Effect of Physically Realistic Potential Energy Form on Spatial Pattern Complexity in a Collective Motion Model

Austin M. Marcus and Hiroki Sayama

Complexity Volume 2023 | Article ID 8852349

Collective motion models most often use self-propelled particles, which are known to produce organized spatial patterns via their collective interactions. However, there is less work considering the possible organized spatial patterns achievable by non-self-propelled particles (nondriven), i.e., those obeying energy and momentum conservation. Moreover, it is not known how the potential energy interaction between the particles affects the complexity of the patterns. To address this, in this paper, a collective motion model with a pairwise potential energy function that conserved the total energy and momentum of the particles was implemented. The potential energy function was derived by generalizing the Lennard–Jones potential to reduce to gravity-like and billiard-ball-like potentials at the extremes of its parameter range. The particle model was simulated under a number of parameterizations of this generalized potential, and the average complexity of the spatial pattern produced by each was computed. Complexity was measured by tracking the information needed to describe the particle system at different scales (the complexity profile). It was found that the spatial patterns of the particles were the most complex around a specific ratio in the parameters. This parameter ratio described a characteristic shape of the potential energy function that is capable of producing complex spatial patterns. It is suggested that the characteristic shape of the potential energy produces complex behavior by balancing the likelihood for particles to bond. Furthermore, these results demonstrate that complex spatial patterns are possible even in an isolated system.

Read the full article at: www.hindawi.com

Sleeping Beauties | Book by Andreas Wagner

Why do some of nature’s marvels have to wait millions of years for their time in the sun?

Life innovates constantly, producing perfectly adapted species – but there’s a catch.

Many animals and plants eke out seemingly unremarkable lives. Passive, constrained, modest, threatened. Then, in a blink of evolutionary time, they flourish spectacularly. Once we start to look, these ‘sleeping beauties’ crop up everywhere. But why?

Looking at the book of life, from apex predators to keystone crops, and informed by his own cutting-edge experiments, renowned scientist Andreas Wagner demonstrates that innovations can come frequently and cheaply to nature, well before they are needed. We have found prehistoric bacteria that harbour the remarkable ability to fight off 21st-century antibiotics. And human history fits the pattern too, as life-changing technologies are invented only to be forgotten, languishing in the shadows before they finally take off.

In probing the mysteries of these sleeping beauties, Wagner reveals a crucial part of nature’s rich and strange tapestry.

Read the full article at: www.simonandschuster.com

The role of complexity for digital twins of cities

G. Caldarelli, E. Arcaute, M. Barthelemy, M. Batty, C. Gershenson, D. Helbing, S. Mancuso, Y. Moreno, J. J. Ramasco, C. Rozenblat, A. Sánchez & J. L. Fernández-Villacañas 
Nature Computational Science (2023)

We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

Read the full article at: https://rdcu.be/da7wK 

Competitive exclusion principle among synthetic non-biochemical protocells

Sai Krishna Katla, Chenyu Lin, Juan Pérez-Mercader

Cell Reports Physical Science VOLUME 4, ISSUE 4, 101359, APRIL 19, 2023

• One-pot synthesis of simple non-biochemical, but functional, protocell populations
• Two populations emerge, differing only in that one has an advantage for reproduction
• The populations compete for food in a shared environment, with one dying out
• Simple protocells display Darwin’s “struggle for existence” without biochemistry

Read the full article at: www.cell.com

Lyapunov exponents for temporal networks

Annalisa Caligiuri, Victor M. Eguíluz, Leonardo Di Gaetano, Tobias Galla, and Lucas Lacasa

Phys. Rev. E 107, 044305

By interpreting a temporal network as a trajectory of a latent graph dynamical system, we introduce the concept of dynamical instability of a temporal network and construct a measure to estimate the network maximum Lyapunov exponent (nMLE) of a temporal network trajectory. Extending conventional algorithmic methods from nonlinear time-series analysis to networks, we show how to quantify sensitive dependence on initial conditions and estimate the nMLE directly from a single network trajectory. We validate our method for a range of synthetic generative network models displaying low- and high-dimensional chaos and finally discuss potential applications.

Read the full article at: link.aps.org