StatsPAI is for empirical researchers who would normally jump between Stata, R, and Python. Its goal is to make common Stata/R econometrics and causal-inference workflows feel native in Python: load a ...

Abstract: This paper presents PyWaveProp, a library for wave propagation modeling, and highlights its application features in tropospheric radio wave propagation. The one-way Helmholtz equation method ...

Modeling strong shock waves in fluids remains a persistent challenge in computational physics. Essential to research efforts in industry and defense, numerous methods have been devised to improve the ...

Physical scientists and engineering research and development (R&D) teams are embracing neural networks in attempts to accelerate their simulations. From quantum mechanics to the prediction of blood ...

The paper presents modeling of bridge elastomeric bearings using large deformation theory and hyperelastic constitutive relations. In this work, the simplest neo-Hookean model was compared with the ...

In undergraduate physical chemistry, Schrödinger’s equation is solved for a variety of cases. In doing so, the energies and wave functions of the system can be interpreted to provide connections with ...

Computational modeling of tissue-scale cardiac electrophysiology requires numerically converged solutions to avoid spurious artifacts. The steep gradients inherent to cardiac action potential ...

Electron energy-loss spectroscopy (EELS) is a unique tool that is extensively used to investigate the plasmonic response of metallic nanostructures. We present here a novel approach for EELS ...