Related papers: XrdML, a new way to store (and exchange) X-ray pow…
Machine learning has been applied to the problem of X-ray diffraction phase prediction with promising results. In this paper, we describe a method for using machine learning to predict crystal structure phases from X-ray diffraction data of…
The classical method of determining the atomic structure of complex molecules by analyzing diffraction patterns is currently undergoing drastic developments. Modern techniques for producing extremely bright and coherent X-ray lasers allow a…
In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…
Monitoring large clusters is a challenging problem. It is necessary to observe a large quantity of devices with a reasonably short delay between consecutive observations. The set of monitored devices may include PCs, network switches, tape…
We report on a new general relativistic computational model enhancing, in various respects, the capability of presently available tools for fitting spectra of X-ray sources. The new model is intended for spectral analysis of black-hole…
We propose a diffusion distillation method that achieves new state-of-the-art in one-step/few-step 1024px text-to-image generation based on SDXL. Our method combines progressive and adversarial distillation to achieve a balance between…
With the advent of both modern X-ray fluorescence (XRF) methods and improved analytical reliability requirements the demand for suitable reference samples has increased. Especially in nanotechnology with the very low areal mass depositions,…
Norm-conserving pseudopotentials are used by a significant number of electronic-structure packages, but the practical differences among codes in the handling of the associated data hinder their interoperability and make it difficult to…
X-ray interaction with matter is an energy-dependent process that is contingent on the atomic structure of the constituent material elements. The most advanced models to capture this relationship currently rely on Monte Carlo (MC)…
The RDF Mapping Language (RML) enables, among other formats, the mapping of tabular data as Comma-Separated Values (CSV) files to RDF graphs. Unfortunately, the widely used spreadsheet format is currently neglected by its specification and…
This paper explores the development and testing of a simple absorption correction model for processing x-ray powder diffraction data from Debye-Scherrer geometry laboratory x-ray experiments. This may be used as a pre-processing step before…
The XMM identification (XID) programme is accumulating Optical/IR data to identify thousands of XMM sources at both high ($bII > 20^{\circ}$) and low galactic latitude. X-ray sources are divided into samples on the basis of their X-ray flux…
XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native-XML database management systems (DBMSs) currently bear limited performances and it is necessary to research for ways…
We introduce a new, open-source, Python module for the acquisition and processing of archival data from many X-ray telescopes - Democratising Archival X-ray Astronomy (hereafter referred to as DAXA). Our software is built to increase access…
We introduce the Linearized Diffusion Map (LDM), a novel linear dimensionality reduction method constructed via a linear approximation of the diffusion-map kernel. LDM integrates the geometric intuition of diffusion-based nonlinear methods…
X-ray free-electron lasers (XFELs) have been widely used for applications such as X-ray crystallography and magnetic spin probes because of their unprecedented performance. Recently, time-resolved X-ray magnetic circular dichroism (XMCD)…
Planetary rovers can use onboard data analysis to adapt their measurement plan on the fly, improving the science value of data collected between commands from Earth. This paper describes the implementation of an adaptive sampling algorithm…
Machine Learning has become the bedrock of recent advances in text, image, video, and audio processing and generation. Most production systems deal with several models during deployment and training, each with a variety of tuned…
The intersection of physics and machine learning has given rise to the physics-enhanced machine learning (PEML) paradigm, aiming to improve the capabilities and reduce the individual shortcomings of data- or physics-only methods. In this…
We used a microfluidic platform to address the problems of obtaining diffraction quality crystals and crystal handling during transfer to the X-ray diffractometer. We optimize crystallization conditions of a pharmaceutical protein and…