To fulfill the 2 Core Courses, take two Core Courses from two different Core Areas. CSE Core Courses are classified into six areas: Introduction to CSE, Computational Mathematics, High Performance ...

This set of tutorials are written at an introductory level for an engineering or physical sciences major. It is ideal for someone who has completed college level courses in linear algebra, calculus ...

However, the rise of Python in scientific computing has opened the doors to powerful, open-source tools for power system analysis. This guide provides a step-by-step walk-through on modeling, ...

Julia Sets are mathematical objects relating to the field of complex dynamics. In general, Julia sets are studied in parallel to Fatou sets, as they are complementary sets defined from a complex ...

School of Petroleum Engineering, Yangtze University, Wuhan City 430100, China Hubei Cooperative Innovation Center of Unconventional Oil & Gas, Yangtze University, Wuhan City 430100, China School of ...

Solving Ordinary Differential Equations (ODEs) lies at the core of modeling dynamic systems in engineering. From predicting chemical reactions to simulating mechanical oscillations, numerical ...

Most reaction rate theories start from the assumption of quasi-equilibrium attained in a given reactant before the reaction occurs. However, in complex networks with multiple nodes, it remains unclear ...

Identifying governing equations from observational data is crucial for understanding nonlinear physical systems but remains challenging due to the risk of overfitting. Here we introduce the Bi-Level ...

Generating synthetic locomotory and neural data is a useful yet cumbersome step commonly required to study theoretical models of the brain’s role in spatial navigation. This process can be time ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...