8 citations · 9 across the 4 of their papers we have counts for
4 papers
Closed-loop machine learning for discovery of novel superconductors
Elizabeth A. Pogue, Alexander New, Kyle McElroy +15
The discovery of novel materials drives industrial innovation, although the pace of discovery tends to be slow due to the infrequency of "Eureka!" moments. These moments are typica…
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations
Alexander New, Benjamin Eng, Andrea C. Timm +1
In this work, we assess the ability of physics-informed neural networks (PINNs) to solve increasingly-complex coupled ordinary differential equations (ODEs). We focus on a pair of…
Neural Basis Functions for Accelerating Solutions to High Mach Euler Equations
David Witman, Alexander New, Hicham Alkendry +1
We propose an approach to solving partial differential equations (PDEs) using a set of neural networks which we call Neural Basis Functions (NBF). This NBF framework is a novel var…
Probability current and thermodynamics of open quantum systems
Benjamin Schumacher, Michael D. Westmoreland, Alexander New +1
This paper explores the generalization of the concept of a "probability current", familiar from wave-function quantum mechanics, to quantum systems with finite-dimensional Hilbert…