READ ME File For Dataset in support of the article "Multiscale geometrical and topological learning in the analysis of soft matter collective dynamics"
Dataset DOI  10.5258/SOTON/D3769

ReadMe Author: Malgosia Kaczmarek, University of Southampton

This dataset supports the publication:
Tetiana Orlova, Malgosia Kaczmarek, Amaranta Membrillo Solis, Tristan Madeleine, Giampaolo D’Alessandro, Jacek Brodzki, Multiscale geometrical and topological learning in the analysis of soft matter collective dynamics, Physical Review Materials journal
This dataset contains:
Experimental data contains polarizing micrographs are taken after 1.5 min, 3 min and 36.9 s under an applied electric field.
The computed image distance matrices for corresponding videos, where frame numbers were converted to seconds of real-time experimental videos
Eigenvalues of the principal components and trajectories in the spaces of the first two and first three principal components for the moving ensembles of: shape-persistent soft quasi-particles, quasi-particles experiencing shape transformation, clustering quasi-particles.
Time evolution of averaged quasiparticle and corresponding power spectra derived from FFT analysis. 
Time evolution of topological Ψ function computed for the case of moving pseudo-crystallite with shape-persistent localized structures, close-packed dynamic localized structures with shape transformation, dynamic clusters of localized structures. Corresponding power spectra derived from FFT analysis of the Ψ functions. 

Licence: CC-BY

Period of data collection: February 2022 – August 2025

Information about geographic location of data collection: University of Southampton, U.K and University of Boulder, USA. 


Date that the file was created: 13 June 2024