5 papers
Posterior Inference of Hamiltonian Parameters from RIXS Spectroscopy
Samuel Klein, Thomas M. Linker, Louis Conreux +14
We present the first application of simulation-based inference to resonant inelastic X-ray scattering spectroscopy. Using truncated marginal neural ratio estimation to efficiently…
Machine Learning Accelerated SSNEB for Efficient Minimum Energy Pathway Calculations
Yu Zhang, Guanzhi Li, Minkyung Han +4
Metastable states and their minimum energy pathways (MEPs) are central to understanding transformations and phase stability in complex materials, yet mapping transition pathways be…
Supercharging Simulation-Based Inference for Bayesian Optimal Experimental Design
Samuel Klein, Willie Neiswanger, Daniel Ratner +2
Bayesian optimal experimental design (BOED) seeks to maximize the expected information gain (EIG) of experiments. This requires a likelihood estimate, which in many settings is int…
Efficient Nudged Elastic Band Method using Neural Network Bayesian Algorithm Execution
Pranav Kakhandiki, Sathya Chitturi, Daniel Ratner +1
The discovery of a minimum energy pathway (MEP) between metastable states is crucial for scientific tasks including catalyst and biomolecular design. However, the standard nudged e…
Efficient Dynamic and Momentum Aperture Optimization for Lattice Design Using Multipoint Bayesian Algorithm Execution
Z. Zhang, I. Agapov, S. Gasiorowski +4
We demonstrate that multipoint Bayesian algorithm execution can overcome fundamental computational challenges in storage ring design optimization. Dynamic (DA) and momentum (MA) op…