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Using frontier agent harnesses to tackle mathematical research problems has emerged as an effective means of advancing mathematics. However, solving frontier problems in mathematics may require a massive number of agents working in parallel for extended periods to construct proofs, thereby generating an enormous volume...
Partial differential equations (PDEs) govern dynamical systems in hydrodynamics, where classical solvers face well-known difficulties with nonlinearity and computational cost. Lagrangian neural surrogates such as GNS and SEGNN learn directly from particle-based simulations, but local message passing alone is limited in...
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