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A series of stationary principles are developed for dynamical systems by formulating the concept of mixed convolved action, which is written in terms of mixed variables, using temporal convolutions and fractional derivatives. Dynamical…

Mathematical Physics · Physics 2015-06-03 Gary F. Dargush , Jinkyu Kim

Projects are finite terminating endeavors with distinctive outcomes, usually, occurring under transient conditions. Nevertheless, most estimation, planning, and scheduling approaches overlook the dynamics of project-based systems in…

Dynamical Systems · Mathematics 2017-11-06 Ricardo Antunes , Vicente A. González , Kenneth Walsh

We consider continuous-time dynamics for distributed optimization with set constraints in the paper. To handle the computational complexity of projection-based dynamics due to solving a general quadratic optimization subproblem with…

Optimization and Control · Mathematics 2022-06-24 Guanpu Chen , Peng Yi , Yiguang Hong , Jie Chen

We use kinetic Monte Carlo simulations to investigate current fluctuations in boundary driven generalized exclusion processes, in different dimensions. Simulation results are in full agreement with predictions based on the additivity…

Statistical Mechanics · Physics 2015-06-01 T. Becker , K. Nelissen , B. Cleuren

Direct numerical simulation of microscale fluid--structure interactions in multicomponent and multiphase flows requires methods that can represent moving boundaries together with fields constrained to evolving interfaces. Diffuse-domain…

Biological Physics · Physics 2026-05-14 Xinpeng Xu

We develop two-dimensional Brownian dynamics simulations to examine the motion of disks under thermal fluctuations and Hookean forces. Our simulations are designed to be experimental-like, since the experimental conditions define the…

Soft Condensed Matter · Physics 2017-05-26 Manuel Pancorbo , Miguel A. Rubio , P. Domínguez-García

Borrowing and extending the method of images we introduce a theoretical framework that greatly simplifies analytical and numerical investigations of the escape rate in open dynamical systems. As an example, we explicitly derive the exact…

Chaotic Dynamics · Physics 2013-06-28 Giampaolo Cristadoro , Georgie Knight , Mirko Degli Esposti

We present and solve a continuum theory of vacancy-mediated diffusion (as evidenced, for example, in the vacancy driven motion of tracers in crystals). Results are obtained for all spatial dimensions, and reveal the strongly non-gaussian…

Statistical Mechanics · Physics 2009-10-31 T. J. Newman

Over the years the field of non-Markovian stochastic processes and anomalous diffusion evolved from a specialized topic to mainstream theory, which transgressed the realms of physics to chemistry, biology and ecology. Numerous…

Statistical Mechanics · Physics 2021-01-14 Alessio Lapolla , Aljaz Godec

The evolution of a mixed quantum-classical system is expressed in the mapping formalism where discrete quantum states are mapped onto oscillator states, resulting in a phase space description of the quantum degrees of freedom. By defining…

Chemical Physics · Physics 2015-06-03 Aaron Kelly , Ramses van Zon , Jeremy Schofield , Raymond Kapral

Denoising diffusion probabilistic models have transformed image generation with their impressive fidelity and diversity. We show that they also excel in estimating optical flow and monocular depth, surprisingly, without task-specific…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Saurabh Saxena , Charles Herrmann , Junhwa Hur , Abhishek Kar , Mohammad Norouzi , Deqing Sun , David J. Fleet

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification.…

Computation · Statistics 2026-05-01 Jingning Yao , Ajay Jasra , Sheng Jiang

This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

This work presents a comprehensive framework for enhanced diffusion modeling in fluid-structure interactions by combining the Immersed Boundary Method (IBM) with stochastic trajectories and high-order spectral boundary conditions. Using…

Analysis of PDEs · Mathematics 2024-10-31 Rômulo Damasclin Chaves dos Santos , Jorge Henrique de Oliveira Sales

We consider the general class of time-homogeneous stochastic dynamical systems, both discrete and continuous, and study the problem of learning a representation of the state that faithfully captures its dynamics. This is instrumental to…

Machine Learning · Computer Science 2024-03-15 Vladimir R. Kostic , Pietro Novelli , Riccardo Grazzi , Karim Lounici , Massimiliano Pontil

This paper reports on a dynamic semantic mapping framework that incorporates 3D scene flow measurements into a closed-form Bayesian inference model. Existence of dynamic objects in the environment can cause artifacts and traces in current…

We propose a new approach to quantize the marginals of the discrete Euler diffusion process. The method is built recursively and involves the conditional distribution of the marginals of the discrete Euler process. Analytically, the method…

Probability · Mathematics 2015-05-25 Gilles Pagès , Abass Sagna

Drops on a free-flow/porous-medium-flow interface have a strong influence on the exchange of mass, momentum and energy between the two macroscopic flow regimes. Modeling droplet-related pore-scale processes in a macro-scale context is…

Computational Physics · Physics 2021-03-17 Sina Ackermann , Carina Bringedal , Rainer Helmig

Pore-scale simulations accurately describe transport properties of fluids in the subsurface. These simulations enhance our understanding of applications such as assessing hydrogen storage efficiency and forecasting CO$_2$ sequestration…

Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and applications. However, the adoption of existing models for multimodal and high-dimensional dependencies is…

Machine Learning · Statistics 2026-05-20 David Huk , Theodoros Damoulas
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