English
Related papers

Related papers: Decoding Noise in Nanofluidic Systems: Adsorption …

200 papers

Data assimilation methodologies are designed to incorporate noisy observations of a physical system into an underlying model in order to infer the properties of the state of the system. Filters refer to a class of data assimilation…

Optimization and Control · Mathematics 2013-08-06 C. E. A. Brett , K. F. Lam , K. J. H. Law , D. S. McCormick , M. R. Scott , A. M. Stuart

Using molecular dynamics simulations, we study the motion of a closely fitting nanometer-size solid sphere in a fluid-filled cylindrical nanochannel at low Reynolds numbers and for a wide range of fluid-solid interactions corresponding to…

Soft Condensed Matter · Physics 2007-05-23 German Drazer , Boris Khusid , Joel Koplik , Andreas Acrivos

Diffuse Correlation Spectroscopy (DCS) allows the label-free investigation of microvascular dynamics deep within living tissue. However, common implementations of DCS are currently limited to measurement depths of $\sim 1-1.5cm$, which can…

We provide a general framework for learning diffusion bridges that transport prior to target distributions. It includes existing diffusion models for generative modeling, but also underdamped versions with degenerate diffusion matrices,…

Machine Learning · Computer Science 2025-08-14 Denis Blessing , Julius Berner , Lorenz Richter , Gerhard Neumann

The self-consistent field (SCF) generation of the three-dimensional (3D) electron density distribution ($\rho$) represents a fundamental aspect of density functional theory (DFT) and related first-principles calculations, and how one can…

Computational Physics · Physics 2024-11-19 Ryong-Gyu Lee , Yong-Hoon Kim

This paper investigates score-based diffusion models when the underlying target distribution is concentrated on or near low-dimensional manifolds within the higher-dimensional space in which they formally reside, a common characteristic of…

Machine Learning · Computer Science 2025-01-03 Gen Li , Yuling Yan

The power spectral density (PSD) is a central frequency-domain descriptor of stochastic processes. While PSDs have been studied for Brownian motion and a few anomalous diffusion processes, the spectral densities of active nonequilibrium…

Statistical Mechanics · Physics 2026-05-12 Yeongjin Kim , Gleb Oshanin , Jae-Hyung Jeon

Resistive Pulse Sensing (RPS) is a key label-free technology to measure particles and single-cell size distribution. As a growing corpus of evidence supports that cancer cells exhibit distinct mechanical phenotypes from healthy cells,…

Biological Physics · Physics 2020-04-01 Antoine Riaud , Anh L. P. Thai , Wei Wang , Valerie Taly

In this paper, we describe direct-sequence code-division multiple-access (DS-CDMA) systems with quadriphase-shift keying in which channel estimation, coherent demodulation, and decoding are iteratively performed without the use of any…

Information Theory · Computer Science 2016-11-18 Don Torrieri , Amitav Mukherjee , Hyuck Kwon

In many molecular systems one encounters the situation where electronic excitations couple to a quasi-continuum of phonon modes. That continuum may be highly structured e.g. due to some weakly damped high frequency modes. To handle such a…

Quantum Physics · Physics 2011-06-14 Jan Roden , Walter T. Strunz , Alexander Eisfeld

With a finite amount of measurement data acquired in variational quantum algorithms, the statistical benefits of several optimized numerical estimation schemes, including the scaled parameter-shift (SPS) rule and finite-difference (FD)…

Quantum Physics · Physics 2024-08-07 Yong Siah Teo

Score distillation sampling (SDS) has proven to be an important tool, enabling the use of large-scale diffusion priors for tasks operating in data-poor domains. Unfortunately, SDS has a number of characteristic artifacts that limit its…

Computer Vision and Pattern Recognition · Computer Science 2024-12-12 David McAllister , Songwei Ge , Jia-Bin Huang , David W. Jacobs , Alexei A. Efros , Aleksander Holynski , Angjoo Kanazawa

Snapshot hyperspectral imaging systems acquire spectral data cubes through compressed sensing. Recently, diffractive snapshot spectral imaging (DSSI) methods have attracted significant attention. While various optical designs and…

Image and Video Processing · Electrical Eng. & Systems 2025-07-08 Zhengyue Zhuge , Jiahui Xu , Shiqi Chen , Hao Xu , Yueting Chen , Zhihai Xu , Huajun Feng

Normalizing flows (NFs) have become a prominent method for deep generative models that allow for an analytic probability density estimation and efficient synthesis. However, a flow-based network is considered to be inefficient in parameter…

Machine Learning · Computer Science 2020-10-26 Sang-gil Lee , Sungwon Kim , Sungroh Yoon

Spectroscopy has played the key role in revealing, and thereby understanding, the structure of atoms and molecules. A central drive in this field is the pursuit of higher precision and accuracy so that ever more subtle effects might be…

Diffusion models have achieved remarkable success in generating high-resolution, realistic images across diverse natural distributions. However, their performance heavily relies on high-quality training data, making it challenging to learn…

Machine Learning · Computer Science 2025-05-22 Tianyu Chen , Yasi Zhang , Zhendong Wang , Ying Nian Wu , Oscar Leong , Mingyuan Zhou

An optical absorption spectrum constitutes one of the most fundamental material characteristics, with relevant applications ranging from material identification to energy harvesting and optoelectronics. However, the database of both…

Materials Science · Physics 2022-09-20 Ruo Xi Yang , Matthew K. Horton , Jason Munro , Kristin A. Persson

The spectral density (SD) function has a central role in the study of open quantum systems (OQSs). We discover a method allowing for a "static" measurement of the SD - i.e., it requires neither the OQS to be initially excited nor its time…

Quantum Physics · Physics 2015-06-24 Francesco Ciccarello

Score Distillation Sampling (SDS) and its variants have been widely used for text-to-3D generation by distilling 2D image diffusion priors. However, the standard SDS objective is prone to severe mode collapse, frequently yielding…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Rohith Ramanan , A. N. Rajagopalan

Synthesizing realistic microstructure images conditioned on processing parameters is crucial for understanding process-structure relationships in materials design. However, this task remains challenging due to limited training micrographs…

Materials Science · Physics 2025-11-21 Hoang Cuong Phan , Minh Tien Tran , Chihun Lee , Hoheok Kim , Sehyeok Oh , Dong-Kyu Kim , Ho Won Lee