Evidence map›Paper›PMID 41333184›Full record

ArticleFrontiers in network physiology2025

Metastability in the mixing/demixing of two species with reciprocally concentration-dependent diffusivity.

Alexander B Neiman, Xiaochen Dong, Benjamin Lindner

Abstract read
In one paragraph

Article in Frontiers in network physiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Alexander B NeimanDepartment of Physics and Astronomy, Ohio University, Athens, OH, United States.
Xiaochen DongBernstein Center for Computational Neuroscience Berlin, Berlin, Germany.
Benjamin LindnerBernstein Center for Computational Neuroscience Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It has been shown before that two species of diffusing particles can separate from each other by the mechanism of reciprocally concentration-dependent diffusivity: the presence of one species amplifies the diffusion coefficient of the respective other one, causing the two densities of particles to separate spontaneously. In a minimal model, this could be observed with a quadratic dependence of the diffusion coefficient on the density of the other species. Here, we consider a more realistic sigmoidal dependence as a logistic function on the other particle's density averaged over a finite sensing radius. The sigmoidal dependence accounts for the saturation effects of the diffusion coefficients, which cannot grow without bounds. We show that sigmoidal (logistic) cross-diffusion leads to a new regime in which a homogeneous disordered (well-mixed) state and a spontaneously separated ordered (demixed) state coexist, forming two long-lived metastable configurations. In systems with a finite number of particles, random fluctuations induce repeated transitions between these two states. By tracking an order parameter that distinguishes mixed from demixed phases, we measure the corresponding mean residence in each state and demonstrate that one lifetime increases and the other decreases as the logistic coupling parameter is varied. The system thus displays typical features of a first-order phase transition, including hysteresis for large particle numbers. In addition, we compute the correlation time of the order parameter and show that it exhibits a pronounced maximum within the bistable parameter range, growing exponentially with the total particle number.

Indexed as

active matterbistabilityBrownian particlesnetwork physiologynoise-induced switchingpattern formationself-organization

Identifiers

PMID41333184
PMCPMC12665743

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.