The numerical solution of partial differential equations (PDEs) is essential in computational physics. Over the past few decades, various quantum-based methods have been developed to formulate and ...

Physics-Informed Neural Networks (PINNs) augment traditional neural architectures by embedding the governing equations of physical systems directly into the loss function. Instead of solely minimising ...

In my last article, I looked at NumPY and some of its uses in numerical simulations. Although NumPY does provide some really robust building blocks, it is a bit lacking in more sophisticated tools.