The project aimed to develop a full stack of technologies to bring the practical advantages of quantum computing to industry in the near term Quantum computing is one of the frontiers of research and ...

Abstract: Physics-Informed Neural Networks (PINNs) have emerged as a robust framework for solving Partial Differential Equations (PDEs) by approximating their solutions via neural networks and ...

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

Linear and quasilinear first order PDE. The method of characteristics. Conservation laws and propagation of shocks. Basic theory for three classical equations of mathematical physics (in all spatial ...

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. To study ...

TWA is one such semiclassical approach that dates back to the 1970s, but is limited to isolated, idealized quantum systems ...