13 papers · 1 filter
mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials
Sourav Mal, Satadeep Bhattacharjee
Magnetic order in crystals is governed by moment-carrying sublattices and ligand-mediated exchange pathways, yet standard crystal graph neural networks treat all atoms homogeneousl…
SR-CGCNN: Shared Recurrent Convolution in Crystal Graph Neural Networks for Materials Property Prediction
Satadeep Bhattacharjee
Crystal graph neural networks predict materials properties by propagating information through local atomic environments. In conventional crystal graph convolutional neural networks…
Uncertainty-Aware Symbolic Regression through Bayesian Support Selection
Satadeep Bhattacharjee
The Sure Independence Screening and Sparsifying Operator (SISSO) framework is a powerful symbolic-regression method for extracting compact and interpretable descriptors from large…
Testing the spin-bath view of self-attention: A Hamiltonian analysis of GPT-2 Transformer
Satadeep Bhattacharjee, Seung-Cheol Lee
The recently proposed physics-based framework by Huo and Johnson~\cite{huo2024capturing} models the attention mechanism of Large Language Models (LLMs) as an interacting two-body s…
Local Symmetry Breaking in Skyrmion-Hosting Centrosymmetric Hexagonal Compounds
Anupam K. Singh, Krishna K. Dubey, Parul Devi +10
Dzyaloshinskii-Moriya interaction (DMI) plays a crucial role in stabilizing the exotic topologically stable skyrmion spin textures in the noncentrosymmetric crystals. The recent di…
Enhancement of spin Hall angle by an order of magnitude via Cu intercalation in MoS/CoFeB heterostructures
Abhisek Mishra, Pritam Das, Rupalipriyadarsini Chhatoi +7
Transition metal dichalcogenides (TMDs) are a novel class of quantum materials with significant potential in spintronics, optoelectronics, valleytronics, and opto-valleytronics. TM…