Neuromorphic computers, inspired by the architecture of the human brain, are proving surprisingly adept at solving complex ...

A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers ...

Perovskite solar cells (PSCs) have emerged as promising alternative for next generation photovoltaics due to their superior ...

Perovskite solar cells (PSCs) have emerged as promising alternative for next generation photovoltaics due to their superior power conversion efficiencies (record currently at 34.9% for ...

Perovskite solar cells offer high efficiency & low cost, but complex structures limit modeling. A new Python simulator ...

This is our code for paper "Convolutional-neural-operator-based transfer learning for solving PDEs". This repository is an extension of the original Conditional Neural Operator (CNO) implementation ...

Solving partial differential equations (PDEs) is a required step in the simulation of natural and engineering systems. The associated computational costs significantly increase when exploring various ...

Abstract: Solving partial differential equations (PDEs) is of great importance in numerous fields including physics, engineering, finance, and scientific computing. Physics-Informed Neural Networks ...

Since the launch of the Crossword in 1942, The Times has captivated solvers by providing engaging word and logic games. In 2014, we introduced the Mini Crossword — followed by Spelling Bee, Letter ...