An encoder-decoder neural network trained on boundary element method data designs and compares layered cloaks for 2D Helmholtz scattering, showing object-fitted layers reduce scattering more than circular ones for circular, star, and kite objects.
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3 Pith papers cite this work, alongside 17 external citations. Polarity classification is still indexing.
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A PINN constrained by the two-component multiplicity model learns the hard-scattering fraction from Zr+Zr events and predicts N_ch more accurately than a data-driven NN on unseen Ru+Ru and Au+Au collisions.