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Data-dependent metrics are powerful tools for learning the underlying structure of high-dimensional data. This article develops and analyzes a data-dependent metric known as diffusion state distance (DSD), which compares points using a…

Machine Learning · Statistics 2020-03-10 Lenore Cowen , Kapil Devkota , Xiaozhe Hu , James M. Murphy , Kaiyi Wu

Differential dynamic microscopy (DDM) is increasingly used in the fields of soft matter physics and biophysics to extract the dynamics of microscopic objects across a range of wavevectors using optical microscopy. Standard DDM is limited to…

Soft Condensed Matter · Physics 2021-02-24 Ruilin You , Ryan McGorty

Particle tracking microrheology (PT-$\mu$r) exploits the thermal motion of embedded particles to probe the local mechanical properties of soft materials. Despite its appealing conceptual simplicity, PT-$\mu$r requires calibration procedures…

Soft Condensed Matter · Physics 2018-01-03 Paolo Edera , Davide Bergamini , Véronique Trappe , Fabio Giavazzi , Roberto Cerbino

The results obtained using my computing program are consistent with the values obtained twenty years ago. It also makes me believe that how to obtain particle size information using the Light Scattering technique needs to be reconsidered.…

Chemical Physics · Physics 2024-06-21 Yong Sun

We present a model of x-ray thermal diffuse scattering (TDS) from a cubic polycrystal with an arbitrary crystallographic texture, based on the classic approach of Warren. We compare the predictions of our model with femtosecond x-ray…

Applied Physics · Physics 2025-08-07 P. G. Heighway , D. J. Peake , T. Stevens , J. S. Wark , B. Albertazzi , S. J. Ali , L. Antonelli , M. R. Armstrong , C. Baehtz , O. B. Ball , S. Banerjee , A. B. Belonoshko , C. A. Bolme , V. Bouffetier , R. Briggs , K. Buakor , T. Butcher , S. Di Dio Cafiso , V. Cerantola , J. Chantel , A. Di Cicco , A. L. Coleman , J. Collier , G. Collins , A. J. Comley , F. Coppari , T. E. Cowan , G. Cristoforetti , H. Cynn , A. Descamps , F. Dorchies , M. J. Duff , A. Dwivedi , C. Edwards , J. H. Eggert , D. Errandonea , G. Fiquet , E. Galtier , A. Laso Garcia , H. Ginestet , L. Gizzi , A. Gleason , S. Goede , J. M. Gonzalez , M. G. Gorman , M. Harmand , N. Hartley , C. Hernandez-Gomez , A. Higginbotham , H. Höppner , O. S. Humphries , R. J. Husband , T. M. Hutchinson , H. Hwang , D. A. Keen , J. Kim , P. Koester , Z. Konopkova , D. Kraus , A. Krygier , L. Labate , A. E. Lazicki , Y. Lee , H-P. Liermann , P. Mason , M. Masruri , B. Massani , E. E. McBride , C. McGuire , J. D. McHardy , D. McGonegle , R. S. McWilliams , S. Merkel , G. Morard , B. Nagler , M. Nakatsutsumi , K. Nguyen-Cong , A-M. Norton , I. I. Oleynik , C. Otzen , N. Ozaki , S. Pandolfi , A. Pelka , K. A. Pereira , J. P. Phillips , C. Prescher , T. Preston , L. Randolph , D. Ranjan , A. Ravasio , J. Rips , D. Santamaria-Perez , D. J. Savage , M. Schoelmerich , J-P. Schwinkendorf , S. Singh , J. Smith , R. F. Smith , A. Sollier , J. Spear , C. Spindloe , M. Stevenson , C. Strohm , T-A. Suer , M. Tang , M. Toncian , T. Toncian , S. J. Tracy , A. Trapananti , T. Tschentscher , M. Tyldesley , C. E. Vennari , T. Vinci , S. C. Vogel , T. J. Volz , J. Vorberger , J. T. Willman , L. Wollenweber , U. Zastrau , E. Brambrink , K. Appel , M. I. McMahon

Diffusion models are typically trained using pointwise reconstruction objectives that are agnostic to the spectral and multi-scale structure of natural signals. We propose a loss-level spectral regularization framework that augments…

