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Successful scientific applications of large-scale molecular dynamics often rely on automated methods for identifying the local crystalline structure of condensed phases. Many existing methods for structural identification, such as Common…

Materials Science · Physics 2016-05-24 Peter Mahler Larsen , Søren Schmidt , Jakob Schiøtz

Spectra of parametric X-ray radiation (PXR) are considered in the range of anomalous dispersion for one of the atoms in a crystal elementary cell. The PXR spectra are calculated both for the ultra-relativistic and non-relativistic electrons…

Materials Science · Physics 2007-05-23 I. D. Feranchuk , A. P. Ulyanenkov

Single Particle Imaging techniques at X-ray lasers have made significant strides, yet the challenge of determining the orientation of freely rotating molecules during delivery remains. In this study, we propose a novel method to partially…

Chemical Physics · Physics 2025-10-27 Tomas André , Emiliano De Santis , Nicusor Timneanu , Carl Caleman

A complete macromolecule modeling package must be able to solve the simplest structure prediction problems. Despite recent successes in high resolution structure modeling and design, the Rosetta software suite fares poorly on deceptively…

Biomolecules · Quantitative Biology 2011-06-08 Rhiju Das

A major challenge in materials science is the determination of the structure of nanometer sized objects. Here we present a novel approach that uses a generative machine learning model based on diffusion processes that is trained on 45,229…

Computational Physics · Physics 2024-11-01 Gabe Guo , Tristan Saidi , Maxwell Terban , Michele Valsecchi , Simon JL Billinge , Hod Lipson

The task of identifying resolving sets has been extensively studied due to its wide relevance in fields such as chemistry, robot navigation, combinatorial optimization, pattern recognition, and image processing. These applications have…

General Mathematics · Mathematics 2026-05-11 Ali Zafari , Saeid Alikhani

Robust Principal Component Analysis (RPCA) via rank minimization is a powerful tool for recovering underlying low-rank structure of clean data corrupted with sparse noise/outliers. In many low-level vision problems, not only it is known…

Computer Vision and Pattern Recognition · Computer Science 2019-02-18 Tae-Hyun Oh , Yu-Wing Tai , Jean-Charles Bazin , Hyeongwoo Kim , In So Kweon

The current state of the art in structural biology is led by NMR, X-ray crystallography and TEM investigations. These powerful tools however all rely on averaging over a large ensemble of molecules. Here, we present an alternative concept…

Atomic and Molecular Clusters · Physics 2015-12-15 Tatiana Latychevskaia , Jean-Nicolas Longchamp , Conrad Escher , Hans-Werner Fink

The large amount of powder diffraction data for which the corresponding crystal structures have not yet been identified suggests the existence of numerous undiscovered, physically relevant crystal structure prototypes. In this paper, we…

Materials Science · Physics 2024-10-31 Abhijith S. Parackal , Rhys E. A. Goodall , Felix A. Faber , Rickard Armiento

An extensive comparison of the path uncertainty in single particle tracking systems for ion imaging was carried out based on Monte Carlo simulations. The spatial resolution as function of system parameters such as geometry, detector…

Medical Physics · Physics 2021-02-24 A. Burker , T. Bergauer , A. Hirtl , C. Irmler , S. Kaser , B. Knäusl , F. Pitters , F. Ulrich-Pur

We have developed a powerful method for crystal structure prediction from "scratch" through particle swarm optimization (PSO) algorithm within the evolutionary scheme. PSO technique is dramatically different with the genetic algorithm and…

Materials Science · Physics 2012-05-11 Yanchao Wang , Jian Lv , Li Zhu , Yanming Ma

Experimentally obtained X-ray diffraction (XRD) patterns can be difficult to solve, precluding the full characterization of materials, pharmaceuticals, and geological compounds. Herein, we propose a method based upon a multi-objective…

Materials Science · Physics 2024-07-09 Stefano Racioppi , Alberto Otero De la Roza , Samad Hajinazar , Eva Zurek

Possible crystalline modifications of chemical compounds at low temperatures correspond to local minima of the energy landscape. Determining these minima via simulated annealing is one method for the prediction of crystal structures, where…

Materials Science · Physics 2008-10-31 K. Doll , J. C. Schoen , M. Jansen

Revealing the structure of complex biological macromolecules, such as proteins, is an essential step for understanding the chemical mechanisms that determine the diversity of their functions. Synchrotron based x-ray crystallography and…

The prediction of energetically stable crystal structures formed by a given chemical composition is a central problem in solid-state physics. In principle, the crystalline state of assembled atoms can be determined by optimizing the energy…

Materials Science · Physics 2022-06-01 Minoru Kusaba , Chang Liu , Ryo Yoshida

The application of powder diffraction methods in two-dimensional crystallography is regarded as intractable because of the uncertainties associated with overlapping reflections. Here, we report an approach that resolves these ambiguities…

Consider a projector matrix P, representing the first order reduced density matrix in a basis of orthonormal atom-centric basis functions. A mathematical question arises, and that is, how to break P into its natural component kernel…

Quantum Physics · Physics 2021-09-09 Cherif F. Matta , Lou Massa

The short and intense pulses of the new X-ray free electron lasers, now operational or under construction, may make possible diffraction experiments on single molecule-sized objects with high resolution, before radiation damage destroys the…

Data Analysis, Statistics and Probability · Physics 2012-04-11 Miklós Tegze , Gábor Bortel

We present a new method for modeling disordered solid solutions, based on the virtual crystal approximation (VCA). The VCA is a tractable way of studying configurationally disordered systems; traditionally, the potentials which represent…

Materials Science · Physics 2009-10-31 Nicholas J. Ramer , Andrew M. Rappe

L1-minimization refers to finding the minimum L1-norm solution to an underdetermined linear system b=Ax. Under certain conditions as described in compressive sensing theory, the minimum L1-norm solution is also the sparsest solution. In…

Computer Vision and Pattern Recognition · Computer Science 2012-08-28 Allen Y. Yang , Zihan Zhou , Arvind Ganesh , S. Shankar Sastry , Yi Ma