26 citations · 89 across the 6 of their papers we have counts for
6 papers
Information Bottleneck in Peptide Conformation Determination by X-ray Absorption Spectroscopy
Eemeli A. Eronen, Anton Vladyka, Florent Gerbon +2
We apply a recently developed technique utilizing machine learning for statistical analysis of computational nitrogen K-edge spectra of aqueous triglycine. This method, the emulato…
Towards Structural Reconstruction from X-Ray Spectra
Anton Vladyka, Christoph J. Sahle, Johannes Niskanen
We report a statistical analysis of Ge K-edge X-ray emission spectra simulated for amorphous GeO at elevated pressures. We find that employing machine learning approaches we ca…
Emulator-based Decomposition for Structural Sensitivity of Core-level Spectra
Johannes Niskanen, Anton Vladyka, Joonas Niemi +1
We explore the sensitivity of several core-level spectroscopic methods to the underlying atomistic structure by using the water molecule as our test system. We first define a metri…
Machine learning in interpretation of electronic core-level spectra
Johannes Niskanen, Anton Vladyka, J. Antti Kettunen +1
Electronic transitions involving core-level orbitals offer a localized, atomic-site and element specific peek window into statistical systems such as molecular liquids. Although fo…
High-Precision Determination of Oxygen-K Transition Energy Excludes Incongruent Motion of Interstellar Oxygen
M. A. Leutenegger, S. Kühn, P. Micke +25
We demonstrate a widely applicable technique to absolutely calibrate the energy scale of x-ray spectra with experimentally well-known and accurately calculable transitions of highl…
Disentangling Structural Information From Core-level Excitation Spectra
Johannes Niskanen, Christoph J. Sahle, Keith Gilmore +3
Core-level spectra of liquids can be difficult to interpret due to the presence of a range of local environments. We present computational methods for investigating core-level spec…