SOURCE-LINKED INTELLIGENCE
TRACE: Spatiotemporal Contact Memory Graph Network Simulator for Granular Dynamics
Learned graph simulators provide an efficient alternative to high-fidelity solvers for granular dynamics. However, granular motion depends strongly on inter-granular contact history, which is difficult to preserve when particle contacts form, break, and rearrange. Existing simulators mainly store temporal information in node features or node-level memory. Here we introduce TRACE, a graph-network simulator that stores interaction history directly on contact edges. Each edge maintains a persistent memory updated by attention-based message passing and a gated recurrent unit, while an edge-identit
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T15:30:41.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.