1 citations · 1 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2026
Agentic multi-fidelity learning of quasiparticle and excitonic properties
Arnab Neogi, Aaron Forde, Christopher A. Lane +2
Many-body GW-Bethe-Salpeter equation calculations are essential for accurate simulations of electronic structure and optical properties in modern low-dimensional nanomaterials. How…
cond-mat.dis-nn2025★ 1 cited
Deep Generative Learning of Magnetic Frustration in Artificial Spin Ice from Magnetic Force Microscopy Images
Arnab Neogi, Suryakant Mishra, Prasad P Iyer +5
Increasingly large datasets of microscopic images with atomic resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena em…