Biological neural networks solve cognitive tasks with varying levels of complexity. However, it remains unclear how specific structural and functional features of these networks are related to increasing difficulty of the problems to be solved. How do network motifs change when the cognitive cost is increased? We address this question by evolving Artificial Neural Networks (ANNs) under the...
We study two variants of the Blume-Emery-Grifith model with long range mean-field-like interaction and random disorder, described by different Hamiltonians. In one variant the system is uniformly populated by $N$ spins and the disorder is represented by $\textit{i.i.d}$ random variables chosen with probability $p$. In the other one, we consider $N_s\sim Bin(N,p)$ $\textit{strong}$ spins, i.e.,...
Vertex models have been widely used to study mechanical phase transitions in confluent tissues. In the classical formulation, the normalized cell perimeter, or shape index, serves as a key geometric control parameter: increasing the shape index drives a transition from solid-like to fluid-like tissue behavior as cells become more elongated. Here, we extend the passive energy of the vertex...
We investigate the escape properties of a Feller diffusion process confined to a finite interval within an exactly solvable framework. The dynamics correspond to a particle in a shifted harmonic potential with state-dependent diffusivity, which lifts the symmetry of the escape events. By assigning the boundaries as extinction (near-zero, fluctuation-suppressed) and outbreak (enhanced-noise)...
The self-organization of recently discovered nematic phases is a central problem in contemporary soft-matter research [1, 2, 3, 4]. Several of these phases exhibit local or long-range ferroelectric order, in some cases accompanied by emergent structural chirality despite the chemical achirality of their constituent molecules. Prominent examples are the uniform ferroelectric nematic phase NF...
Turing patterns are an example of thermodynamical systems out of equilibrium, exhibiting symmetry breaking and self-organization. Turing in 1952 showed theoretically that in reaction-diffusion under certain conditions a spatially homogeneous stable system can be destabilized by diffusion. Then, a large-scale spatially periodic static pattern emerges. In 1990, Cassettes et al., made the first...
We investigate a Brownian information engine driven by space-dependent diffusivity. The working protocol is described by overdamped Langevin dynamics within a harmonic confinement and is controlled via resetting. The geometry of the space-dependent diffusivity has a significant impact on the information processing. If the fluctuation increases, while moving away from the potential's center...
Thermodynamic uncertainty relations (TURs) bound the precision of thermodynamic currents in autonomous nonequilibrium steady states and constrain the trade-off between power, efficiency, and constancy in heat engines. We study a minimal autonomous heat engine composed of a discrete ratchet that performs work against a constant bias and an underdamped harmonic oscillator acting as an internal...
From a broader perspective, our objective is to investigate the kinetic and thermodynamic features associated with chemical computation, an emerging and highly significant area of current research. The central motivation is to examine whether chemical computational schemes can offer benefits compared to conventional computing approaches. Our study focuses on systematically exploring different...
Odd systems, characterised by broken time-reversal or parity symmetry, exhibit striking transport phenomena due to transverse responses. In this talk, I will introduce the concept of odd diffusion, a generalisation of diffusion in two-dimensional systems that incorporates antisymmetric tensor components. Focusing on systems of interacting particles, I present analytical results on effective...
