Current understanding of collective behaviour in nature is based largely on models that
assume that identical agents obey the same interaction rules, but in reality interactions may …

Mobile microrobots are envisioned to be useful in a wide range of high-impact applications,
many of which require cohesive group formation to maintain self-bounded swarms in the …

In this paper we consider the clustering coefficient, and clustering function in a random
graph model proposed by Krioukov et al. in 2010. In this model, nodes are chosen randomly …

We review the agent-based models (ABM) on social physics including econophysics. The
ABM consists of agent, system space, and external environment. The agent is autonomous …

Behavioral neuroscience underwent a technology-driven revolution with the emergence of
machine-vision and machine-learning technologies. These technological advances …

While the collective movements of fish schools evading predators in nature are complex,
they can be fundamentally represented by simplified mathematical models. Here we …

Non-reciprocal interactions are prevalent in various natural systems such as neuronal
networks and predator–prey dynamics, sparking significant interest in recent research. This …

We study the q-state active Potts model (APM) on a two-dimensional lattice in which self-
propelled particles have q internal states corresponding to the q directions of motion. A local …

We study the active 4-state Potts model (APM) on the square lattice in which active particles
have four internal states corresponding to the four directions of motion. A local alignment …

We introduce an eigen microstate approach (EMA) in the quantum system to describe the
quantum phase transition without knowing the order parameter. Phases of a quantum …