reason, it is necessary to analyze theoretically, numerically and experimentally the consequences of higher-order interactions in complex systems. Here, we provide experimental datasets of the dynamics of three nonlinear electronic oscillators, namely, Rössler oscillators, interacting into a simplicial complex whose connections rely on both linear (diffusive) and nonlinear (high-order) coupling. It is well-known that Rössler systems only achieve the synchronization when they are coupled by means of or variable. Considering this fact, we designed our experiment considering four scenarios. The first one, when both linear and nonlinear coupling functions are introduced through the variable. The second one, occurring when linear coupling is introduced through the variable and the nonlinear coupling through the variable. The third case happens when the linear coupling is introduced through the variable whereas nonlinear coupling goes through the variable. The last case, when both linear and nonlinear coupling are introduced through the variable. For each scenario, we acquired 10000 times series when both the linear and nonlinear coupling strengths were modified. Each time series contained 30000 temporal points. These datasets are useful to corroborate the conditions to reach the synchronized state varying the linear/non-linear coupling strengths and to test new metrics for better understanding the effects of higher-order interactions in complex networks.
一些现实世界的现象和人为问题已被建模为网络，其中对象形成成对相互作用。然而，当高阶相互作用的存在是系统（如大脑、社交网络和生态系统）所固有的时，这种方法是有限的。这些高阶相互作用影响复杂系统集体行为的方式仍然是一个悬而未决的问题。因此，有必要从理论、数值和实验上分析复杂系统中高阶相互作用的后果。在这里，我们提供了三个非线性电子振荡器（即罗斯勒振荡器）动力学的实验数据集，它们相互作用形成一个单纯复形，其连接依赖于线性（扩散）和非线性（高阶）耦合。众所周知，罗斯勒系统只有通过 或 变量耦合时才会实现同步。考虑到这一事实，我们设计了包含四种情况的实验。第一种情况是，线性和非线性耦合函数都通过 变量引入。第二种情况是，线性耦合通过 变量引入，非线性耦合通过 变量引入。第三种情况是，线性耦合通过 变量引入，而非线性耦合通过 变量引入。最后一种情况是，线性和非线性耦合都通过 变量引入。对于每种情况，当线性和非线性耦合强度都被修改时，我们获取了10000个时间序列。每个时间序列包含30000个时间点。这些数据集有助于证实通过改变线性/非线性耦合强度达到同步状态的条件，并测试新的指标，以便更好地理解复杂网络中高阶相互作用的影响。
