A geometric decomposition of entropy production rate in reaction-diffusion systems isolates excess dissipation driving patterns and yields speed limits, uncertainty relations, and an optimal-transport extension for efficient pattern formation.
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Neptune infers spatiotemporal parameter fields in PDEs from as few as 45 sparse measurements using independent coordinate neural networks, outperforming PINNs and neural operators with lower errors and better extrapolation.
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Geometric thermodynamics of reaction-diffusion systems: Thermodynamic trade-off relations and optimal transport for pattern formation
A geometric decomposition of entropy production rate in reaction-diffusion systems isolates excess dissipation driving patterns and yields speed limits, uncertainty relations, and an optimal-transport extension for efficient pattern formation.
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Estimating Parameter Fields in Multi-Physics PDEs from Scarce Measurements
Neptune infers spatiotemporal parameter fields in PDEs from as few as 45 sparse measurements using independent coordinate neural networks, outperforming PINNs and neural operators with lower errors and better extrapolation.