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We introduce stochastic models for continuous-time evolution of angles and develop their estimation. We focus on studying Langevin diffusions with stationary distributions equal to well-known distributions from directional statistics, since…

In the last three decades, powerful computer-assisted techniques have been developed in order to validate a posteriori numerical solutions of semilinear elliptic problems of the form $\Delta u +f(u,\nabla u) = 0$. By studying a well chosen…

Analysis of PDEs · Mathematics 2022-03-02 Maxime Breden

Guided diffusion is a technique for conditioning the output of a diffusion model at sampling time without retraining the network for each specific task. One drawback of diffusion models, however, is their slow sampling process. Recent…

Computer Vision and Pattern Recognition · Computer Science 2023-01-30 Suttisak Wizadwongsa , Supasorn Suwajanakorn

(abridged) Imaging observations are generally affected by a fluctuating background of speckles, a particular problem when detecting faint stellar companions at small angular separations. Knowing the distribution of the speckle intensities…

Astrophysics · Physics 2009-11-13 Michael P. Fitzgerald , James R. Graham

Ultrafast-optical-pump -- structural-probe measurements, including ultrafast electron and x-ray scattering, provide direct experimental access to the fundamental timescales of atomic motion, and are thus foundational techniques for studying…

Modern optical flow methods make use of salient scene feature points detected and matched within the scene as a basis for sparse-to-dense optical flow estimation. Current feature detectors however either give sparse, non uniform point…

Computer Vision and Pattern Recognition · Computer Science 2019-05-21 Felix Stephenson , Toby Breckon , Ioannis Katramados

We propose a novel framework for the systematic design of lensless imaging systems based on the hyperuniform random field solutions of nonlinear reaction-diffusion equations from pattern formation theory. Specifically, we introduce a new…

Optics · Physics 2021-11-03 Yuyao Chen , Wesley A. Britton , Luca Dal Negro

The reported results for ultrasonic wave attenuation constant ({\alpha}) in pure water show noticeable inconsistency in magnitude. A "Propagating-Wave" model analysis of the most popular pulse-echo technique indicates that this is a…

Other Condensed Matter · Physics 2018-01-18 Barnana Pal

Spectral methods for solving partial differential equations (PDEs) and stochastic partial differential equations (SPDEs) often use Fourier or polynomial spectral expansions on either uniform and non-uniform grids. However, while very widely…

Numerical Analysis · Mathematics 2025-07-30 Channa Hatharasinghe , Run Yan Teh , Jesse van Rhijn , Peter D. Drummond , Margaret D. Reid

The spark plasma sintering (SPS) process, a key technology for advanced material manufacturing, demands accurate and efficient simulation tools to capture the complex electro-thermal-mechanical interactions inherent in powder materials.…

Computational Physics · Physics 2024-12-03 A. Kumar , Z. Zhang , M. Bambach , M. Afrasiabi

We present a real-time propagation method for computing linear and nonlinear optical properties of molecules based on the Bethe-Salpeter equation. The method follows the time evolution of the one-particle density matrix under an external…

Computational Physics · Physics 2025-09-29 Štěpán Marek , Jan Wilhelm

Image enhancement holds extensive applications in real-world scenarios due to complex environments and limitations of imaging devices. Conventional methods are often constrained by their tailored models, resulting in diminished robustness…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Yixuan Zhu , Wenliang Zhao , Ao Li , Yansong Tang , Jie Zhou , Jiwen Lu

We develop the Fourier-Laplace Inversion of the Perturbation Theory (FLIPT), a novel numerically exact "black box" method to compute perturbative expansions of the density matrix with rigorous convergence conditions. Specifically, the FLIPT…

Chemical Physics · Physics 2020-04-21 Cyrille Lavigne , Paul Brumer

We propose a new theoretical framework that exploits convolution kernels to transform a Volterra-type path-dependent (non-Markovian) stochastic process into a standard (Markovian) diffusion process. Remarkably, it is also possible to go…

Mathematical Finance · Quantitative Finance 2025-10-10 Ofelia Bonesini , Giorgia Callegaro , Martino Grasselli , Gilles Pagès

A Gaussian process (GP)-based methodology is proposed to emulate complex dynamical computer models (or simulators). The method relies on emulating the numerical flow map of the system over an initial (short) time step, where the flow map is…

Methodology · Statistics 2024-11-26 Hossein Mohammadi , Peter Challenor , Marc Goodfellow

Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle confined in an optical trap is generally modelled by the…

Data Analysis, Statistics and Probability · Physics 2017-02-01 Sudipta Bera , Shuvojit Paul , Rajesh Singh , Dipanjan Ghosh , Avijit Kundu , Ayan Banerjee , R. Adhikari

We demonstrate a strategy for simulating wide-range X-ray scattering patterns, which spans the small- and wide scattering angles as well as the scattering angles typically used for Pair Distribution Function (PDF) analysis. Such simulated…

Due to the nonlocal feature of fractional differential operators, the numerical solution to fractional partial differential equations usually requires expensive memory and computation costs. This paper develops a fast scheme for fractional…

Numerical Analysis · Mathematics 2025-03-21 Hao Yuan , Xiaoping Xie

X-ray free electron laser (XFEL) experiments have brought unique capabilities and opened new directions in research, such as creating new states of matter or directly measuring atomic motion. One such area is the ability to use finely…

The goal of this paper is to propose two nonlinear variational models for obtaining a refined motion estimation from an image sequence. Both the proposed models can be considered as a part of a generalized framework for an accurate…

Computer Vision and Pattern Recognition · Computer Science 2024-06-04 Hirak Doshi , N. Uday Kiran
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