Published September 22, 2026 | Version v1

Arrested coarsening, oscillations, and memory from a conserved phase separating nucleator in a self-straining cytoskeletal network: Videos, Plots and Data

  • 1. ROR icon TU Wien
  • 2. ROR icon Université Paris-Saclay
  • 3. ROR icon École Polytechnique

Description

This Data supplements the paper: Phase separating nucleator in a self-straining filament network:

arXiv:2509.07181

There we describe the interplay of a phase separating nucleator and an active filament network following self-straining dynamics. The model proposed consists of filaments nucleating in droplets, being transported by motors and advecting the droplet fluid. This constitues a mechanical activator-inhibitor mechanism. We show, that this model not only arrests coarsening, but also supports memory encoded in the spatial frequency of droplets and shows chaotic and oscillatory states for certain parameters.

videos.zip

In this files, all the videos corresponding to simulations shown in figure 6 (a) are save, together with parameter files for every simulation and the change rate of the system variables. Destinct parameters are given in the Filename.

 

videos_c_0_3.zip

In this files, all the videos corresponding to simulations shown in figure 6 (b) are save, together with parameter files for every simulation and the change rate of the system variables. Destinct parameters are given in the Filename.

 

chaos_2d_graphs.zip

In this folder one finds the evolution of the L1-norm difference of simulations initialised with slightly different initial conditions for non-steady 2d simulations. Destinct parameters are given in the Filename and correspond to simulations shown in figure 6 (a).

waiting_times_memory.zip

Contains lists of waiting times for different level of noise for different frequencies of 1D simulations - one file per frequency. Noise-levels are found in the paper, together with the other parameters used (see figure 5) 

Files

chaos_2d_graphs.zip

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Additional details

Related works

Cites
Preprint: 10.48550/arXiv.2509.07181 (DOI)

Funding

Vienna Science and Technology Fund
10.47379/VRG20002
ASC (Austrian scientific cluster)