5 papers
XANE(3): An E(3)-Equivariant Graph Neural Network for Accurate Prediction of XANES Spectra from Atomic Structures
Vitor F. Grizzi, Luke N. Pretzie, Jiayi Xu +1
We present XANE(3), a physics-based E(3)-equivariant graph neural network for predicting X-ray absorption near-edge structure (XANES) spectra directly from atomic structures. The m…
ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation
Vitor F. Grizzi, Thang Duc Pham, Luke N. Pretzie +3
Computational X-ray absorption near-edge structure (XANES) is widely used to interpret local coordination environments, oxidation states, and electronic structure, but large comput…
Recent Developments and Perspectives in Variational Quantum Eigensolvers for Molecular Electronic Structure: Methods, Tradeoffs, and Benchmarking
Taylor Harville, Rishu Khurana, Vitor F. Grizzi +1
The variational quantum eigensolver (VQE) is a hybrid quantum-classical algorithm designed for noisy intermediate-scale quantum (NISQ) hardware to estimate eigenvalues of many-body…
NuGraph2 with Explainability: Post-hoc Explanations for Geometric Neural Network Predictions
Margaret Voetberg, Vitor F. Grizzi, Giuseppe Cerati +2
With the growing popularity of artificial intelligence used for scientific applications, the ability of attribute a result to a reasoning process from the network is in high demand…
NuGraph2 with Context-Aware Inputs: Physics-Inspired Improvements in Semantic Segmentation
Vitor F. Grizzi, Margaret Voetberg, V Hewes +2
Graph neural networks have recently shown strong promise for event reconstruction tasks in Liquid Argon Time Projection Chambers, yet their performance remains limited for underrep…