[HTML][HTML] Structural biology in the age of X-ray free-electron lasers and exascale computing

S Mous, F Poitevin, MS Hunter, DN Asthagiri… - Current Opinion in …, 2024 - Elsevier
Serial femtosecond X-ray crystallography has emerged as a powerful method for
investigating biomolecular structure and dynamics. With the new generation of X-ray free …

On ultrafast x-ray scattering methods for magnetism

R Plumley, SR Chitturi, C Peng, TA Assefa… - … in Physics: X, 2024 - Taylor & Francis
With the introduction of x-ray free electron laser sources around the world, new scientific
approaches for visualizing matter at fundamental length and time-scales have become …

3D Heisenberg universality in the van der Waals antiferromagnet NiPS3

R Plumley, S Mardanya, C Peng, J Nokelainen… - npj Quantum …, 2024 - nature.com
Van der Waals (vdW) magnetic materials are comprised of layers of atomically thin sheets,
making them ideal platforms for studying magnetism at the two-dimensional (2D) limit. These …

Bayesian experimental design and parameter estimation for ultrafast spin dynamics

Z Chen, C Peng, AN Petsch, SR Chitturi… - Machine Learning …, 2023 - iopscience.iop.org
Advanced experimental measurements are crucial for driving theoretical developments and
unveiling novel phenomena in condensed matter and materials physics, which often suffer …

Enhancing Accuracy and Parameter-Efficiency of Neural Representations for Network Parameterization

H Choi, JJ Thiagarajan, R Glatt, S Liu - arXiv preprint arXiv:2407.00356, 2024 - arxiv.org
In this work, we investigate the fundamental trade-off regarding accuracy and parameter
efficiency in the parameterization of neural network weights using predictor networks. We …

Implicit neural representations for experimental steering of advanced experiments

Z Chen, AN Petsch, Z Ji, SR Chitturi, C Peng… - Cell Reports Physical …, 2024 - cell.com
Scattering measurements using electrons, neutrons, or photons are essential for obtaining
microscopic insights into materials. However, limited facility availability and high …

Uncovering Obscured Phonon Dynamics from Powder Inelastic Neutron Scattering using Machine Learning

Y Su, C Li - arXiv preprint arXiv:2404.13507, 2024 - arxiv.org
The study of phonon dynamics is pivotal for understanding material properties, yet it faces
challenges due to the irreversible information loss inherent in powder inelastic neutron …

Hyper-Compression: Model Compression via Hyperfunction

F Fan, J Fan, D Wang, J Zhang, Z Dong… - arXiv preprint arXiv …, 2024 - arxiv.org
The rapid growth of large models' size has far outpaced that of GPU memory. To bridge this
gap, inspired by the succinct relationship between genotype and phenotype, we turn the …

Machine learning enabled experimental design and parameter estimation for ultrafast spin dynamics

Z Chen, C Peng, AN Petsch, SR Chitturi… - arXiv preprint arXiv …, 2023 - arxiv.org
Advanced experimental measurements are crucial for driving theoretical developments and
unveiling novel phenomena in condensed matter and material physics, which often suffer …

Data-Driven Techniques for Materials Characterization and Intelligent Experimental Design at Advanced Scattering Facilities

SR Chitturi - 2024 - search.proquest.com
This dissertation addresses the need to accelerate materials discovery, particularly within
the context of advanced scattering facilities. The complexity of materials discovery arises …