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Learning the effective order of a hypergraph dynamical system.
- Source :
-
Science Advances . 5/10/2024, Vol. 10 Issue 19, p1-11. 11p. - Publication Year :
- 2024
-
Abstract
- Dynamical systems on hypergraphs can display a rich set of behaviors not observable for systems with pairwise interactions. Given a distributed dynamical system with a putative hypergraph structure, an interesting question is thus how much of this hypergraph structure is actually necessary to faithfully replicate the observed dynamical behavior. To answer this question, we propose a method to determine the minimum order of a hypergraph necessary to approximate the corresponding dynamics accurately. Specifically, we develop a mathematical framework that allows us to determine this order when the type of dynamics is known. We use these ideas in conjunction with a hypergraph neural network to directly learn the dynamics itself and the resulting order of the hypergraph from both synthetic and real datasets consisting of observed system trajectories. [ABSTRACT FROM AUTHOR]
- Subjects :
- *DYNAMICAL systems
*HAMILTONIAN graph theory
*HYPERGRAPHS
Subjects
Details
- Language :
- English
- ISSN :
- 23752548
- Volume :
- 10
- Issue :
- 19
- Database :
- Academic Search Index
- Journal :
- Science Advances
- Publication Type :
- Academic Journal
- Accession number :
- 177135126
- Full Text :
- https://doi.org/10.1126/sciadv.adh4053