arXiv subjects

Laya Parkavousi

Publications and source records attributed to Laya Parkavousi.

5 recordsLinked to original sources

arXiv2026

Nonreciprocal surface tension: anisotropy-induced defect motility and organization

We show that interfacial nonreciprocity transforms defect dynamics in conserved scalar fields within the framework of the Nonreciprocal Cahn-Hilliard model. Nonreciprocal surface tension alone produces intermittently stable defects: system-spanning target patterns form, lose stability, self-destruct, and nucleate again from a defect-chaotic state. When bulk and interfacial contributions interplay in a particular way, the system forms a distinct mosaic-wave state: traveling waves remain coherent within finite domains demarcated by linear arrangements of motile dislocations, which act as lines of phase slip. Mosaic-waves exhibit scale-free fluctuations at length scales much larger than the average wavelength of the traveling patterns. To explain the wide range of emergent dynamics, we construct the dynamics of the Goldstone-mode. The nonlinearities governing its large-scale fluctuations belong to the anisotropic Kardar-Parisi-Zhang universality class, with the sign of the nonlinear anisotropy controlling the nature of the out-of-equilibrium dynamics.

cond-mat.soft↗

arXiv2026

Compositional disorder in a multicomponent non-reciprocal mixture: stability and patterns

The mean compositions of individual components can be tuned to control phase behavior in number-conserving passive mixtures. In this work, we investigate the role of variable average density in a system of infinitely many non-reciprocally interacting scalar densities, within the framework of the multi-species non-reciprocal Cahn-Hilliard (NRCH) model. Rather than focusing on specific parameter choices, we study ensembles of systems where the inter-species interaction coefficients and average densities are sampled from probability distributions. We show that non-reciprocity stabilizes the homogeneous mixed state even in the presence of compositional disorder. Using random matrix theory, we derive a general condition for the onset of spinodal instability, which we verify through simulations. Finally, we illustrate the connection between the statistics of the most unstable eigenvalue and the emergent nonlinear dynamics.

cond-mat.stat-mech↗

arXiv2024

Enhanced stability and chaotic condensates in multi-species non-reciprocal mixtures

Random non-reciprocal interactions between a large number of conserved densities are shown to enhance the stability of the system towards pattern formation. The enhanced stability is an exact result when the number of species approaches infinity and is confirmed numerically by simulations of the multi-species non-reciprocal Cahn-Hilliard model. Furthermore, the diversity in dynamical patterns increases with increasing number of components and novel steady states such as pulsating or spatiotemporally chaotic condensates are observed. Our results may help to unravel the mechanisms by which living systems self-organise via metabolism.

cond-mat.soft↗

arXiv2023

Voids and Halos in Voids statistics as a probe of the Expansion History of the Universe

Structures in the Universe are arranged into the cosmic web. Distributions, statistics, and evolutions of the structures can be used as probes for cosmological models. We investigate the number density of voids and dark matter halos-in-voids in the Excursion Set Theory (EST). We study the Markov and non-Markov frameworks of EST in both spherical and ellipsoidal collapse models. Afterward, we compare the number density of voids and halos-in-voids in the standard $Λ$CDM and the reconstructed model. The reconstructed model is a model-independent reconstruction based on background observations. This work explores the effects of the collapse model barrier in the different EST frameworks on the statistics of voids and the statistics of halos-in-voids. Finally, we find the hint that cosmological models can be distinguished by the number density of halos-in-voids in the $1.0-2.5$ redshift range. The maximum difference is observed in $z\sim1.9$.

astro-ph.CO↗

arXiv2023

Data-Driven Reconstruction of Stochastic Dynamical Equations based on Statistical Moments

Stochastic processes are encountered in many contexts, ranging from generation sizes of bacterial colonies and service times in a queueing system to displacements of Brownian particles and frequency fluctuations in an electrical power grid. If such processes are Markov, then their probability distribution is governed by the Kramers-Moyal (KM) equation, a partial differential equation that involves an infinite number of coefficients, which depend on the state variable. The KM coefficients must be evaluated based on measured time series for a data-driven reconstruction of the governing equations for the stochastic dynamics. We present an accurate method of computing the KM coefficients, which relies on computing the coefficients' conditional moments based on the statistical moments of the time series. The method's advantages over state-of-the-art approaches are demonstrated by investigating prototypical stochastic processes with well-known properties.

cond-mat.stat-mech↗