Using methods from the field of topological data analysis, we investigate the self-assembly and emergence of three-dimensional quasi-crystalline structures in a single-component colloidal system. Combining molecular dynamics and persistent homology, we analyse the time evolution of persistence diagrams and particular local structural motifs. Our analysis reveals the formation and dissipation of specific particle constellations in these trajectories, and shows that the persistence diagrams are sensitive to nucleation and convergence to a final structure. Identification of local motifs allows quantification of the similarities between the final structures in a topological sense. This analysis reveals a continuous variation with density between crystalline clathrate, quasi-crystalline, and disordered phases quantified by 'topological proximity', a visualization of the Wasserstein distances between persistence diagrams. From a topological perspective, there is a subtle, but direct connection between quasi-crystalline, crystalline and disordered states. Our results demonstrate that topological data analysis provides detailed insights into molecular self-assembly.
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http://dx.doi.org/10.1098/rspa.2020.0170 | DOI Listing |
JMIR Res Protoc
January 2025
Department of Women's and Children's Health, Participatory eHealth and Health Data Research Group, Uppsala University, Uppsala, Sweden.
Background: Digital health interventions have become increasingly popular in recent years, expanding the possibilities for treatment for various patient groups. In clinical research, while the design of the intervention receives close attention, challenges with research participant engagement and retention persist. This may be partially due to the use of digital health platforms, which may lack adequacy for participants.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Physics, University of Arizona, Tucson, AZ 85721, USA.
J Appl Comput Topol
June 2023
IST Austria (Institute of Science and Technology Austria), Klosterneuburg, Austria.
We characterize critical points of 1-dimensional maps paired in persistent homology geometrically and this way get elementary proofs of theorems about the symmetry of persistence diagrams and the variation of such maps. In particular, we identify branching points and endpoints of networks as the sole source of asymmetry and relate the cycle basis in persistent homology with a version of the stable marriage problem. Our analysis provides the foundations of fast algorithms for maintaining a collection of sorted lists together with its persistence diagram.
View Article and Find Full Text PDFJ Chem Theory Comput
December 2024
Department of Materials Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan.
Coarse-grained molecular dynamics (CG-MD) simulations and subsequent persistent homology (PH) analysis were performed to correlate the structure and stress-strain behavior of polymer films. During uniaxial tensile MD simulations, the first principal component of the persistence diagram obtained by principal component analysis (PCA) was in good agreement with the stress-strain curve. This indicates that PH + PCA can identify critical ring structures relevant to the dynamic changes in MD simulations without requiring any prior knowledge.
View Article and Find Full Text PDFEntropy (Basel)
October 2024
Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 7610001, Israel.
The concept of emergence, or synergy in its simplest form, is widely used but lacks a rigorous definition. Our work connects information and set theory to uncover the mathematical nature of synergy as the failure of distributivity. For the trivial case of discrete random variables, we explore whether and how it is possible to get more information out of lesser parts.
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