A Russian mathematician has developed a new method for analyzing a class of equations that underpin models in physics and ...

Abstract: Fourier neural operator (FNO) is a recently proposed data-driven scheme to approximate the implicit operators characterized by partial differential equations (PDEs) between functional spaces ...

This repository contains code for the paper: "Enabling Local Neural Operators to perform Equation-Free System-Level Analysis" G. Fabiani, H. Vandecasteele, S. Goswami, C. Siettos, I.G. Kevrekidis ...

Exploration of the Lorenz system using data-driven and physics-informed methods, including FFT, DMD, EDMD, Takens embedding, Deep Koopman learning, and PINNs. Jupyter notebooks demonstrate modeling, ...

Abstract: The analysis of limit cycle oscillations (LCOs) and flutter behavior in hypersonic aeroelastic systems presents significant challenges owing to their strong nonlinearities. This study ...

Somer G. Anderson is CPA, doctor of accounting, and an accounting and finance professor who has been working in the accounting and finance industries for more than 20 years. Her expertise covers a ...

A differential equation is an equality constraining a mathematical function in relation to its derivatives over one or multiple variables. Such equations may constitute the mathematical model for a ...

Lea Uradu, J.D., is a Maryland state registered tax preparer, state-certified notary public, certified VITA tax preparer, IRS annual filing season program participant, and tax writer. Vikki Velasquez ...

1Institute for Basic Research, Eurasian National University, Astana, Kazakhstan 2Department of Theoretical and Nuclear Physics, Al-Farabi Kazakh National University, Almaty, Kazakhstan. One can give ...