69 citations · 105 across the 5 of their papers we have counts for
5 papers
FluxGAN: A Physics-Aware Generative Adversarial Network Model for Generating Microstructures That Maintain Target Heat Flux
Artem K. Pimachev, Manoj Settipalli, Sanghamitra Neogi
We propose a physics-aware generative adversarial network model, FluxGAN, capable of simultaneously generating high-quality images of large microstructures and description of their…
Bidirectional Learning of Relationships between Atomic Environments and Electronic Band Dispersion in Semiconductor Heterostructures
Artem K Pimachev, Sanghamitra Neogi
Atomic-scale variations in semiconductor heterostructures, arising from strain, interfaces, and compositional modulation, strongly influence electronic band dispersion but remain d…
First-Principles Prediction of Electronic Transport in Experimental Semiconductor Heterostructures via Physics-Based Machine Learning
Artem K. Pimachev, Sanghamitra Neogi
First-principles techniques for electronic transport property prediction have seen rapid progress in recent years. However, it remains a challenge to model heterostructures incorpo…
Modulation of Semiconductor Superlattice Thermopower Through Symmetry and Strain
Vitaly. S. Proshchenko, Manoj Settipalli, Artem K. Pimachev +1
In doped semiconductors and metals, the thermopower decreases with increasing carrier concentration, in agreement with the Pisarenko relation. Here, we demonstrate a new strain eng…
Accuracy vs run time in adiabatic quantum search
A. T. Rezakhani, A. K. Pimachev, D. A. Lidar
Adiabatic quantum algorithms are characterized by their run time and accuracy. The relation between the two is essential for quantifying adiabatic algorithmic performance, yet is o…