Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential ...

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My childhood fascination with the night sky led me to study astronomy and physics at university. By my second year, I was operating the telescope atop the physics building, tracking celestial objects ...

We’re suckers for good-looking old-school calculators, so this interesting numerical equation-solving calculator by [Peter Balch] caught our attention. Based around the ESP32-WROOM-32 module and an ...

Euler Method: The simplest numerical method for solving ODEs, which uses the derivative to project forward. [ y_{n+1} = y_n + h \cdot f(x_n, y_n) ] Heun's Method (Improved Euler Method): A two-step ...

Porous media play a critical role in various industrial fields due to their complex pore networks and considerable specific surface areas. The transport and reaction phenomena within porous media are ...

Abstract: Fourier neural operator (FNO) is a recently proposed data-driven scheme to approximate the implicit operators characterized by partial differential equations (PDEs) between functional spaces ...