GitHub

StatsPAI: a Python-native Stata/R replacement for applied causal inference

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 ...
PNAS

Designing unique mechanical modes through an extension of the quantum hopping method

We introduce an extension of the hopping method, typically used in quantum systems, to mechanical networks for constructing dynamical matrices. This innovative and efficient approach facilitates the ...
GitHub

HTS Coils — REBCO Optimization Framework for Fusion & Antimatter Applications

Comprehensive computational framework for REBCO HTS coils and plasma physics applications. Features validated 7.07T superconducting magnet designs, Lentz soliton simulation with interferometric ...
IEEE

Tropospheric radio wave propagation modeling in Python 3 using PyWaveProp

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 ...
Frontiers

A hybrid finite volume method and smoothed particle hydrodynamics approach for efficient and accurate blast simulations

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 ...
Frontiers

A Review of Stochastic Programming Methods for Optimization of Process Systems Under Uncertainty

Uncertainties are widespread in the optimization of process systems, such as uncertainties in process technologies, prices, and customer demands. In this paper, we review the basic concepts and recent ...