Abstract: A novel meshless electromagnetic (EM) simulation framework based on Physics-Informed Neural Networks (PINNs), enhanced by the integration of Kolmogorov–Arnold Networks (KANs) is presented.
Crystals, bacterial colonies, flame fronts: the growth of surfaces was first described in the 1980s by the ...
Python-derived pTOS shows promise as a side-effect-free appetite suppressant, offering a new path for weight loss and metabolic therapies.
Morning Overview on MSN
Physics-trained AI models speed engineering design and simulations
When engineers at Sumitomo Riko needed to speed up the design cycle for automotive rubber and polymer components, they turned ...
When trying out the feature for myself, I asked Gemini to make a simulation of the Moon orbiting the Earth, and it created a ...
With their ability to shapeshift and manipulate delicate objects, soft robots could work as medical implants, deliver drugs ...
As climate change intensifies harmful algal blooms worldwide, an international team led by Hiroshima University has developed ...
New research from UBC Okanagan mathematically demonstrates that the universe cannot be simulated. Using Gödel’s incompleteness theorem, scientists found that reality requires “non-algorithmic ...
Abstract: The increasing demand for high-speed optical interconnects requires the integration of photonics and electronics, with electro-optic (EO) co-simulation being crucial. However, fragmented ...
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