A new Dirac-Frenkel-Onsager dynamics injects gauge momentum to achieve unbiased, temporally smooth parameter evolution for nonlinear PDE approximations.
Nathan Kutz
2 Pith papers cite this work. Polarity classification is still indexing.
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Reformulating DRL in a moving reference frame enables reliable control of rapid transitions between mode-locked states in a 1D RDE model by separating fast detonation propagation from slower operating-mode dynamics.
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A Dirac-Frenkel-Onsager principle: Instantaneous residual minimization with gauge momentum for nonlinear parametrizations of PDE solutions
A new Dirac-Frenkel-Onsager dynamics injects gauge momentum to achieve unbiased, temporally smooth parameter evolution for nonlinear PDE approximations.
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Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions
Reformulating DRL in a moving reference frame enables reliable control of rapid transitions between mode-locked states in a 1D RDE model by separating fast detonation propagation from slower operating-mode dynamics.