Complex network has been a popular topic in the past decade and attracted the research interests of multiple disciplines, including computer science, social science, physical science and mathematical ...

Data-driven deep learning (DL) models often underestimate the intensity of extreme weather and climate events due to the scarcity of extreme samples in training datasets and the smoothing effects of ...

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...

A recent study, led by Sabre Kais, Distinguished Professor of Chemistry and professor of electrical and computer engineering at Purdue University, and IBM’s Barbara Jones, used a quantum computer to ...

Building on ES_APPM 420-1, this course covers advanced perturbation and asymptotic methods. They may include methods for ordinary differential equations (e.g. WKB method), for integrals (e.g.

This course teaches commonly used approximation methods in quantum mechanics. They include time-independent perturbation theory, time-dependent perturbation theory, tight binding method, variational ...

Is it possible for a deterministic system to be unpredictable? Although counter-intuitive, the answer is yes. Such systems are called “chaotic systems,” which are characterized by sensitive dependence ...

Asymptotic expansions of integrals. Regular and singular perturbation methods for ordinary and partial differential equations. Boundary layer theory. Matched asymptotic expansions. Homogenization. Two ...