Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Ruiz-Garcia, Miguel"'
Autor:
Martinez-Calvo, Alejandro, Biviano, Matthew D, Christensen, Anneline, Katifori, Eleni, Jensen, Kaare H., Ruiz-Garcia, Miguel
Fluid flow networks are ubiquitous and can be found in a broad range of contexts, from human-made systems such as water supply networks to living systems like animal and plant vasculature. In many cases, the elements forming these networks exhibit a
Externí odkaz:
http://arxiv.org/abs/2303.10777
Autor:
Ruíz-García, Miguel, Ozaita, Juan, Pereda, María, Alfonso, Antonio, Brañas-Garza, Pablo, Cuesta, Jose A., Sánchez, Ángel
Publikováno v:
Proceedings of the National Academy of Sciences (USA), 120, e2215041120 (2023)
Networks of social interactions are the substrate upon which civilizations are built. Often, we create new bonds with people that we like or feel that our relationships are damaged through the intervention of third parties. Despite their importance a
Externí odkaz:
http://arxiv.org/abs/2209.03683
Autor:
Ruiz-Garcia, Miguel, Gutierrez, C. Miguel Barriuso, Alexander, Lachlan C., Aarts, Dirk G. A. L., Ghiringhelli, Luca, Valeriani, Chantal
Active matter spans a wide range of time and length scales, from groups of cells and synthetic self-propelled particles to schools of fish, flocks of birds, or even human crowds. The theoretical framework describing these systems has shown tremendous
Externí odkaz:
http://arxiv.org/abs/2203.14846
Autor:
Ruiz-Garcia, Miguel
The work of McCloskey and Cohen popularized the concept of catastrophic interference. They used a neural network that tried to learn addition using two groups of examples as two different tasks. In their case, learning the second task rapidly deterio
Externí odkaz:
http://arxiv.org/abs/2108.03940
We show that learning can be improved by using loss functions that evolve cyclically during training to emphasize one class at a time. In underparameterized networks, such dynamical loss functions can lead to successful training for networks that fai
Externí odkaz:
http://arxiv.org/abs/2102.03793
Publikováno v:
J. Mech. Phys. Solids. 149, 104296 (2021)
Steady progress in the miniaturization of structures and devices has reached a scale where thermal fluctuations become relevant and it is thus important to understand how such fluctuations affect their mechanical stability. Here, we investigate the b
Externí odkaz:
http://arxiv.org/abs/2005.05949
Autor:
Ruiz-Garcia, Miguel, Katifori, Eleni
Publikováno v:
Phys. Rev. E 103, 062301 (2021)
Flow networks can describe many natural and artificial systems. We present a model for a flow system that allows for volume accumulation, includes conduits with a non-linear relation between current and pressure difference, and can be applied to netw
Externí odkaz:
http://arxiv.org/abs/2003.10003
Autor:
Ruiz-Garcia, Miguel, Katifori, Eleni
Flow networks are essential for both living organisms and enginneered systems. These networks often present complex dynamics controlled, at least in part, by their topology. Previous works have shown that topologically complex networks interconnectin
Externí odkaz:
http://arxiv.org/abs/2001.01811
We analyze the spontaneous rippling of graphene membranes as function of the coupling between lattice deformations and electrons. We numerically study a model of an elastic membrane coupled to Dirac fermions. We identify a phase transition from a fla
Externí odkaz:
http://arxiv.org/abs/1911.10536
Publikováno v:
Phys. Rev. B 101, 235428 (2020)
Suspended graphene exhibits ripples of size ranging from 50 to 100 {\AA} and height $\sim$10{\AA}, however, their origin remains undetermined. Previous theoretical works have proposed that rippling in graphene might be generated by the coupling betwe
Externí odkaz:
http://arxiv.org/abs/1911.10510