Machine Learning · Computer Science 2026-03-04 Satish Chandran , Nicolas Roque dos Santos , Yunshu Wu , Greg Ver Steeg , Evangelos Papalexakis

We study a dispersive counterpart of the classical gas dynamics problem of the interaction of a shock wave with a counter-propagating simple rarefaction wave often referred to as the shock wave refraction. The refraction of a…

Pattern Formation and Solitons · Physics 2015-05-28 G. A. El , V. V. Khodorovskii , A. M. Leszczyszyn

Background: Windowed Fourier decompositions (WFD) are widely used in measuring stationary and non-stationary spectral phenomena and in describing pairwise relationships among multiple signals. Although a variety of WFDs see frequent…

Quantitative Methods · Quantitative Biology 2019-01-30 Christopher K. Kovach , Phillip E. Gander

Diffusion models have demonstrated exceptional performances in various fields of generative modeling, but suffer from slow sampling speed due to their iterative nature. While this issue is being addressed in continuous domains, discrete…

Machine Learning · Computer Science 2025-05-12 Satoshi Hayakawa , Yuhta Takida , Masaaki Imaizumi , Hiromi Wakaki , Yuki Mitsufuji

Scattering of electronic waves in square and triangular lattice half-planes by a step on the surface is analyzed using the nearest-neighbour tight binding approximation. The changes in lattice spacing and the transfer integral between…

Mesoscale and Nanoscale Physics · Physics 2019-09-04 Basant Lal Sharma

Defects in solid-state materials play a central role in determining coherence, stability, and performance in quantum technologies. Although narrowband techniques can probe specific resonances with high precision, a broadband spectroscopic…

Diffuse correlation spectroscopy (DCS) is a noninvasive optical technique that probes microvascular blood flow in deep tissues. Here, we present and validate a new on-chip hardware correlator for high-speed DCS measurements. The correlator…

The diffusive properties in velocity fields whose small scales are parameterized by non $\delta$-correlated noise is investigated using multiscale technique. The analytical expression of the eddy diffusivity tensor is found for a 2D steady…

Condensed Matter · Physics 2009-10-31 P. Castiglione , A. Crisanti

Plane wave imaging (PWI) in medical ultrasound is becoming an important reconstruction method with high frame rates and new clinical applications. Recently, single PWI based on deep learning (DL) has been studied to overcome lowered frame…

Image and Video Processing · Electrical Eng. & Systems 2023-11-21 Hyunwoo Cho , Seongjun Park , Jinbum Kang , Yangmo Yoo

Currently, methods for single-image deblurring based on CNNs and transformers have demonstrated promising performance. However, these methods often suffer from perceptual limitations, poor generalization ability, and struggle with heavy or…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Xiaoyang Liu , Yuquan Wang , Zheng Chen , Jiezhang Cao , He Zhang , Yulun Zhang , Xiaokang Yang

Van der Waals (vdW) semiconductors have emerged as promising platforms for efficient nonlinear optical conversion, including harmonic and entangled photon generation. Although major efforts are devoted to integrating vdW materials in…

We present the full classification of wave patterns evolving from an initial step-like discontinuity for arbitrary choice of boundary conditions at the discontinuity location in the DNLS equation theory. In this non-convex dispersive…

Pattern Formation and Solitons · Physics 2018-01-22 A. M. Kamchatnov

Diffusivity is a key quantity in describing velocity fluctuations in granular materials. These fluctuations are the basis of many thermodynamic and hydrodynamic models which aim to provide a statistical description of granular systems. We…

Soft Condensed Matter · Physics 2009-11-10 Brian Utter , R. P. Behringer

We study the diffusion of monochromatic classical waves in a disordered acoustic medium by scattering theory. In order to avoid artifacts associated with mathematical point scatterers, we model the randomness by small but finite insertions.…

Disordered Systems and Neural Networks · Physics 2009-11-11 Sijmen Gerritsen , Gerrit E. W. Bauer

Hydroelastic surface waves propagate at the surface of water covered by a thin elastic sheet and can be directly measured with accurate space and time resolution. We present an experimental approach using hydroelastic waves that allows us…

Fluid Dynamics · Physics 2019-02-04 Lucie Domino , M. Fermigier , E. Fort , A. Eddi