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Since its first successful applications in the early 2000s, x-ray Thomson scattering (XRTS) has emerged as one of the most successful tools for the diagnostics of extreme states of matter in the laboratory. By sampling the dynamic structure…

Plasma Physics · Physics 2026-04-28 Tobias Dornheim , Hannah Bellenbaum , Thomas Gawne , Jan Vorberger , Dirk O. Gericke

Predicting protein secondary structures such as alpha helices, beta sheets, and coils from amino acid sequences is essential for understanding protein function. This work presents a transformer-based model that applies attention mechanisms…

Artificial Intelligence · Computer Science 2025-12-10 Manzi Kevin Maxime

The lack of a mechanistic framework for chemical reactions forming inorganic extended solids presents a challenge to accelerated materials discovery. We demonstrate here a combined computational and experimental methodology to tackle this…

The Bayesian view of the brain hypothesizes that the brain constructs a generative model of the world, and uses it to make inferences via Bayes' rule. Although many types of approximate inference schemes have been proposed for hierarchical…

Neurons and Cognition · Quantitative Biology 2019-11-15 Shashwat Shukla , Hideaki Shimazaki , Udayan Ganguly

Small-angle scattering (SAS) is a key experimental technique for analyzing nano-scale structures in various materials.In SAS data analysis, selecting an appropriate mathematical model for the scattering intensity is critical, as it…

Data Analysis, Statistics and Probability · Physics 2024-01-22 Yui Hayashi , Shun Katakami , Shigeo Kuwamoto , Kenji Nagata , Masaichiro Mizumaki , Masato Okada

We propose a new framework to systematically incorporate data uncertainty in Gaussian Splatting. Being the new paradigm of neural rendering, Gaussian Splatting has been investigated in many applications, with the main effort in extending…

Graphics · Computer Science 2026-04-28 Doğa Yılmaz , Jialin Zhu , Deshan Gong , He Wang

To enhance the reflectivity of X-ray mirrors beyond the critical angle, multilayer coatings are required. Interface imperfections in the multilayer growth process are known to cause non-specular scattering and degrade the mirror optical…

Optics · Physics 2013-04-05 B. Salmaso , D. Spiga , R. Canestrari , L. Raimondi

Light-scattering in the terahertz region is demonstrated for granular matter. A quantum-cascade laser is used in a benchtop setup to determine the angle-dependent scattering of spherical grains as well as coffee powder and sugar grains. For…

Soft Condensed Matter · Physics 2014-05-26 Philip Born , Nick Rothbart , Matthias Sperl , Heinz-Wilhelm Hübers

We propose a novel approach to detect the binding between proteins making use of the anomalous diffraction of natively present heavy elements inside the molecule 3D structure. In particular, we suggest considering sulfur atoms contained in…

We study the statistical properties of the complex generalization of Wigner time delay $\tau_\text{W}$ for sub-unitary wave chaotic scattering systems. We first demonstrate theoretically that the mean value of the $\text{Re}[\tau_\text{W}]$…

Disordered Systems and Neural Networks · Physics 2021-11-15 Lei Chen , Steven M. Anlage , Yan V. Fyodorov

We have developed x-ray diffraction measurements with high energy-resolution and accuracy to study water structure at three different temperatures (7, 25 and 66 C) under normal pressure. Using a spherically curved Ge crystal an energy…

Soft Condensed Matter · Physics 2017-09-13 Congcong Huang , K. T. Wikfeldt , D. Nordlund , U. Bergmann , T. McQueen , J. Sellberg , L. G. M. Pettersson , A. Nilsson

Many aspects of the study of protein folding and dynamics have been affected by the recent advances in machine learning. Methods for the prediction of protein structures from their sequences are now heavily based on machine learning tools.…

Biological Physics · Physics 2019-11-25 Frank Noé , Gianni De Fabritiis , Cecilia Clementi

Grazing-Incidence Small-Angle X-ray Scattering (GISAXS) is a modern imaging technique used in material research to study nanoscale materials. Reconstruction of the parameters of an imaged object imposes an ill-posed inverse problem that is…

Machine Learning · Computer Science 2022-10-05 Maksim Zhdanov , Lisa Randolph , Thomas Kluge , Motoaki Nakatsutsumi , Christian Gutt , Marina Ganeva , Nico Hoffmann

We develop a Machine Learning Inversion method for analyzing scattering functions of mechanically driven polymers and extracting the corresponding feature parameters, which include energy parameters and conformation variables. The polymer…

Soft Condensed Matter · Physics 2025-11-21 Lijie Ding , Chi-Huan Tung , Bobby G. Sumpter , Wei-Ren Chen , Changwoo Do

In this paper, we extend a recently developed machine-learning (ML) based CREASE-2D method to analyze the entire two-dimensional (2D) scattering pattern obtained from small angle X-ray scattering measurements of supramolecular dipeptide…

Soft Condensed Matter · Physics 2025-04-08 Nitant Gupta , Sri V. V. R. Akepati , Simona Bianco , Jay Shah , Dave J. Adams , Arthi Jayaraman

We study nuclear reaction cross-sections for stable and unstable projectiles and targets within Glauber model, using densities obtained from various relativistic mean field formalisms. The calculated cross-sections are compared with the…

Nuclear Theory · Physics 2008-11-26 A. Shukla , B. K. Sharma , R. Chandra , P. Arumugam , S. K. Patra

The systematic discovery of outflows in the optical spectra of low-mass X-ray binaries opened a new avenue for the study of the outburst evolution in these extreme systems. However, the efficient detection of such features in a continuously…

High Energy Astrophysical Phenomena · Physics 2023-06-28 D. Mata Sánchez , T. Muñoz-Darias , J. Casares , M. Huertas-Company , G. Panizo-Espinar

Context. Scaling relations between cluster properties embody the formation and evolution of cosmic structure. Intrinsic scatters and correlations between X-ray properties are determined from merger history, baryonic processes, and dynamical…

Cosmology and Nongalactic Astrophysics · Physics 2019-12-04 Mauro Sereno , Stefano Ettori , Dominique Eckert , Paul Giles , Ben J. Maughan , Florian Pacaud , Marguerite Pierre , Patrick Valageas

A general machine learning architecture is introduced that uses wavelet scattering coefficients of an inputted three dimensional signal as features. Solid harmonic wavelet scattering transforms of three dimensional signals were previously…

Computational Physics · Physics 2019-01-30 Xavier Brumwell , Paul Sinz , Kwang Jin Kim , Yue Qi , Matthew Hirn